Cloud-based healthcare analytics to link resource acquisition behavior with localized utilization trends across larger data sets

Abstract

To improve medical treatment of a patient.SOLUTION: A cloud-based analytics medical system comprises a processor, a memory, an input / output interface to access data from medical hub communication devices, each coupled to a surgical instrument, and a database to store the data. The processor aggregates patient outcome data from the medical hubs. The patient outcome data comprises data pertaining to steps performed and corresponding timings for each step in patient procedures, data pertaining to an outcome of each patient procedure performed, and data pertaining to medical resources used in the patient procedures. The patient outcome data comprises location data describing which medical facility the medical resource is allocated to and data indicating whether the outcome is a success or failure. The processor aggregates medical resource acquisition data from the medical hubs, determines correlation between positive outcomes and the resource acquisition data, generates medical recommendations based on the correlation, and displays the medical recommendations on medical hubs located at different medical facilities.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] (CROSS REFERENCE TO RELATED APPLICATIONS) This application claims the benefit of priority under 35 U.S.C. §119(e) to U.S. Provisional Application No. 62 / 649,333, filed March 28, 2018, entitled "CLOUD-BASED MEDICAL ANALYTICS FOR CUSTOMIZATION AND RECOMMENDATIONS TO A USER," the disclosure of which is incorporated herein by reference in its entirety.

[0002] This application further claims the benefit of priority under 35 U.S.C. §119(e) to U.S. Provisional Patent Application No. 62 / 611,341, entitled "INTERACTIVE SURGICAL PLATFORM," filed December 28, 2017, U.S. Provisional Patent Application No. 62 / 611,340, entitled "CLOUD-BASED MEDICAL ANALYTICS," filed December 28, 2017, and U.S. Provisional Patent Application No. 62 / 611,339, entitled "ROBOT ASSISTED SURGICAL PLATFORM," filed December 28, 2017, the disclosures of each of which are incorporated herein by reference in their entireties. [Background technology]

[0003] The present disclosure relates to various surgical systems. In the digital information age, medical systems and facilities are often slower to implement systems or procedures utilizing newer and improved technologies due to the general desire to maintain patient safety and traditional practices. However, medical systems and facilities often, as a result, may lack communication and shared knowledge with other nearby or similarly situated facilities. Summary of the Invention [Problem to be solved by the invention]

[0004] It would be desirable to find ways to facilitate the interconnection of healthcare systems and facilities to improve patient care. [Means for solving the problem]

[0005] In one general aspect, a cloud-based analytical medical system is provided. The cloud-based analytical medical system includes at least one processor, at least one memory communicatively coupled to the at least one processor, an input / output interface configured to access data from a plurality of medical hub communication devices, each communicatively coupled to at least one surgical instrument, and a database resident in the at least one memory and configured to store data. The at least one memory stores instructions executable by the at least one processor to aggregate patient outcome data from the plurality of medical hubs. The patient outcome data includes data regarding steps performed in a patient procedure and corresponding timing of each step, data regarding outcomes of each patient procedure performed, and data regarding medical resources used in the patient procedure. The patient outcome data also includes, for each data item regarding the medical resources, location data describing the medical facility to which the medical resources were assigned, and, for each data item regarding outcomes of the patient procedure, data regarding an indication of whether the outcome is a success or failure. The at least one memory further stores instructions executable by the at least one processor to aggregate medical resource acquisition data from the multiple medical hubs, determine a correlation between positive outcomes from the patient outcome data and the resource acquisition data, generate medical suggestions for modifying medical resource acquisition practices based on the correlation, and display the medical suggestions on the multiple medical hubs located in the different medical facilities.

[0006] In another general aspect, a computer-readable medium is provided. The computer-readable medium is non-transitory and stores computer-readable instructions executable by at least one processor of a cloud-based analysis system for aggregating patient outcome data from a plurality of medical hubs. The patient outcome data includes data regarding steps performed in a patient procedure and corresponding timing of each step, data regarding outcomes of each patient procedure performed, data regarding medical resources used in the patient procedure, and for each data item regarding the medical resources, location data describing the medical facility to which the medical resource was assigned, and for each data item regarding the outcome of the patient procedure, data regarding an indication of whether the outcome is successful or unsuccessful. The executable instructions also aggregate the medical resource acquisition data from the plurality of medical hubs, determine a correlation between a positive outcome from the patient outcome data and the resource acquisition data, generate a medical suggestion for modifying medical resource acquisition practices based on the correlation, and cause the medical suggestion to be displayed on a plurality of medical hubs located in different medical facilities.

[0007] In yet another general aspect, another cloud-based analysis medical system is provided. The cloud-based analysis medical system includes at least one processor, at least one memory communicatively coupled to the at least one processor, an input / output interface configured to access data from a plurality of medical hub communication devices, each communicatively coupled to at least one surgical instrument, and a database resident in the at least one memory and configured to store data. The at least one memory stores instructions executable by the at least one processor to aggregate the medical instrument data from the plurality of medical hubs. The medical instrument data includes data related to physical and performance parameters of the medical instrument, and for each data related to the medical instrument, usage data related to a medical procedure utilizing the medical instrument, and for each medical procedure, an outcome of the medical procedure, and a status of the condition of the medical instrument during the medical procedure. The at least one memory stores instructions executable by the at least one processor to determine a correlation between outcomes of the medical procedures and a status of a condition of a medical device utilized in each medical procedure; access live medical procedure data for the current medical procedure, the live medical procedure data including a description of the medical device in the operating room in which the current medical procedure is being performed; determine an irregularity in the description of the medical device in the current medical procedure based on the determined correlation between the outcomes and the medical device utilized; and provide an alert to a medical communication hub utilized in the operating room of the current medical procedure. [Brief description of the drawings]

[0008] The features of the various aspects are set forth in detail in the appended claims, however the various aspects, both as to organization and method of operation, together with further objects and advantages thereof, may best be understood by reference to the following description taken in conjunction with the accompanying drawings in which: [Figure 1]FIG. 1 is a block diagram of a computer-implemented interactive surgical system according to at least one aspect of the present disclosure. [Diagram 2] 1 is a surgical system used to perform a surgical procedure in an operating room, according to at least one embodiment of the present disclosure. [Diagram 3] 1 is a surgical hub paired with a visualization system, a robotic system, and an intelligent instrument according to at least one aspect of the present disclosure. [Figure 4] FIG. 13 is a partial perspective view of a surgical hub housing and a combination generator module slidably receivable within a drawer of the surgical hub housing, according to at least one embodiment of the present disclosure. [Diagram 5] FIG. 1 illustrates a perspective view of a combination generator module including bipolar, ultrasonic, and monopolar contacts and smoke evacuation components according to at least one embodiment of the present disclosure. [Figure 6] 1 illustrates individual power bus attachments for multiple lateral docking ports of a lateral modular housing configured to receive multiple modules, according to at least one embodiment of the present disclosure. [Figure 7] 1 illustrates a vertical modular housing configured to receive a plurality of modules, according to at least one embodiment of the present disclosure. [Figure 8] 1 illustrates a surgical data network comprising a modular communications hub configured to connect modular devices located in one or more operating rooms of a medical facility, or any room in a medical facility equipped with specialized equipment for surgical procedures, to a cloud, in accordance with at least one aspect of the present disclosure. [Figure 9] 1 illustrates a computer-implemented interactive surgical system according to at least one aspect of the present disclosure. [Figure 10] 1 illustrates a surgical hub comprising a plurality of modules coupled to a modular control tower in accordance with at least one embodiment of the present disclosure. [Figure 11] 1 illustrates one embodiment of a Universal Serial Bus (USB) network hub device in accordance with at least one embodiment of the present disclosure. [Figure 12] 1 illustrates a logic diagram of a control system for a surgical instrument or tool, according to at least one embodiment of the present disclosure. [Figure 13] 1 illustrates a control circuit configured to control an aspect of a surgical instrument or tool, according to at least one aspect of the present disclosure. [Figure 14] 1 illustrates a combinatorial logic circuit configured to control aspects of a surgical instrument or tool, according to at least one aspect of the present disclosure. [Figure 15] 1 illustrates a sequential logic circuit configured to control aspects of a surgical instrument or tool, in accordance with at least one aspect of the present disclosure. [Figure 16] 1 illustrates a surgical instrument or tool with multiple motors that can be activated to perform various functions, in accordance with at least one aspect of the present disclosure. [Figure 17] FIG. 1 is a circuit diagram of a robotic surgical instrument configured to manipulate a surgical tool described herein, in accordance with at least one aspect of the present disclosure. [Figure 18] FIG. 1 illustrates a block diagram of a surgical instrument programmed to control distal translation of a displacement member, in accordance with at least one embodiment of the present disclosure. [Figure 19] FIG. 1 is a circuit diagram of a surgical instrument configured to control various functions, according to at least one embodiment of the present disclosure. [Figure 20] FIG. 1 is a simplified block diagram of a generator configured to provide inductorless tuning, among other advantages, in accordance with at least one aspect of the present disclosure. [Figure 21] 21 illustrates an example of a generator, which is a form of the generator of FIG. 20, in accordance with at least one embodiment of the present disclosure. [Figure 22] FIG. 1 is a block diagram of a computer-implemented interactive surgical system according to at least one aspect of the present disclosure. [Figure 23] FIG. 1 is a block diagram illustrating a functional architecture of a computer-implemented interactive surgical system in accordance with at least one aspect of the present disclosure. [Figure 24]FIG. 13 is an exemplary diagram of a compilation of various resources related to a particular type of surgical classification, in accordance with at least one embodiment of the present disclosure. [Diagram 25] 1 provides an example illustration of how data is analyzed by a cloud system to provide comparisons between multiple facilities to compare resource usage, according to at least one aspect of the present disclosure. [Figure 26] 1 illustrates an example of how a cloud system may determine effectiveness trends from a set of aggregated data across domains, in accordance with at least one aspect of the present disclosure. [Figure 27] An exemplary illustration of several types of analytics, in accordance with at least one aspect of the present disclosure, is presented, which the cloud system may be configured to execute to provide predictive modeling. [Figure 28] An illustration of one example analysis is provided, in accordance with at least one aspect of the present disclosure, and a cloud system may be implemented to provide these suggestions. [Figure 29] In accordance with at least one aspect of the present disclosure, a description is presented of how the cloud system performs analysis to identify statistical correlations to local problems that are tied to how devices are used in localized settings. [Diagram 30] In accordance with at least one aspect of the present disclosure, an illustration of an example is presented of how some devices may satisfy equivalent use compared to an intended device, and how a cloud system may determine such equivalent use. [Diagram 31] In accordance with at least one aspect of the present disclosure, various examples are presented of how some data may be used as variables in determining how a post-operative decision tree may branch. [Diagram 32] 1 is a timeline illustrating situational awareness of a surgical hub, in accordance with at least one embodiment of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] The applicant of this application owns the following U.S. provisional patent applications, filed March 28, 2018, the disclosures of each of which are incorporated by reference in their entirety herein: · U.S. Provisional Patent Application No. 62 / 649,302, entitled "INTERACTIVE SURGICAL SYSTEMS WITH ENCRYPTED COMMUNICATION CAPABILITIES"; · U.S. Provisional Patent Application No. 62 / 649,294, entitled "DATA STRIPPING METHOD TO INTERROGATE PATIENT RECORDS AND CREATE ANONYMIZED RECORD"; · U.S. Provisional Patent Application No. 62 / 649,300, entitled “SURGICAL HUB SITUATIONAL AWARENESS”; · U.S. Provisional Patent Application No. 62 / 649,309, entitled “SURGICAL HUB SPATIAL AWARENESS TO DETERMINE DEVICES IN OPERATING THEATER”; · U.S. Provisional Patent Application No. 62 / 649,310, entitled “COMPUTER IMPLEMENTED INTERACTIVE SURGICAL SYSTEMS”; U.S. Provisional Patent Application No. 62 / 649,291, entitled “USE OF LASER LIGHT AND RED-GREEN-BLUE COLORATION TO DETERMINE PROPERTIES OF BACK SCATTERED LIGHT”; U.S. Provisional Patent Application No. 62 / 649,296, entitled "ADAPTIVE CONTROL PROGRAM UPDATES FOR SURGICAL DEVICES"; · U.S. Provisional Patent Application No. 62 / 649,333, entitled "CLOUD-BASED MEDICAL ANALYTICS FOR CUSTOMIZATION AND RECOMMENDATIONS TO A USER"; U.S. Provisional Patent Application No. 62 / 649,327, entitled "CLOUD-BASED MEDICAL ANALYTICS FOR SECURITY AND AUTHENTICATION TRENDS AND REACTIVE MEASURES"; · U.S. Provisional Patent Application No. 62 / 649,315, entitled "DATA HANDLING AND PRIORITIZATION IN A CLOUD ANALYTICS NETWORK"; U.S. Provisional Patent Application No. 62 / 649,313, entitled "CLOUD INTERFACE FOR COUPLED SURGICAL DEVICES"; · U.S. Provisional Patent Application No. 62 / 649,320, entitled "DRIVE ARRANGEMENTS FOR ROBOT-ASSISTED SURGICAL PLATFORMS"; U.S. Provisional Patent Application No. 62 / 649,307, entitled "AUTOMATIC TOOL ADJUSTMENTS FOR ROBOT-ASSISTED SURGICAL PLATFORMS," and · U.S. Provisional Patent Application No. 62 / 649,323, entitled “SENSING ARRANGEMENTS FOR ROBOT-ASSISTED SURGICAL PLATFORMS.”

[0010] The applicant of this application owns the following U.S. patent applications, filed March 29, 2018, the disclosures of each of which are incorporated by reference in their entirety herein: U.S. Patent Application No. ______, entitled "INTERACTIVE SURGICAL SYSTEMS WITH ENCRYPTED COMMUNICATION CAPABILITIES," Attorney Docket No. END8499USNP / 170766; U.S. Patent Application Serial No. ______, entitled "INTERACTIVE SURGICAL SYSTEMS WITH CONDITION HANDLING OF DEVICES AND DATA CAPABILITIES," Attorney Docket No. END8499USNP1 / 170766-1; U.S. Patent Application Serial No. ______, Attorney Docket No. END8499USNP2 / 170766-2, entitled "SURGICAL HUB COORDINATION OF CONTROL AND COMMUNICATION OF OPERATING ROOM DEVICES"; U.S. Patent Application No. ________, entitled “SPATIAL AWARENESS OF SURGICAL HUBS IN OPERATING ROOMS”, Attorney Docket No. END8499USNP3 / 170766-3; U.S. Patent Application No. ________, entitled “COOPERATIVE UTILIZATION OF DATA DERIVED FROM SECONDARY SOURCES BY INTELLIGENT SURGICAL HUBS,” Attorney Docket No. END8499USNP4 / 170766-4; · U.S. Patent Application Serial No. _______ entitled “SURGICAL HUB CONTROL ARRANGEMENTS”, Attorney Docket No. END8499USNP5 / 170766-5; U.S. Patent Application Serial No. ______, Attorney Docket No. END8500USNP / 170767, entitled "DATA STRIPPING METHOD TO INTERROGATE PATIENT RECORDS AND CREATE ANONYMIZED RECORD"; U.S. Patent Application Serial No. ________, Attorney Docket No. END8500USNP1 / 170767-1, entitled "COMMUNICATION HUB AND STORAGE DEVICE FOR STORING PARAMETERS AND STATUS OF A SURGICAL DEVICE TO BE SHARED WITH CLOUD BASED ANALYTICS SYSTEMS"; U.S. Patent Application Serial No. ______, entitled “SELF DESCRIBING DATA PACKETS GENERATED AT AN ISSUING INSTRUMENT,” Attorney Docket No. END8500USNP2 / 170767-2; U.S. Patent Application Serial No. ______, entitled "DATA PAIRING TO INTERCONNECT A DEVICE MEASURED PARAMETER WITH AN OUTCOME," Attorney Docket No. END8500USNP3 / 170767-3; · U.S. Patent Application Serial No. _______ entitled “SURGICAL HUB SITUATIONAL AWARENESS”, Attorney Docket No. END8501USNP / 170768; U.S. Patent Application No. ________, entitled “SURGICAL SYSTEM DISTRIBUTED PROCESSING”, Attorney Docket No. END8501USNP1 / 170768-1; U.S. Patent Application Serial No. ______, entitled “AGGREGATION AND REPORTING OF SURGICAL HUB DATA,” Attorney Docket No. END8501USNP2 / 170768-2; U.S. Patent Application No. ________, Attorney Docket No. END8502USNP / 170769, entitled "SURGICAL HUB SPATIAL AWARENESS TO DETERMINE DEVICES IN OPERATING THEATER"; U.S. Patent Application Serial No. ______, entitled "DISPLAY OF ALIGNMENT OF STAPLE CARTRIDGE TO PRIOR LINEAR STAPLE LINE," Attorney Docket No. END8502USNP1 / 170769-1; U.S. Patent Application No. ________, entitled “STERILE FIELD INTERACTIVE CONTROL DISPLAYS,” Attorney Docket No. END8502USNP2 / 170769-2; U.S. Patent Application No. ______, entitled “COMPUTER IMPLEMENTED INTERACTIVE SURGICAL SYSTEMS,” Attorney Docket No. END8503USNP / 170770; U.S. Patent Application Serial No. ______, entitled "USE OF LASER LIGHT AND RED-GREEN-BLUE COLORATION TO DETERMINE PROPERTIES OF BACK SCATTERED LIGHT," Attorney Docket No. END8504USNP / 170771; U.S. Patent Application No. ______, entitled “CHARACTERIZATION OF TISSUE IRREGULARITIES THROUGH THE USE OF MONO-CHROMATIC LIGHT REFRACTIVITY”, Attorney Docket No. END8504USNP1 / 170771-1, and · U.S. patent application Ser. No. _______ entitled “DUAL CMOS ARRAY IMAGING”, Attorney Docket No. END8504USNP2 / 170771-2.

[0011] The applicant of this application owns the following U.S. patent applications, filed March 29, 2018, the disclosures of each of which are incorporated by reference in their entirety herein: U.S. Patent Application Serial No. ______, entitled "ADAPTIVE CONTROL PROGRAM UPDATES FOR SURGICAL DEVICES," Attorney Docket No. END8506USNP / 170773; U.S. Patent Application No. ______, entitled “ADAPTIVE CONTROL PROGRAM UPDATES FOR SURGICAL HUBS,” Attorney Docket No. END8506USNP1 / 170773-1; U.S. Patent Application Serial No. ______, entitled "CLOUD-BASED MEDICAL ANALYTICS FOR CUSTOMIZATION AND RECOMMENDATIONS TO A USER," Attorney Docket No. END8507USNP / 170774; U.S. Patent Application Serial No. ______, entitled "CLOUD-BASED MEDICAL ANALYTICS FOR MEDICAL FACILITY SEGMENTED INDIVIDUALIZATION OF INSTRUMENT FUNCTION," Attorney Docket No. END8507USNP2 / 170774-2; U.S. Patent Application No. ________, entitled "CLOUD-BASED MEDICAL ANALYTICS FOR SECURITY AND AUTHENTICATION TRENDS AND REACTIVE MEASURES," Attorney Docket No. END8508USNP / 170775; U.S. Patent Application Serial No. ______, entitled "DATA HANDLING AND PRIORITIZATION IN A CLOUD ANALYTICS NETWORK," Attorney Docket No. END8509USNP / 170776, and · U.S. Patent Application Serial No. ________ entitled “CLOUD INTERFACE FOR COUPLED SURGICAL DEVICES”, Attorney Docket No. END8510USNP / 170777.

[0012] The applicant of this application owns the following U.S. patent applications, filed March 29, 2018, the disclosures of each of which are incorporated by reference in their entirety herein: U.S. Patent Application No. ______, entitled "DRIVE ARRANGEMENTS FOR ROBOT-ASSISTED SURGICAL PLATFORMS," Attorney Docket No. END8511USNP / 170778; U.S. Patent Application No. ______, entitled "COMMUNICATION ARRANGEMENTS FOR ROBOT-ASSISTED SURGICAL PLATFORMS," Attorney Docket No. END8511USNP1 / 170778-1; U.S. Patent Application No. ______, entitled “CONTROLS FOR ROBOT-ASSISTED SURGICAL PLATFORMS,” Attorney Docket No. END8511USNP2 / 170778-2; U.S. Patent Application No. ______, entitled "AUTOMATIC TOOL ADJUSTMENTS FOR ROBOT-ASSISTED SURGICAL PLATFORMS," Attorney Docket No. END8512USNP / 170779; U.S. Patent Application No. ______, entitled "CONTROLLERS FOR ROBOT-ASSISTED SURGICAL PLATFORMS," Attorney Docket No. END8512USNP1 / 170779-1; U.S. Patent Application No. ______, entitled “COOPERATIVE SURGICAL ACTIONS FOR ROBOT-ASSISTED SURGICAL PLATFORMS,” Attorney Docket No. END8512USNP2 / 170779-2; U.S. Patent Application No. ______, entitled "DISPLAY ARRANGEMENTS FOR ROBOT-ASSISTED SURGICAL PLATFORMS," Attorney Docket No. END8512USNP3 / 170779-3, and · U.S. Patent Application Serial No. _______ entitled “SENSING ARRANGEMENTS FOR ROBOT-ASSISTED SURGICAL PLATFORMS”, Attorney Docket No. END8513USNP / 170780.

[0013] Before describing the various aspects of the surgical device and generator in detail, it should be noted that the illustrated embodiments are not limited in application or use to the details of construction and arrangement of parts shown in the accompanying drawings and description. The illustrative embodiments may be embodied or incorporated in other aspects, variations, and modifications, and may be practiced or carried out in various ways. Moreover, unless otherwise specified, the terms and phrases used herein have been selected for the purpose of describing the illustrative embodiments for the convenience of the reader, and not for the purpose of limiting them. It will also be understood that one or more of the aspects, embodiment of the aspects, and / or embodiments described below can be combined with any one or more of the other aspects, embodiment of the aspects, and / or embodiments described below.

[0014] 1, a computer-implemented interactive surgical system 100 includes one or more surgical systems 102 and a cloud-based system (e.g., a cloud 104 that may include a remote server 113 coupled to a storage device 105). Each surgical system 102 includes at least one surgical hub 106 in communication with the cloud 104 that may include the remote server 113. In one embodiment, as shown in FIG. 1, the surgical systems 102 include a visualization system 108, a robotic system 110, and a handheld intelligent surgical instrument 112 configured to communicate with each other and / or with the hub 106. In some aspects, the surgical system 102 may include M hubs 106, N visualization systems 108, O robotic systems 110, and P handheld intelligent surgical instruments 112, where M, N, O, and P are integers equal to or greater than 1.

[0015] FIG. 3 illustrates an example of a surgical system 102 used to perform a surgical procedure on a patient lying on an operating table 114 in a surgical room 116. A robotic system 110 is used as part of the surgical system 102 in the surgical procedure. The robotic system 110 includes a surgeon's console 118, a patient side cart 120 (surgical robot), and a surgical robot hub 122. The patient side cart 120 can manipulate at least one detachably coupled surgical tool 117 during minimally invasive incision of the patient's body while the surgeon views the surgical site via the surgeon's console 118. Images of the surgical site can be obtained by a medical imaging device 124, which can be manipulated by the patient side cart 120 to orient the imaging device 124. The robotic hub 122 can be used to process images of the surgical site for subsequent display to the surgeon via the surgeon's console 118.

[0016] Other types of robotic systems can be readily adapted for use with the surgical system 102. Various examples of robotic systems and surgical tools suitable for use with the present disclosure are described in U.S. Provisional Patent Application No. 62 / 611,339, filed December 28, 2017, entitled "ROBOT ASSISTED SURGICAL PLATFORM," the disclosure of which is incorporated herein by reference in its entirety.

[0017] Various examples of cloud-based analytics performed by cloud 104 and suitable for use with the present disclosure are described in U.S. Provisional Patent Application No. 62 / 611,340, entitled "CLOUD-BASED MEDICAL ANALYTICS," filed December 28, 2017, the entire disclosure of which is incorporated herein by reference.

[0018] In various embodiments, the imager 124 includes at least one image sensor and one or more optical components. Suitable image sensors include, but are not limited to, charge-coupled device (CCD) sensors and complementary metal-oxide semiconductor (CMOS) sensors.

[0019] The optical components of the imager 124 may include one or more illumination sources and / or one or more lenses. The one or more illumination sources may be directed to illuminate a portion of the surgical field. The one or more image sensors may receive light reflected or refracted from the surgical field, including light reflected or refracted from tissue and / or surgical instruments.

[0020] The one or more illumination sources may be configured to emit electromagnetic energy in the visible and invisible spectrum. The visible spectrum, sometimes called the optical spectrum or luminous spectrum, is the portion of the electromagnetic spectrum that is visible to (i.e., detectable by) the human eye, and is sometimes called visible light, or simply light. A typical human eye responds to wavelengths in air between about 380 nm and about 750 nm.

[0021] The invisible spectrum (i.e., the non-radiative spectrum) is the portion of the electromagnetic spectrum that lies below and above the visible spectrum (i.e., wavelengths below about 380 nm and above about 750 nm). The invisible spectrum is not detectable by the human eye. Wavelengths above about 750 nm are longer than the red visible spectrum, which are invisible infrared (IR), microwave, and wireless electromagnetic radiation. Wavelengths below about 380 nm are shorter than the violet spectrum, which are invisible ultraviolet, X-ray, and gamma ray electromagnetic radiation.

[0022] In various aspects, the imaging device 124 is configured for use in minimally invasive surgery. Examples of imaging devices suitable for use with the present disclosure include, but are not limited to, arthroscopes, angioscopes, bronchoscopes, cholangioscopes, colonoscopes, cytoscopes, duodenoscopes, enteroscopes, esophagogastroduodenoscopes (gastroscopes), endoscopes, laryngoscopes, nasopharyngo-neproscopes, sigmoidoscopes, thoracoscopes, and ureteroscopes.

[0023] In one aspect, the imaging device uses multispectral monitoring to distinguish between topography and underlying structures. Multispectral imaging captures image data within a specific wavelength range across the electromagnetic spectrum. The wavelengths can be separated by filters or by using instruments sensitive to light from specific wavelengths including frequencies beyond the visible light range, for example, IR and ultraviolet light. Spectral imaging can allow for the extraction of additional information that the human eye cannot capture with its red, green, and blue receptors. The use of multispectral imaging is described in detail in the "Advanced Imaging Acquisition Module" section of U.S. Provisional Patent Application No. 62 / 611,341, entitled "INTERACTIVE SURGICAL PLATFORM," filed December 28, 2017, the entire disclosure of which is incorporated herein by reference. Multispectral monitoring can be a useful tool to reposition the surgical field to perform one or more of the above-mentioned tests on the treated tissue after one surgical procedure is completed.

[0024] It is self-evident that any surgical procedure requires strict sterilization of the operating room and surgical instruments. The strict sanitary and sterile conditions required in the "surgical theater", i.e., operating room or procedure room, require the utmost sterility of all medical devices and equipment. Part of that sterilization process is the need to sterilize everything that comes into contact with the patient or enters the sterile field, including the imaging device 124 and its accessories and components. It will be understood that the sterile field may be considered a specific area that is deemed free of microorganisms, such as in a tray or on a sterile towel, or the sterile field may be considered the area immediately surrounding the patient who is prepared for the surgical procedure. The sterile field may include cleaned team members in appropriate clothing, and all the equipment and fixtures in the area.

[0025] In various aspects, the visualization system 108 includes one or more imaging sensors strategically aligned with respect to the sterile field, one or more image processing units, one or more storage arrays, and one or more displays, as shown in Figure 2. In one aspect, the visualization system 108 includes HL7, PACS, and EMR interfaces. The various components of the visualization system 108 are described in the "Advanced Imaging Acquisition Module" section of U.S. Provisional Patent Application No. 62 / 611,341, entitled "INTERACTIVE SURGICAL PLATFORM," filed December 28, 2017, the entire disclosure of which is incorporated herein by reference.

[0026] As shown in FIG. 2, the primary display 119 is positioned within the sterile field so as to be visible to an operator positioned at the operating table 114. In addition, the visualization tower 111 is positioned outside the sterile field. The visualization tower 111 includes a first non-sterile display 107 and a second non-sterile display 109 facing away from each other. A visualization system 108 guided by the hub 106 is configured to coordinate information flow to operators inside and outside the sterile field using the displays 107, 109, and 119. For example, the hub 106 may cause the visualization system 108 to maintain a live video of the surgical site on the primary display 119 while displaying snapshots of the surgical site recorded by the imager 124 on the non-sterile displays 107 or 109. The snapshots on the non-sterile displays 107 or 109 can, for example, enable the non-sterile operator to perform diagnostic steps related to the surgical procedure.

[0027] In one aspect, the hub 106 is also configured to send diagnostic input or feedback entered by a non-sterile operator located in the sterile field at the visualization tower 111 to the primary display 119 in the sterile field for viewing by a sterile operator located at the operating table. In one example, the input can be in the form of a correction to a snapshot displayed on the non-sterile display 107 or 109 that can be sent by the hub 106 to the primary display 119.

[0028] 2, a surgical instrument 112 is used as part of the surgical system 102 in a surgical procedure. The hub 106 is also configured to coordinate information flow to the display of the surgical instrument 112. See, for example, U.S. Provisional Patent Application No. 62 / 611,341, filed December 28, 2017, entitled "INTERACTIVE SURGICAL PLATFORM," the disclosure of which is incorporated herein by reference in its entirety. Diagnostic input or feedback entered by a non-sterile operator at the visualization tower 111 may be sent by the hub 106 to the surgical instrument display 115 in the sterile field, where the diagnostic input or feedback may be viewed by the operator of the surgical instrument 112. Exemplary surgical instruments suitable for use with the surgical system 102 are described, for example, in the section entitled "Surgical Instrument Hardware" and in U.S. Provisional Patent Application No. 62 / 611,341, filed December 28, 2017, entitled "INTERACTIVE SURGICAL PLATFORM," the entire disclosure of which is incorporated herein by reference.

[0029] 3, the hub 106 is shown in communication with a visualization system 108, a robotic system 110, and a handheld intelligent surgical instrument 112. The hub 106 includes a hub display 135, an imaging module 138, a generator module 140, a communications module 130, a processor module 132, and a storage array 134. In certain aspects, as shown in FIG. 3, the hub 106 further includes a smoke evacuation module 126 and / or a suction / irrigation module 128.

[0030] During a surgical procedure, the application of energy to tissue for sealing and / or cutting is typically accompanied by smoke evacuation, aspiration of excess fluid, and / or irrigation of tissue. Fluid, power, and / or data lines from different sources often become entangled during a surgical procedure. Valuable time may be lost addressing this issue during a surgical procedure. Untangling the lines may require unplugging the lines from their corresponding modules, which may require resetting the modules. The modular housing 136 of the hub provides a unified environment for managing the power, data, and fluid lines, reducing the frequency of such tangling between lines.

[0031] Aspects of the present disclosure present a surgical hub for use in a surgical procedure involving the application of energy to tissue at a surgical site. The surgical hub includes a hub housing and a combination generator module slidably receivable within a docking station of the hub housing. The docking station includes data and power contacts. The combination generator module includes two or more of an ultrasonic energy generator component, a bipolar RF energy generator component, and a monopolar RF energy generator component housed within a single unit. In one aspect, the combination generator module further includes a smoke evacuation component, at least one energy delivery cable for connecting the combination generator module to a surgical instrument, at least one smoke evacuation component configured to evacuate smoke, fluid, and / or particulates generated by the application of therapeutic energy to tissue, and a fluid line extending from a remote surgical site to the smoke evacuation component.

[0032] In one aspect, the fluid line is a first fluid line and a second fluid line extends from a remote surgical site to an aspiration and irrigation module that is slidably received within the hub housing. In one aspect, the hub housing includes a fluid interface.

[0033] Certain surgical procedures may require the application of more than one energy type to tissue. One energy type may be more beneficial for cutting tissue, while another different energy type may be more beneficial for sealing tissue. For example, a bipolar generator may be used to seal tissue, while an ultrasonic generator may be used to cut the sealed tissue. Aspects of the present disclosure present a solution in which the modular housing 136 of the hub is configured to house and facilitate bidirectional communication between various generators. One advantage of the modular housing 136 of the hub is that it allows for quick removal and / or replacement of various modules.

[0034] Aspects of the present disclosure present a modular surgical housing for use in a surgical procedure involving application of energy to tissue, the modular surgical housing including a first energy generator module configured to generate a first energy for application to tissue, and a first docking station including a first docking port including first data and power contacts, the first energy generator module slidably movable into electrical engagement with the power and data contacts, and the first energy generator module slidably movable out of electrical engagement with the first power and data contacts.

[0035] In addition to the above, the modular surgical housing further includes a second energy generator module configured to generate a second energy for application to tissue, different from the first energy, and a second docking station including a second docking port including second data and power contacts, wherein the second energy generator module is slidably movable into electrical engagement with the power and data contacts, and the second energy generator module is slidably movable out of electrical engagement with the second power and data contacts.

[0036] Additionally, the modular surgical housing further includes a communication bus between the first docking port and the second docking port configured to facilitate communication between the first energy generator module and the second energy generator module.

[0037] 3-7, aspects of the disclosure are presented relating to a hub modular housing 136 that allows for modular integration of a generator module 140, a smoke evacuation module 126, and an aspiration / irrigation module 128. The hub modular housing 136 further facilitates bidirectional communication between the modules 140, 126, 128. As shown in FIG. 5, the generator module 140 may be a generator module that includes integrated monopolar, bipolar, and ultrasonic components supported within a single housing unit 139 that is slidably insertable into the hub modular housing 136. As shown in FIG. 5, the generator module 140 may be configured to connect to a monopolar device 146, a bipolar device 147, and an ultrasonic device 148. Alternatively, the generator module 140 may include a series of monopolar, bipolar, and / or ultrasonic generator modules that interact via the hub modular housing 136. The hub modular housing 136 can be configured to facilitate the insertion of multiple generators and bidirectional communication between the generators docked to the hub modular housing 136 such that the multiple generators function as a single generator.

[0038] In one aspect, the hub modular housing 136 includes a modular power and communications backplane 149 with external and wireless communication headers to allow removable attachment of the modules 140, 126, 128 and bidirectional communication therebetween.

[0039] In one aspect, the hub modular housing 136 includes a docking station or drawer 151, also referred to herein as a drawer, configured to slidably receive the modules 140, 126, 128. FIG. 4 shows a partial perspective view of the surgical hub housing 136 and a combination generator module 145 slidably receivable in the docking station 151 of the surgical hub housing 136. A docking port 152 having power and data contacts on the rear side of the combination generator module 145 is configured to engage the corresponding docking port 150 with the power and data contacts of the corresponding docking station 151 of the hub modular housing 136 when the combination generator module 145 is slid into position within the corresponding docking station 151 of the hub modular housing 136. In one aspect, the combination generator module 145 includes bipolar, ultrasonic, and monopolar modules and a smoke evacuation module integrated together with a single housing unit 139, as shown in FIG.

[0040] In various aspects, the smoke evacuation module 126 includes fluid lines 154 that transport captured / collected smoke and / or fluids away from the surgical site, for example, to the smoke evacuation module 126. Vacuum suction generated from the smoke evacuation module 126 can draw smoke into openings in utility conduits at the surgical site. Utility conduits coupled to the fluid lines can be in the form of flexible tubing that terminates at the smoke evacuation module 126. The utility conduits and fluid lines define a fluid pathway that extends toward the smoke evacuation module 126, which is received within the hub housing 136.

[0041] In various aspects, the aspiration / irrigation module 128 is coupled to a surgical tool that includes aspiration and suction fluid lines. In one embodiment, the aspiration and suction fluid lines are in the form of flexible tubing that extends from the surgical site towards the aspiration / irrigation module 128. One or more drive systems can be configured to effect irrigation and suction of fluids to and from the surgical site.

[0042] In one aspect, the surgical tool includes a shaft having an end effector at its distal end, at least one energy treatment portion associated with the end effector, a suction tube, and an irrigation tube. The suction tube can have an inlet port at its distal end, and the suction tube extends through the shaft. Similarly, the irrigation tube can extend through the shaft and have an inlet port proximate to the energy delivery instrument. The energy delivery instrument is configured to deliver ultrasonic and / or RF energy to the surgical site and is initially coupled to the generator module 140 by a cable extending through the shaft.

[0043] The irrigation tube can be in fluid communication with a fluid source and the suction tube can be in fluid communication with a vacuum source. The fluid source and / or vacuum source can be housed within the aspiration / irrigation module 128. In one embodiment, the fluid source and / or vacuum source can be housed within the hub housing 136 separate from the aspiration / irrigation module 128. In such an embodiment, the fluid interface can be configured to connect the aspiration / irrigation module 128 to the fluid source and / or vacuum source.

[0044] In one aspect, the modules 140, 126, 128 and / or their corresponding docking stations on the hub modular housing 136 may include alignment features configured to align the docking ports of the modules into engagement with their counterparts in the docking stations of the hub modular housing 136. For example, as shown in FIG. 4 , the combination generator module 145 includes side brackets 155 configured to slidably engage with corresponding brackets 156 of the corresponding docking stations 151 of the hub modular housing 136. The brackets cooperate to guide the docking port contacts of the combination generator module 145 into electrical engagement with the docking port contacts of the hub modular housing 136.

[0045] In some aspects, the drawers 151 of the hub's modular housing 136 are the same or substantially the same size, and the modules are sized to be received within the drawers 151. For example, the side brackets 155 and / or 156 may be larger or smaller depending on the size of the module. In other aspects, the drawers 151 are different sizes, each designed to accommodate a particular module.

[0046] Additionally, to prevent inserting a module into a drawer with incompatible contacts, the contacts of a particular module may be keyed to engage with the contacts of a particular drawer.

[0047] 4, the docking port 150 of one drawer 151 may be coupled to the docking port 150 of another drawer 151 via a communication link 157 to facilitate bidirectional communication between the modules housed within the hub modular housing 136. Alternatively, or in addition, the docking port 150 of the hub modular housing 136 may facilitate wireless bidirectional communication between the modules housed within the hub modular housing 136. Any suitable wireless communication may be used, such as, for example, Air Titan-Bluetooth.

[0048] 6 illustrates individual power bus attachments of multiple lateral docking ports of a lateral modular housing 160 configured to receive multiple modules of a surgical hub 206. The lateral modular housing 160 is configured to laterally receive and interconnect modules 161. The modules 161 are slidably inserted into a docking station 162 of the lateral modular housing 160 that includes a backplane for interconnecting the modules 161. As shown in FIG. 6, the modules 161 are disposed laterally within the lateral modular housing 160. Alternatively, the modules 161 may be disposed vertically within the lateral modular housing.

[0049] FIG. 7 illustrates a vertical modular housing 164 configured to receive a plurality of modules 165 of the surgical hub 106. The modules 165 are slidably inserted into a docking station or drawer 167 of the vertical modular housing 164 that includes a backplane for interconnecting the modules 165. The drawers 167 of the vertical modular housing 164 are vertically oriented, although in certain cases the vertical modular housing 164 may include horizontally oriented drawers. Additionally, the modules 165 may interact with each other via docking ports of the vertical modular housing 164. In the embodiment of FIG. 7, a display 177 is provided for displaying data related to the operation of the modules 165. Additionally, the vertical modular housing 164 includes a master module 178 that houses a plurality of sub-modules that are slidably received within the master module 178.

[0050] In various aspects, the imaging module 138 includes an integrated video processor and a modular light source and is adapted for use with various imaging devices. In one aspect, the imaging device is configured with a modular housing that can be assembled with a light source module and a camera module. The housing can be a disposable housing. In at least one embodiment, the disposable housing is removably coupled with a reusable controller, a light source module, and a camera module. The light source module and / or the camera module can be selectively selected depending on the type of surgical procedure. In one aspect, the camera module includes a CCD sensor. In another aspect, the camera module includes a CMOS sensor. In another aspect, the camera module is configured for imaging of a scanned beam. Similarly, the light source module can be configured to deliver white light or a different light depending on the surgical procedure.

[0051] During a surgical procedure, it may be inefficient to remove a surgical device from the surgical field and replace it with another surgical device including a different camera or a different light source. Temporary loss of view of the surgical field may result in undesirable results. The modular imaging device of the present disclosure is configured to allow replacement of a light source module or a camera module midstream during a surgical procedure without the need to remove the imaging device from the surgical field.

[0052] In one aspect, the imaging device comprises a tubular housing including a plurality of channels. A first channel is configured to slidably receive a camera module that may be configured for snap-fit ​​engagement with the first channel. A second channel is configured to slidably receive a light source module that may be configured for snap-fit ​​engagement with the second channel. In another embodiment, the camera module and / or the light source module may be rotated into a final position within their corresponding channels. A threaded engagement may be employed instead of a snap-fit ​​engagement.

[0053] In various embodiments, multiple imaging devices are positioned at different locations within the surgical field to provide multiple fields of view. The imaging module 138 can be configured to switch between the imaging devices to provide an optimal field of view. In various aspects, the imaging module 138 can be configured to integrate images from the different imaging devices.

[0054] Various image processors and imaging devices suitable for use with the present disclosure are described in U.S. Patent No. 7,995,045, issued Aug. 9, 2011, entitled "COMBINED SBI AND CONVENTIONAL IMAGE PROCESSOR," which is incorporated herein by reference in its entirety. Additionally, U.S. Patent No. 7,982,776, issued Jul. 19, 2011, entitled "SBI MOTION ARTIFACT REMOVAL APPARATUS AND METHOD," which is incorporated herein by reference in its entirety, describes various systems for removing motion artifacts from image data. Such systems may be integrated with the imaging module 138. Additionally, U.S. Patent Application Publication No. 2011 / 0306840, published December 15, 2011, entitled "CONTROLLABLE MAGNETIC SOURCE TO FIXTURE INTRACORPOREAL APPARATUS," and U.S. Patent Application Publication No. 2014 / 0243597, published August 28, 2014, entitled "SYSTEM FOR PERFORMING A MINIMALLY INVASIVE SURGICAL PROCEDURE," are each incorporated herein by reference in their entirety.

[0055] FIG. 8 illustrates a surgical data network 201 comprising a modular communication hub 203 configured to connect modular devices located in one or more operating rooms of a medical facility, or any room in a medical facility with specialized equipment for surgical procedures, to a cloud-based system (e.g., cloud 204, which may include a remote server 213 coupled to storage device 205). In one embodiment, the modular communication hub 203 comprises a network hub 207 and / or a network switch 209 in communication with a network router. The modular communication hub 203 can further be coupled to a local computer system 210 to provide local computer processing and data manipulation. The surgical data network 201 may be configured as passive, intelligent, or switched. A passive surgical data network acts as a conduit for data, allowing data to go from one device (or segment) to another device (or segment) and to cloud computing resources. An intelligent surgical data network includes additional mechanisms that allow traffic to pass through the monitored surgical data network and configure each port in the network hub 207 or network switch 209. An intelligent surgical data network may be referred to as a manageable hub or switch. A switching hub reads the destination address of each packet and then forwards the packet to the correct port.

[0056] Modular devices 1a-1n located in the operating room may be coupled to the modular communication hub 203. The network hub 207 and / or the network switch 209 may be coupled to the network router 211 to connect the devices 1a-1n to the cloud 204 or the local computer system 210. Data associated with the devices 1a-1n may be transferred to a cloud-based computer via the router for remote data processing and manipulation. Data associated with the devices 1a-1n may also be transferred to the local computer system 210 for local data processing and manipulation. Modular devices 2a-2m located in the same operating room may also be coupled to the network switch 209. The network switch 209 may be coupled to the network hub 207 and / or the network router 211 to connect the devices 2a-2m to the cloud 204. Data associated with the devices 2a-2n may be transferred to the cloud 204 via the network router 211 for data processing and manipulation. Data associated with the devices 2a-2m may also be transferred to the local computer system 210 for local data processing and manipulation.

[0057] It will be appreciated that the surgical data network 201 may be expanded by interconnecting multiple network hubs 207 and / or multiple network switches 209 with multiple network routers 211. The modular communications hub 203 may be housed in a modular control tower configured to receive multiple devices 1a-1n / 2a-2m. The local computer system 210 may also be housed in the modular control tower. The modular communications hub 203 is connected to a display 212 to display images acquired by some of the devices 1a-1n / 2a-2m, for example, during a surgical procedure. In various aspects, devices 1a-1n / 2a-2m may include various modules, such as an imaging module 138 coupled to an endoscope, a generator module 140 coupled to an energy-based surgical device, a smoke evacuation module 126, a suction / irrigation module 128, a communications module 130, a processor module 132, a storage array 134, a surgical device coupled to a display, and / or a non-contact sensor module, among other modular devices that may be connected to a modular communications hub 203 of a surgical data network 201.

[0058] In one aspect, the surgical data network 201 may include a combination of network hub(s), network switch(es), and network router(s) that connect the devices 1a-1n / 2a-2m to the cloud. Any one or all of the devices 1a-1n / 2a-2m coupled to the network hub or network switch may collect data in real time and transfer the data to a cloud computer for data processing and manipulation. It will be understood that cloud computing relies on shared computing resources rather than having local servers or personal devices to handle software applications. Although the term "cloud" is sometimes used as a metaphor for the "internet," the term is not so limited. Thus, the term "cloud computing" may be used herein to refer to "a type of internet-based computing" where various services such as servers, storage, and applications are delivered to the modular communications hub 203 and / or computer system 210 located at the surgical site (e.g., fixed, mobile, temporary, or on-site operating room or space) and to devices connected to the modular communications hub 203 and / or computer system 210 via the internet. The cloud infrastructure may be maintained by a cloud service provider. In this context, the cloud service provider may be an entity that coordinates the use and control of devices 1a-1n / 2a-2m located in one or more operating rooms. The cloud computing services may perform numerous calculations based on data collected by smart surgical instruments, robots, and other computerized devices located in the operating room. The hub hardware allows multiple devices or connections to connect to a computer that communicates with cloud computing resources and storage.

[0059] By applying cloud computer data processing techniques to data collected by the devices 1a-1n / 2a-2m, the surgical data network provides improved surgical outcomes, reduced costs, and improved patient satisfaction. At least some of the devices 1a-1n / 2a-2m can be used to observe tissue status and evaluate leakage or perfusion of sealed tissue after tissue sealing and cutting procedures. At least some of the devices 1a-1n / 2a-2m can be used to diagnostically inspect data including images of samples of body tissue to identify pathologies such as disease effects using cloud-based computing. This includes tissue and phenotypic localization and margin confirmation. At least some of the devices 1a-1n / 2a-2m can be used to identify anatomical structures of the body using techniques such as various sensors integrated with the imaging devices and overlaying images captured by multiple imaging devices. Data collected by the devices 1a-1n / 2a-2m, including image data, may be transferred to the cloud 204 or a local computer system 210, or both, for data processing and manipulation, including image processing and manipulation. The data can be analyzed to improve the outcome of the surgical procedure by determining whether further treatments can be pursued, such as endoscopic interventions, emerging technologies, targeted radiation, targeted interventions, and application of precision robotics to tissue-specific sites and conditions. Such data analysis may further employ prognostic analysis processes, and using a standardized approach can provide useful feedback to either confirm or suggest modifications to surgical treatments and surgeon performance.

[0060] In one implementation, the operating room devices 1a-1n may be connected to the modular communication hub 203 via wired or wireless channels depending on the configuration of the devices 1a-1n relative to the network hub. The network hub 207 may be implemented in one embodiment as a local network broadcast device that operates on the physical layer of the Open Systems Interconnection (OSI) model. The network hub provides connectivity to the devices 1a-1n located in the same operating room network. The network hub 207 collects data in the form of packets and sends them to the router in half-duplex mode. The network hub 207 does not store any Media Access Control / Internet Protocol (MAC / IP) for forwarding device data. Only one of the devices 1a-1n can send data at a time through the network hub 207. The network hub 207 does not have a routing table or intelligence on where to send the information and broadcasts all network data across each connection and to the remote server 213 (FIG. 9) on the cloud 204. Although network hub 207 can detect basic network errors such as collisions, broadcasting all information to multiple ports can pose security risks and cause bottlenecks.

[0061] In another implementation, the operating room devices 2a-2m may be connected to the network switch 209 via wired or wireless channels. The network switch 209 functions within the data link layer of the OSI model. The network switch 209 is a multicast device for connecting the devices 2a-2m located in the same operating room to the network. The network switch 209 transmits data in the form of frames to the network router 211 and functions in full duplex mode. Multiple devices 2a-2m can transmit data simultaneously through the network switch 209. The network switch 209 stores and uses the MAC addresses of the devices 2a-2m to forward data.

[0062] The network hub 207 and / or the network switch 209 are coupled to a network router 211 to connect to the cloud 204. The network router 211 functions within the network layer of the OSI model. The network router 211 creates a path for sending data packets received from the network hub 207 and / or the network switch 211 to cloud-based computer resources for further processing and manipulation of data collected by any one or all of the devices 1a-1n / 2a-2m. The network router 211 may be used to connect two or more different networks located at different locations, such as different networks located in different operating rooms of the same medical facility, or different operating rooms of different medical facilities. The network router 211 transmits data in the form of packets to the cloud 204 and functions in full-duplex mode. Multiple devices can transmit data simultaneously. The network router 211 uses IP addresses to forward data.

[0063] In one embodiment, the network hub 207 may be implemented as a USB hub that allows multiple USB devices to be connected to a host computer. The USB hub may expand a single USB port into several tiers so that more ports are available for connecting devices to the host system computer. The network hub 207 may include wired or wireless capabilities for receiving information over wired or wireless channels. In one aspect, a wireless USB short-range, high-bandwidth wireless communication protocol may be used for communication between the devices 1a-1n and 2a-2m located in the operating room.

[0064] In other embodiments, the operating room devices 1a-1n / 2a-2m may communicate with the modular communications hub 203 via the Bluetooth wireless technology standard to exchange data over short distances from fixed and mobile devices (using short wavelength UHF radio waves in the 2.4-2.485 GHz ISM band) and to create a personal area network (PAN). In other aspects, the operating room devices 1a-1n / 2a-2m may communicate with the modular communications hub 203 via numerous wireless or wired communications standards or protocols, including but not limited to Wi-Fi (IEEE 802.11 family), WiMAX (IEEE 802.16 family), IEEE 802.20, Long Term Evolution (LTE), and Ev-DO, HSPA+, HSDPA+, HSUPA+, EDGE, GSM, GPRS, CDMA, TDMA, DECT, and Ethernet derivatives thereof, as well as any other wireless and wired protocols designated 3G, 4G, 5G, and beyond. The computing module may include multiple communication modules, for example, a first communication module may be dedicated to short-range wireless communication such as Wi-Fi and Bluetooth, and a second communication module may be dedicated to long-range wireless communication such as GPS, EDGE, GPRS, CDMA, WiMAX, LTE, Ev-DO, etc.

[0065] The modular communications hub 203 can act as a central connection for one or all of the operating room devices 1a-1n / 2a-2m and handles data types known as frames. Frames carry data generated by the devices 1a-1n / 2a-2m. Once the frames are received by the modular communications hub 203, they are amplified and transmitted to the network router 211, which forwards this data to cloud computing resources by using any number of wireless or wired communications standards or protocols described herein.

[0066] The modular communications hub 203 may be used as a stand-alone device or may be connected to compatible network hubs and network switches to form a larger network. The modular communications hub 203 is generally easy to install, configure, and maintain, making the modular communications hub 203 a good choice for networking the operating room devices 1a-1n / 2a-2m.

[0067] FIG. 9 illustrates a computer-implemented interactive surgical system 200. The computer-implemented interactive surgical system 200 is similar in many respects to the computer-implemented interactive surgical system 100. For example, the computer-implemented interactive surgical system 200 includes one or more surgical systems 202 that are similar in many respects to the surgical system 102. Each surgical system 202 includes at least one surgical hub 206 that communicates with a cloud 204 that may include a remote server 213. In one aspect, the computer-implemented interactive surgical system 200 includes a modular control tower 236 connected to a plurality of operating room devices, such as, for example, intelligent surgical instruments, robots, and other computerized devices located in the operating room. As shown in FIG. 10, the modular control tower 236 includes a modular communication hub 203 coupled to a computer system 210. As illustrated in the embodiment of FIG. 9, the modular control tower 236 is coupled to an imaging module 238 coupled to an endoscope 239, a generator module 240 coupled to an energy device 241, a smoke evacuator module 226, a suction / irrigation module 228, a communication module 230, a processor module 232, a storage array 234, a smart device / instrument 235 optionally coupled to a display 237, and a non-contact sensor module 242. The operating room devices are coupled to cloud computing resources and data storage via the modular control tower 236. The robot hub 222 may also be connected to the modular control tower 236 and cloud computing resources. The devices / instruments 235, visualization system 208, among others, may be coupled to the modular control tower 236 via wired or wireless communication standards or protocols described herein. The modular control tower 236 may be coupled to a hub display 215 (e.g., monitor, screen) for displaying and overlaying images received from the imaging module, device / instrument display, and / or other visualization system 208. The hub display may also display data received from devices connected to the modular control tower along with images and overlay images.

[0068] FIG. 10 illustrates a surgical hub 206 comprising a number of modules coupled to a modular control tower 236. The modular control tower 236 comprises a modular communications hub 203, e.g., a network-connected device, and a computer system 210, e.g., for providing local processing, visualization, and imaging. As shown in FIG. 10, the modular communications hub 203 can be connected in a hierarchical configuration to expand the number of modules (e.g., devices) that can be connected to the modular communications hub 203 to transfer data associated with the modules to the computer system 210, cloud computing resources, or both. As shown in FIG. 10, each of the network hubs / switches in the modular communications hub 203 includes three downstream ports and one upstream port. The upstream network hub / switch is connected to a processor to provide communication connections to cloud computing resources and a local display 217. Communication to the cloud 204 can be via either wired or wireless communication channels.

[0069] The surgical hub 206 uses the non-contact sensor module 242 to measure the dimensions of the operating room and generate a map of the operating field using either an ultrasound or laser-based non-contact measurement device. As described in U.S. Provisional Patent Application No. 62 / 611,341, filed December 28, 2017, entitled "INTERACTIVE SURGICAL PLATFORM," section "Surgical Hub Spatial Awareness Within an Operating Room," which is incorporated herein by reference in its entirety, the ultrasound-based non-contact sensor module is configured to scan the operating room by transmitting bursts of ultrasound and receiving echoes as the bursts of ultrasound reflect off the exterior walls of the operating room, where the sensor module determines the size of the operating room and adjusts the distance limit for Bluetooth pairing. The laser-based non-contact sensor module scans the operating room, for example, by transmitting laser light pulses, receiving laser light pulses that reflect off the exterior walls of the operating room, and comparing the phase of the transmitted pulses to the received pulses to determine the size of the operating room and adjust the distance limit for Bluetooth pairing.

[0070] The computer system 210 includes a processor 244 and a network interface 245. The processor 244 is coupled to a communication module 247, storage 248, memory 249, non-volatile memory 250, and input / output interface 251 via a system bus. The system bus may be any of several types of bus structure(s) including a memory bus or memory controller, a peripheral bus or external bus, and / or a local bus using any of a variety of bus architectures, including, but not limited to, a 9-bit bus, Industry Standard Architecture (ISA), MicroChannel Architecture (MSA), Enhanced ISA (EISA), Intelligent Drive Electronics (IDE), VESA Local Bus (VLB), Peripheral Component Interconnect (PCI), USB, Advanced Graphics Port (AGP), Personal Computer Memory Card International Association bus (PCMCIA), Small Computer System Interface (SCSI), or any other proprietary bus.

[0071] Processor 244 may be any single-core or multi-core processor, such as those known under the trade name ARM Cortex manufactured by Texas Instruments. In one aspect, the processor may be an LM4F230H5QR ARM Cortex-M4F processor core available from Texas Instruments, including, for example, 256KB of on-chip memory of single-cycle flash memory or other non-volatile memory up to 40MHz, a pre-fetch buffer to improve performance above 40MHz, 32KB of single-cycle serial random access memory (SRAM), internal read-only memory (ROM) loaded with StellarisWare® software, 2KB of electrically erasable programmable read-only memory (EEPROM), and / or one or more pulse width modulation (PWM) modules, one or more quadrature encoder input (QEI) analogs, one or more 12-bit analog-to-digital converters (ADCs) with 12 analog input channels, details of which are available in a product data sheet.

[0072] In one aspect, the processor 244 may include a safety controller, including two controller families such as the TMS570 and RM4x, also known under the trade name Hercules ARM Cortex R4 from Texas Instruments. The safety controller may be specifically configured for IEC 61508 and ISO 26262 safety limiting applications, among others, to provide advanced integrated safety mechanisms while offering scalable performance, connectivity, and memory options.

[0073] System memory includes volatile and nonvolatile memory. The basic input / output system (BIOS), containing the basic routines for transferring information between elements within a computer system, such as during start-up, is stored in nonvolatile memory. For example, nonvolatile memory may include ROM, programmable ROM (PROM), electrically programmable ROM (EPROM), EEPROM, or flash memory. Volatile memory includes random access memory (RAM), which acts as external cache memory. In addition, RAM is available in many forms, such as SRAM, dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), SyncLink DRAM (SLDRAM), and direct RAMbus RAM (DRRAM).

[0074] The computer system 210 also includes removable / non-removable, volatile / non-volatile computer storage media, such as disk storage. Disk storage includes, but is not limited to, devices such as magnetic disk drives, floppy disk drives, tape drives, Jaz drives, Zip drives, LS-60 drives, flash memory cards, or memory sticks. In addition, disk storage can include storage media either independently or in combination with other storage media, including, but not limited to, optical disk drives, such as compact disk ROM drives (CD-ROMs), compact disk recordable drives (CD-R drives), compact disk rewriteable drives (CD-RW drives), or digital versatile disk ROM drives (DVD-ROMs). Removable or non-removable interfaces may be used to facilitate connection of disk storage devices to the system bus.

[0075] It should be appreciated that the computer system 210 includes software that acts as an intermediary between users and the basic computer resources described in a preferred operating environment. Such software includes an operating system. The operating system, which may be stored on disk storage, functions to control and allocate resources of the computer system. System applications take advantage of the operating system's management of resources through program modules and program data stored either in system memory or on disk storage. It should be appreciated that the various components described herein can be implemented with various operating systems or combinations of operating systems.

[0076] A user inputs commands or information into the computer system 210 through input device(s) coupled to the I / O interface 251. Input devices include, but are not limited to, pointing devices such as a mouse, trackball, stylus, touchpad, keyboard, microphone, joystick, gamepad, satellite dish, scanner, TV tuner card, digital camera, digital video camera, webcam, and the like. These and other input devices connect to the processor through the system bus via interface port(s). Interface port(s) include, for example, serial port, parallel port, game port, and USB. Output device(s) use some of the same types of ports as the input device(s). Thus, for example, a USB port may be used to provide input to the computer system and also to output information from the computer system to an output device. Output adapters are provided to illustrate that there are some output devices such as monitors, displays, speakers, and printers, among other output devices that require special adapters. Output adapters include, by way of example and not limitation, video and sound cards that provide a means of connection between the output device and the system bus. It should be noted that other devices and / or systems of devices, such as remote computer(s), provide both input and output capabilities.

[0077] The computer system 210 can operate in a networked environment using logical connections to one or more remote or local computers, such as cloud computer(s). The remote cloud computer(s) can be a personal computer, a server, a router, a network PC, a workstation, a microprocessor-based device, a peer device, or other general network node, and typically includes many or all of the elements described with respect to a computer system. For simplicity, only memory storage devices are shown with the remote computer(s). The remote computer(s) are logically connected to the computer system through a network interface, and then physically connected through a communication connection. The network interface encompasses communication networks, such as local area networks (LANs) and wide area networks (WANs). LAN technologies include Fiber Distributed Data Interface (FDDI), Copper Distributed Data Interface (CDDI), Ethernet / IEEE 802.3, Token Ring / IEEE 802.5, and the like. WAN technologies include, but are not limited to, point-to-point links, circuit-switched networks such as Integrated Services Digital Networks (ISDN) and its variants, packet-switched networks, and Digital Subscriber Lines (DSL).

[0078] In various aspects, the computer system 210 of FIG. 10, the imaging module 238 of FIGS. 9-10, and / or the visualization system 208, and / or the processor module 232 may include an image processor, an image processing engine, a media processor, or any special-purpose digital signal processor (DSP) used to process digital images. The image processor may use parallel computing using single instruction multiple data (SIMD) or multiple instruction multiple data (MIMD) techniques to increase speed and efficiency. The digital image processing engine may perform a variety of tasks. The image processor may be a system on a chip with a multi-core processor architecture.

[0079] The communications connection(s) refers to the hardware / software used to connect the network interface to the bus. For clarity of illustration, the communications connections are shown internal to the computer system, however, the communications connections may also be external to the computer system 210. For purposes of illustration only, the hardware / software required to connect to the network interface may include internal and external technologies such as modems, including ordinary telephone grade modems, cable modems, and DSL modems, ISDN adapters, and Ethernet cards.

[0080] FIG. 11 illustrates a functional block diagram of one embodiment of a USB network hub 300 device according to one embodiment of the present disclosure. In the illustrated embodiment, the USB network hub device 300 employs a Texas Instruments TUSB2036 integrated circuit hub. The USB network hub 300 is a CMOS device that provides an upstream USB transmit / receive port 302 and up to three downstream USB transmit / receive ports 304, 306, 308 that conform to the USB 2.0 standard. The upstream USB transmit / receive port 302 is a differential rooted data port that includes a differential data minus (DM0) input paired with a differential data plus (DP0) input. The three downstream USB transmit / receive ports 304, 306, 308 are differential data ports, with each port including a differential data plus (DP1-DP3) output paired with a differential data minus (DM1-DM3) output.

[0081] The USB network hub 300 device is implemented with a digital state machine instead of a microcontroller and does not require firmware programming. A fully compliant USB transceiver is integrated into the circuitry of the upstream USB transmit / receive port 302 and all downstream USB transmit / receive ports 304, 306, 308. The downstream USB transmit / receive ports 304, 306, 308 support both full speed and low speed devices by automatically setting the slew rate depending on the speed of the device attached to the port. The USB network hub 300 device may be configured in either bus-powered or self-powered mode and includes hub power logic 312 to manage power.

[0082] The USB network hub 300 device includes a serial interface engine 310 (SIE). The SIE 310 is the front end of the USB network hub 300 hardware and handles most of the protocol described in Chapter 8 of the USB specification. The SIE 310 typically understands signaling down to the transaction level. Functions it handles may include packet recognition, transaction reordering, detection / generation of SOP, EOP, RESET, and RESUME signals, clock / data separation, non-return to zero inverted (NRZI) data encoding / decoding and bit stuffing, CRC generation and checking (token and data), Packet ID (PID) generation and checking / decoding, and / or serial-parallel / parallel-serial conversion. 310 receives a clock input 314 and is coupled to suspend / resume logic and frame timer 316 circuitry and hub repeater circuitry 318 to control communication between the upstream USB transmit / receive port 302 and the downstream USB transmit / receive ports 304, 306, 308 via port logic circuits 320, 322, 324. The SIE 310 is coupled to a command decoder 326 via interface logic for controlling commands from a serial EEPROM via a serial EEPROM interface 330 .

[0083] In various aspects, the USB network hub 300 can connect up to 127 functions organized in up to six logical layers to a single computer. Additionally, the USB network hub 300 can connect to all peripherals using a standardized four-wire cable that provides both communication and power distribution. The power configurations are bus-powered and self-powered. The USB network hub 300 may be configured to support four modes of power management: bus-powered hub with either individual port power management or ganged port power management, and self-powered hub with either individual port power management or ganged port power management. In one aspect, using a USB cable, the USB network hub 300, the upstream USB transmit / receive port 302 is plugged into a USB host controller, and the downstream USB transmit / receive ports 304, 306, 308 are exposed for connecting USB compatible devices, etc.

[0084] Surgical Instrument Hardware FIG. 12 illustrates a logic diagram of a surgical instrument or tool control system 470 according to one or more embodiments of the present disclosure. The system 470 comprises a control circuit. The control circuit includes a microcontroller 461 with a processor 462 and a memory 468. For example, one or more of the sensors 472, 474, 476 provide real-time feedback to the processor 462. A motor 482 driven by a motor driver 492 operatively couples the longitudinally movable displacement member to drive the I-beam knife member. A tracking system 480 is configured to determine a position of the longitudinally movable displacement member. The position information is provided to the processor 462, which can be programmed or configured to determine the position of the longitudinally movable drive member, as well as the position of the firing member, firing bar, and I-beam knife element. Additional motors may be provided to the tool driver interface to control the firing of the I-beam, the movement of the closure tube, the rotation of the shaft, and the articulation. A display 473 displays various operating conditions of the instrument and may include touch screen functionality for data entry. Information displayed on the display 473 can be overlaid with images acquired via the endoscopic imaging module.

[0085] In one embodiment, microcontroller 461 may be any single-core or multi-core processor, such as those known under the trade name ARM Cortex manufactured by Texas Instruments. In one embodiment, main microcontroller 461 may be an LM4F230H5QR ARM Cortex-M4F processor core available from Texas Instruments, including, for example, 256KB of on-chip memory of single-cycle flash memory or other non-volatile memory up to 40MHz, a pre-fetch buffer to improve performance above 40MHz, 32KB of single-cycle SRAM, internal ROM loaded with StellarisWare® software, 2KB of EEPROM, one or more PWM modules, one or more QEI analog, and / or one or more 12-bit ADCs with 12 analog input channels, details of which are available in a product data sheet.

[0086] In one embodiment, the microcontroller 461 may include a safety controller, including two controller families such as TMS570 and RM4x, also known under the trade name Hercules ARM Cortex R4, manufactured by Texas Instruments. The safety controller may be specifically configured for IEC 61508 and ISO 26262 safety limiting applications, among others, to provide advanced integrated safety mechanisms while offering scalable performance, connectivity, and memory options.

[0087] The microcontroller 461 may be programmed to perform various functions, such as precise control over the speed and position of the knife system and the articulation system. In one aspect, the microcontroller 461 includes a processor 462 and a memory 468. The electric motor 482 may be a brushed direct current (DC) motor with a gearbox and mechanical linkage to the articulation system or the knife system. In one aspect, the motor driver 492 may be an A3941 available from Allegro Microsystems, Inc. Other motor drivers may be easily substituted for use in the tracking system 480 with the absolute positioning system. A detailed description of the absolute positioning system is provided in U.S. Patent Application Publication No. 2017 / 0296213, published October 19, 2017, entitled "SYSTEMS AND METHODS FOR CONTROLLING A SURGICAL STAPLING AND CUTTING INSTRUMENT," which is incorporated herein by reference in its entirety.

[0088] The microcontroller 461 may be programmed to provide precise control over the velocity and position of the displacement members and articulation system. The microcontroller 461 may be configured to calculate a response within the microcontroller 461 software. The calculated response is compared to the measured response of the actual system to obtain an "observed" response, which is used to determine the actual feedback. The observed response is a suitable adjusted value that balances the smooth and continuous nature of the simulated response with the measured response, which can detect external influences on the system.

[0089] In one aspect, the motor 482 may be controlled by a motor driver 492 and may be used by the firing system of the surgical instrument or tool. In various configurations, the motor 482 may be a brushed DC drive motor having a maximum rotational speed of, for example, about 25,000 RPM. In another configuration, the motor 482 may include a brushless motor, a cordless motor, a synchronous motor, a stepper motor, or any other suitable electric motor. The motor driver 492 may include, for example, an H-bridge driver including field effect transistors (FETs). The motor 482 may be powered by a power supply assembly releasably attached to the handle assembly or tool housing to provide control power to the surgical instrument or tool. The power supply assembly may include a battery, which may include multiple battery cells connected in series, that may be used as a power source to power the surgical instrument or tool. Under certain circumstances, the battery cells of the power supply assembly 706 may be replaceable and / or rechargeable. In at least one example, the battery cells may be lithium ion batteries that may be connectable to and separable from the power supply assembly.

[0090] The motor driver 492 may be an A3941 available from Allegro Microsystems, Inc. The A3941 492 is a full-bridge controller for use with external N-channel power metal-oxide semiconductor field effect transistors (MOSFETs) specifically designed for inductive loads such as brushed DC motors. The driver 492 has an intrinsic charge pump regulator that provides full (>10V) gate drive for battery voltages up to 7V, allowing the A3941 to operate with reduced gate drive down to 5.5V. A bootstrap capacitor may be used to provide the required battery supply voltage above that required for the N-channel MOSFETs. An internal charge pump for the high-side drive allows DC (100% duty cycle) operation. The full-bridge may be driven in fast or slow decay mode with diode or synchronous rectification. In slow decay mode, current recirculation is possible through either the high-side or low-side FETs. The power FETs are protected from shoot-through by resistor adjustable dead time. Integrated diagnostics indicate undervoltage, overtemperature, and power bridge faults and can be configured to protect the power MOSFETs under most short circuit conditions. Other motor drivers can be easily substituted for use in tracking system 480 with an absolute positioning system.

[0091] The tracking system 480 includes a controlled motor drive circuitry that includes a position sensor 472 according to one aspect of the present disclosure. The position sensor 472 for the absolute positioning system provides a unique position signal corresponding to the position of the displacement member. In one aspect, the displacement member represents a longitudinally movable drive member that includes a rack of drive teeth for meshing engagement with a corresponding drive gear of a gear reducer assembly. In another aspect, the displacement member represents a firing member that may be adapted and configured to include a rack of drive teeth. In yet another aspect, the displacement member represents a firing bar or an I-beam, each of which may be adapted and configured to include a rack of drive teeth. Thus, as used herein, the term displacement member is used generally to refer to any movable member of a surgical instrument, such as a drive member, firing member, firing bar, I-beam, or any element that can be displaced. In one aspect, the longitudinally movable drive member is coupled to the firing member, firing bar, and I-beam. Thus, the absolute positioning system can actually track the linear displacement of the I-beam by tracking the linear displacement of the longitudinally movable drive member. In various other aspects, the displacement member may be coupled to any suitable position sensor 472 for measuring linear displacement. Thus, the longitudinally movable drive member, firing member, firing bar, or I-beam, or combinations thereof, may be coupled to any suitable displacement sensor. The linear displacement sensor may include a contact or non-contact type displacement sensor. The linear displacement sensor may include a linear variable differential transformer (LVDT), a differential variable reluctance transducer (DVRT), a slide potentiometer, a magnetic sensing system with a movable magnet and a series of linearly arranged Hall effect sensors, a magnetic sensing system with a fixed magnet and a series of movable linearly arranged Hall effect sensors, an optical detection system with a movable light source and a series of linearly arranged photodiodes or photodetectors, an optical detection system with a fixed light source and a series of movable linearly arranged photodiodes or photodetectors, or any combination thereof.

[0092] The electric motor 482 may include a rotatable shaft operatively interfaced with a gear assembly mounted in meshing engagement with a set or rack of drive teeth on the displacement member. The sensor element may be operatively coupled to the gear assembly such that one revolution of the position sensor 472 element corresponds to some linear longitudinal translation of the displacement member. The gearing and sensor mechanism may be connected to a linear actuator by a rack and pinion mechanism or to a rotary actuator by a spur gear or other connection. The power source provides power to the absolute positioning system and the output indicator may display the output of the absolute positioning system. The displacement member represents a longitudinally movable drive member with a rack of drive teeth formed thereon for meshing engagement with a corresponding drive gear of a gear reducer assembly. The displacement member represents a longitudinally movable firing member, a firing bar, an I-beam, or a combination thereof.

[0093] One revolution of the sensor element associated with the position sensor 472 corresponds to a linear longitudinal displacement d1 of the displacement member, where d1 is the linear longitudinal distance traveled by the displacement member from point "a" to point "b" after one revolution of the sensor element coupled to the displacement member. The sensor mechanism may be connected via a gear reduction that results in the position sensor 472 completing one or more revolutions for a full stroke of the displacement member. The position sensor 472 may complete multiple revolutions for a full stroke of the displacement member.

[0094] A series of switches (where n is an integer greater than 1) may be used alone or in combination with gear reduction to provide a unique position signal for two or more revolutions of the position sensor 472. The state of the switches is fed back to the microcontroller 461 which applies logic to determine a unique position signal corresponding to the longitudinal linear displacement d1+d2+...dn of the displacement member. The output of the position sensor 472 is provided to the microcontroller 461. The sensor mechanism position sensor 472 may comprise a magnetic sensor, an analog rotary sensor such as a potentiometer, or an array of analog Hall effect elements that output a unique combination of position signals or values.

[0095] The position sensor 472 may comprise any number of magnetic sensing elements, such as magnetic sensors classified based on whether they measure the total magnetic field or vector components of a magnetic field. The technologies used to produce both types of magnetic sensors involve many aspects of physics and electronics. Technologies used to sense magnetic fields include search coils, fluxgates, optical pumping, nuclear precession, SQUIDs, Hall effect, anisotropic magnetoresistance, giant magnetoresistance, magnetic tunnel junctions, giant magnetoimpedance, magnetostrictive / piezoelectric composites, magnetodiodes, magnetotransistors, optical fiber, magneto-optical, and microelectromechanical systems based magnetic sensors, among others.

[0096] In one aspect, the position sensor 472 of the tracking system 480 with absolute positioning system comprises a magnetic rotation absolute positioning system. The position sensor 472 may be implemented as an AS5055EQFT single chip magnetic rotation position sensor available from Austria Microsystems, AG. The position sensor 472 works with the microcontroller 461 to provide the absolute positioning system. The position sensor 472 is a low voltage, low power component and includes four Hall effect elements in the area of ​​the position sensor 472 located above the magnet. Additionally, a high resolution ADC and a smart power management controller are provided on the chip. A Coordinate Rotation Digital Computer (CORDIC) processor, also known as the digit-by-digit method and Volder's algorithm, is provided to implement simple and efficient algorithms for calculating hyperbolic and trigonometric functions, requiring only addition, subtraction, bit shifting, and table lookup operations. The angular position, alarm bits, and magnetic field information are transmitted to the microcontroller 461 via a standard serial communication interface, such as a Serial Peripheral Interface (SPI) interface. The position sensor 472 provides 12-bit or 14-bit resolution and may be an AS5055 chip provided in a small QFN 16-pin 4x4x0.85mm package.

[0097] A tracking system 480 with an absolute positioning system may include and / or be programmed to implement a feedback controller, such as PID, state feedback, and adaptive controllers. A power supply converts a signal from the feedback controller into a physical input to the system, in this case voltage. Other examples include PWM of voltage, current, and force. In addition to the position measured by position sensor 472, other sensor(s) may be provided to measure physical parameters of the physical system. In some embodiments, the other sensor(s) may include sensor mechanisms such as those described in U.S. Pat. No. 9,345,481, issued May 24, 2016, entitled "STAPLE CARTRIDGE TISSUE THICKNESS SENSOR SYSTEM," which is incorporated herein by reference in its entirety; U.S. Patent Application Publication No. 2014 / 0263552, published September 18, 2014, entitled "STAPLE CARTRIDGE TISSUE THICKNESS SENSOR SYSTEM," which is incorporated herein by reference in its entirety; and U.S. Patent Application No. 15 / 628,175, filed June 20, 2017, entitled "TECHNIQUES FOR ADAPTIVE CONTROL OF MOTOR VELOCITY OF A SURGICAL STAPLING AND CUTTING INSTRUMENT," which is incorporated herein by reference in its entirety. In a digital signal processing system, the absolute positioning system is coupled to a digital data acquisition system, where the output of the absolute positioning system has a finite resolution and sampling frequency. The absolute positioning system may include comparison and combination circuitry to combine the calculated response with the measured response using algorithms such as weighted average and theoretical control loops that drive the calculated response towards the measured response. The calculated response of the physical system takes into account properties such as mass, inertia, viscous friction, induced resistance, etc., in order to predict what the state and output of the physical system will be by knowing the input.

[0098] The absolute positioning system provides the absolute position of the displacement member upon powering up of the instrument without retracting or advancing the displacement member to a reset (zero or home) position, as may be required with conventional rotary encoders that simply count the number of steps taken by the motor 482 forward or backward to estimate the position of the device actuator, drive bar, knife, etc.

[0099] The sensor 474, e.g., a strain gauge or micro strain gauge, is configured to measure one or more parameters of the end effector, e.g., the amplitude of strain exerted on the anvil during the clamping operation, which can be indicative of the closure force applied to the anvil. The measured strain is converted to a digital signal and provided to the processor 462. Instead of or in addition to the sensor 474, a sensor 476, e.g., a load sensor, can measure the closure force applied to the anvil 914 by the closure drive system. For example, the sensor 476, e.g., a load sensor, can measure the firing force applied to the I-beam during the firing stroke of the surgical instrument or tool. The I-beam is configured to engage a wedge-shaped sled that is configured to cam the staple driver upward to drive the staples into deforming contact with the anvil. The I-beam also includes a sharp cutting edge that can be used to cut tissue as the I-beam is advanced distally by the firing bar. Alternatively, a current sensor 478 can be used to measure the current draw by the motor 482. The force required to advance the displacement member may correspond, for example, to the current drawn by the motor 482. The measured force is converted to a digital signal and provided to the processor 462.

[0100] In one form, a strain gauge sensor 474 can be used to measure the force applied by the end effector to the tissue. A strain gauge can be coupled to the end effector to measure the force applied by the end effector to the tissue being treated. A system for measuring the force applied to the gripped tissue by the end effector includes a strain gauge sensor 474, such as, for example, a micro strain gauge configured to measure one or more parameters of the end effector. In one aspect, the strain gauge sensor 474 can measure the amplitude or magnitude of the strain exerted on the jaw members of the end effector during the gripping operation, which can indicate compression of the tissue. The measured strain is converted to a digital signal and provided to the processor 462 of the microcontroller 461. The load sensor 476 can measure the force used to manipulate the knife element, for example, to cut the tissue captured between the anvil and the staple cartridge. A magnetic field sensor can be used to measure the thickness of the captured tissue. The magnetic field sensor measurements can also be converted to a digital signal and provided to the processor 462.

[0101] Measurements of tissue compression, tissue thickness, and / or force required to close the end effector on the tissue, as measured by sensors 474, 476, respectively, can be used by microcontroller 461 to characterize a selected position of the firing member and / or a corresponding value of the velocity of the firing member. In one example, memory 468 can store techniques, equations, and / or look-up tables that can be used by microcontroller 461 in the evaluation.

[0102] The surgical instrument or tool control system 470 may also include wired or wireless communication circuitry for communicating with a modular communications hub as shown in Figures 8-11.

[0103] FIG. 13 illustrates a control circuit 500 configured to control an embodiment of a surgical instrument or tool according to one embodiment of the present disclosure. The control circuit 500 can be configured to implement various processes described herein. The control circuit 500 may comprise a microcontroller comprising one or more processors 502 (e.g., microprocessors, microcontrollers) coupled to at least one memory circuit 504. The memory circuit 504 stores machine executable instructions that, when executed by the processor 502, cause the processor 502 to execute machine instructions to implement various processes described herein. The processor 502 may be any one of a number of single or multi-core processors known in the art. The memory circuit 504 may include volatile and non-volatile storage media. The processor 502 may include an instruction processing unit 506 and an arithmetic unit 508. The instruction processing unit may be configured to receive instructions from the memory circuit 504 of the present disclosure.

[0104] 14 illustrates a combinational logic circuit 510 configured to control an aspect of a surgical instrument or tool, according to one aspect of the present disclosure. The combinational logic circuit 510 can be configured to implement various processes described herein. The combinational logic circuit 510 may include a finite state machine including combinational logic 512 configured to receive data associated with the surgical instrument or tool at an input 514, process the data through the combinational logic 512, and provide an output 516.

[0105] FIG. 15 illustrates a sequential logic circuit 520 configured to control an aspect of a surgical instrument or tool according to one aspect of the disclosure. The sequential logic circuit 520 or the combinatorial logic 522 can be configured to implement various processes described herein. The sequential logic circuit 520 may include a finite state machine. The sequential logic circuit 520 may include, for example, the combinatorial logic 522, at least one memory circuit 524, and a clock 529. The at least one memory circuit 524 can store a current state of the finite state machine. In certain examples, the sequential logic circuit 520 may be synchronous or asynchronous. The combinatorial logic 522 is configured to receive data associated with the surgical instrument or tool from an input 526, process the data through the combinatorial logic 522, and provide an output 528. In other aspects, the circuit may include a combination of a processor (e.g., the processor 502 of FIG. 13) and a finite state machine that implements various processes herein. In other aspects, the finite state machine may include a combination of combinational logic (eg, combinational logic 510 of FIG. 14) and sequential logic 520.

[0106] 16 illustrates a surgical instrument or tool with multiple motors that can be activated to perform various functions. In a particular example, a first motor can be activated to perform a first function, a second motor can be activated to perform a second function, a third motor can be activated to perform a third function, a fourth motor can be activated to perform a fourth function, and so on. In a particular example, the multiple motors of the robotic surgical instrument 600 can be individually activated to produce a firing, closing, and / or articulation motion in the end effector. The firing, closing, and / or articulation motion can be transmitted to the end effector via a shaft assembly, for example.

[0107] In certain examples, the surgical instrument system or tool may include a firing motor 602. The firing motor 602 may be operably coupled to a firing motor drive assembly 604, which may be configured to transmit a firing motion generated by the motor 602 to an end effector, specifically to displace an I-beam member. In certain examples, the firing motion generated by the motor 602 may, for example, deploy staples from a staple cartridge into tissue captured by the end effector and / or advance a cutting blade of the I-beam element to cut the captured tissue. The I-beam element may be retracted by reversing the direction of the motor 602.

[0108] In certain examples, the surgical instrument or tool may include a closure motor 603. The closure motor 603 may be operatively coupled to a closure motor drive assembly 605, which may be configured to transmit a closure motion generated by the motor 603 to an end effector, specifically to displace a closure tube to close the anvil and compress tissue between the anvil and the staple cartridge. The closure motion may, for example, transition the end effector from an open configuration to an approximated configuration to capture tissue. The end effector may be transitioned to the open position by reversing the direction of the motor 603.

[0109] In certain examples, a surgical instrument or tool may include, for example, one or more articulation motors 606a, 606b. The motors 606a, 606b may be operatively coupled to corresponding articulation motor drive assemblies 608a, 608b that may be configured to transfer articulation motion generated by the motors 606a, 606b to an end effector. In certain examples, the articulation motion may, for example, cause the end effector to articulate relative to the shaft.

[0110] As discussed above, a surgical instrument or tool may include multiple motors that may be configured to perform various independent functions. In certain examples, multiple motors of a surgical instrument or tool may be independently or separately activated to perform one or more functions while other motors remain stopped. For example, articulation motors 606a, 606b may be activated to articulate an end effector while firing motor 602 remains stopped. Alternatively, firing motor 602 may be activated to fire multiple staples and / or advance a cutting edge while articulation motor 606 is stopped. Additionally, closure motor 603 may be activated simultaneously with firing motor 602 to distally advance a closure tube and an I-beam element, as described in more detail herein below.

[0111] In certain examples, a surgical instrument or tool may include a common control module 610 that can be used with multiple motors of the surgical instrument or tool. In certain examples, the common control module 610 can accommodate one of the multiple motors at a time. For example, the common control module 610 may be capable of individually coupling and decoupling multiple motors of a robotic surgical instrument. In certain examples, multiple motors of a surgical instrument or tool may share one or more common control modules, such as the common control module 610. In certain examples, multiple motors of a surgical instrument or tool can be independently and selectively engaged with the common control module 610. In certain examples, the common control module 610 can be selectively switched from coupling with one of the multiple motors of the surgical instrument or tool to coupling with another of the multiple motors of the surgical instrument or tool.

[0112] In at least one example, the common control module 610 can be selectively switched between operative engagement with the articulation motors 606a, 606b and operative engagement with either the firing motor 602 or the closure motor 603. In at least one embodiment, as shown in FIG. 16 , the switch 614 can move or transition between a number of positions and / or states. For example, in a first position 616, the switch 614 can electrically couple the common control module 610 to the firing motor 602, in a second position 617, the switch 614 can electrically couple the common control module 610 to the closure motor 603, in a third position 618a, the switch 614 can electrically couple the common control module 610 to the first articulation motor 606a, and in a fourth position 618b, the switch 614 can electrically couple the common control module 610 to the second articulation motor 606b. In certain examples, a separate common control module 610 can be electrically coupled to the firing motor 602, the closing motor 603, and the articulation motors 606a, 606b simultaneously. In certain examples, the switch 614 can be a mechanical switch, an electromechanical switch, a solid-state switch, or any suitable switching mechanism.

[0113] Each of the motors 602, 603, 606a, 606b may be equipped with a torque sensor to measure the output torque on the shaft of the motor. The force on the end effector may be sensed in any conventional manner, such as by a force sensor outside the jaws or by a torque sensor on the motor that actuates the jaws.

[0114] 16, common control module 610 may include a motor driver 626, which may include one or more H-bridge FETs. Motor driver 626 may modulate power transferred from a power source 628 to a motor coupled to common control module 610 based on, for example, input from a microcontroller 620 ("controller"). In certain examples, as described above, for example, microcontroller 620 may be used to determine the current drawn by a motor while the motor is coupled to common control module 610.

[0115] In particular examples, microcontroller 620 may include a microprocessor 622 ("processor") and one or more non-transitory computer-readable media or memory units 624 ("memory"). In particular examples, memory 624 may store various program instructions that, when executed, may cause processor 622 to perform multiple functions and / or calculations described herein. In particular examples, one or more of memory units 624 may be coupled to processor 622, for example.

[0116] In certain examples, the power source 628 may be used, for example, to power the microcontroller 620. In certain examples, the power source 628 may include a battery (or "battery pack" or "power pack"), such as, for example, a lithium ion battery. In certain examples, the battery pack may be configured to be releasably attached to the handle to power the surgical instrument 600. Multiple battery cells connected in series may be used as the power source 628. In certain examples, the power source 628 may be, for example, replaceable and / or rechargeable.

[0117] In various examples, the processor 622 can control the motor driver 626 to control the position, direction of rotation, and / or speed of the motors coupled to the common control module 610. In certain examples, the processor 622 can signal the motor driver 626 to stop and / or disable the motors coupled to the common control module 610. The term "processor" as used herein should be understood to include any suitable microprocessor, microcontroller, or other basic computing device that integrates the functionality of a computer's central processing unit (CPU) on one integrated circuit or up to a few integrated circuits. A processor is a general-purpose programmable device that accepts digital data as input, processes the data according to instructions stored in a memory, and provides the results as an output. It is an example of sequential digital logic since it has an internal memory. The processor operates on numbers and symbols represented in the binary system.

[0118] In one example, the processor 622 may be any single-core or multi-core processor, such as those known under the trade name ARM Cortex manufactured by Texas Instruments. In a particular example, the microcontroller 620 may be, for example, the LM 4F230H5QR available from Texas Instruments. In at least one embodiment, the Texas Instruments LM4F230H5QR is an ARM Cortex-M4F processor core that includes, among other characteristics readily available in the product data sheet, 256KB of on-chip memory of single-cycle flash memory or other non-volatile memory up to 40MHz, a pre-fetch buffer to improve performance above 40MHz, 32KB of single-cycle SRAM, internal ROM loaded with StellarisWare® software, 2KB of EEPROM, one or more PWM modules, one or more QEI analog, one or more 12-bit ADC with 12 analog input channels. Other microcontrollers may be readily substituted for use with the module 4410. Thus, the present disclosure should not be limited in this context.

[0119] In certain examples, the memory 624 may include program instructions for controlling each of the motors of the surgical instrument 600 that are connectable to the common control module 610. For example, the memory 624 may include program instructions for controlling the firing motor 602, the closing motor 603, and the articulation motors 606a, 606b. Such program instructions may cause the processor 622 to control the firing, closing, and articulation functions according to inputs from algorithms or control programs of the surgical instrument or tool. In certain examples, one or more mechanisms and / or sensors, such as, for example, the sensor 630, may be used to alert the processor 622 to the program instructions to be used in a particular setting. For example, the sensor 630 may alert the processor 622 to use program instructions associated with firing, closing, and articulating the end effector. In certain examples, the sensor 630 may include a position sensor that may be used to sense the position of the switch 614, for example. Thus, for example, when processor 622 detects via sensor 630 that switch 614 is in first position 616, processor 622 may use program instructions associated with firing an I-beam of the end effector, for example, when processor 622 detects via sensor 630 that switch 614 is in second position 617, and processor 622 may use program instructions associated with closing anvil, for example, when processor 622 detects via sensor 630 that switch 614 is in third position 618a or fourth position 618b.

[0120] 17 is a circuit diagram of a robotic surgical instrument 700 configured to operate a surgical tool described herein, according to one embodiment of the present disclosure. The robotic surgical instrument 700 may be programmed or configured to control distal / proximal translation of a displacement member, distal / proximal displacement of an closure tube, shaft rotation, and articulation using either single or multiple articulation drive couplings. In one embodiment, the surgical instrument 700 may be programmed or configured to individually control a firing member, a closure member, a shaft member, or one or more articulation members. The surgical instrument 700 includes a control circuit 710 configured to control a motorized firing member, a closure member, a shaft member, or one or more articulation members.

[0121] In one aspect, the robotic surgical instrument 700 includes a control circuit 710 configured to control the anvil 716 and I-beam 714 (including sharp cutting blade) portions of the end effector 702, the removable staple cartridge 718, the shaft 740, and one or more articulating members 742a, 742b via a number of motors 704a-704e. A position sensor 734 may be configured to provide position feedback of the I-beam 714 to the control circuit 710. Other sensors 738 may be configured to provide feedback to the control circuit 710. A timer / counter 731 provides timing and counting information to the control circuit 710. An energy source 712 may be provided to operate the motors 704a-704e, and a current sensor 736 provides motor current feedback to the control circuit 710. The motors 704a-704e may be individually operated by the control circuit 710 in open-loop or closed-loop feedback control.

[0122] In one aspect, the control circuitry 710 may comprise one or more microcontrollers, microprocessors, or other suitable processors for executing instructions that cause a processor or processors to perform one or more tasks. In one aspect, the timer / counter circuitry 731 provides an output signal, such as an elapsed time or a digital count, to the control circuitry 710 to correlate the position of the I-beam 714 determined by the position sensor 734 with the output of the timer / counter circuitry 731, such that the control circuitry 710 can determine the position of the I-beam 714 at a particular time (t) relative to a starting position or time (t) when the I-beam 714 is at a particular position relative to the starting position. The timer / counter 731 may be configured to measure elapsed time, count external events, or time an external event.

[0123] In one aspect, the control circuitry 710 may be programmed to control the function of the end effector 702 based on one or more tissue conditions. The control circuitry 710 may be programmed to sense tissue conditions, such as thickness, either directly or indirectly, as described herein. The control circuitry 710 may be programmed to select a firing control program or a closing control program based on the tissue condition. The firing control program may describe the distal motion of the displacement member. Different firing control programs may be selected to better handle different tissue conditions. For example, when thicker tissue is present, the control circuitry 710 may be programmed to translate the displacement member at a slower speed and / or with less power. When thinner tissue is present, the control circuitry 710 may be programmed to translate the displacement member at a higher speed and / or with more power. The closing control program may control the closing force applied to the tissue by the anvil 716. Other control programs control the rotation of the shaft 740 and the articulating members 742a, 742b.

[0124] In one aspect, the control circuitry 710 may generate motor set point signals. The motor set point signals may be provided to various motor controllers 708a-708e. The motor controllers 708a-708e may comprise one or more circuits configured to provide motor drive signals to the motors 704a-704e to drive the motors 704a-704e as described herein. In some embodiments, the motors 704a-704e may be brushed DC electric motors. For example, the speed of the motors 704a-704e may be proportional to the respective motor drive signals. In some embodiments, the motors 704a-704e may be brushless DC electric motors, and the respective motor drive signals may include PWM signals provided to one or more stator windings of the motors 704a-704e. Also, in some embodiments, the motor controllers 708a-708e may be omitted and the control circuitry 710 may directly generate the motor drive signals.

[0125] In one aspect, the control circuit 710 may initially operate each of the motors 704a-704e in an open-loop configuration for a first open-loop portion of the displacement member stroke. Based on the response of the robotic surgical instrument 700 during the open-loop portion of the stroke, the control circuit 710 may select a firing control program for a closed-loop configuration. The instrument response may include the translation distance of the displacement member during the open-loop portion, the time elapsed during the open-loop portion, the energy provided to one of the motors 704a-704e during the open-loop portion, the sum of the pulse widths of the motor drive signals, etc. After the open-loop portion, the control circuit 710 may implement the selected firing control program for a second portion of the displacement member stroke. For example, during the closed-loop portion of the stroke, the control circuit 710 may modulate one of the motors 704a-704e in a closed-loop manner based on translation data describing the position of the displacement member to translate the displacement member at a constant velocity.

[0126] In one aspect, the motors 704a-704e may receive power from an energy source 712. The energy source 712 may be a DC power source driven by a mains AC power source, a battery, a supercapacitor, or any other suitable energy source. The motors 704a-704e may be mechanically coupled to respective moveable mechanical elements, such as the I-beam 714, the anvil 716, the shaft 740, the articulation section 742a, and the articulation section 742b, via respective transmissions 706a-706e. The transmissions 706a-706e may include one or more gears or other coupling components for coupling the motors 704a-704e to the moveable mechanical elements. The position sensor 734 may sense the position of the I-beam 714. The position sensor 734 may be or include any type of sensor capable of generating position data indicative of the position of the I-beam 714. In some embodiments, the position sensor 734 may include an encoder configured to provide a series of pulses to the control circuitry 710 as the I-beam 714 translates distally and proximally. The control circuitry 710 may track the pulses to determine the position of the I-beam 714. Other suitable position sensors may be used, including, for example, a proximity sensor. Other types of position sensors may provide other signals indicative of the movement of the I-beam 714. Also, in some embodiments, the position sensor 734 may be omitted. If any of the motors 704a-704e are step motors, the control circuitry 710 may track the position of the I-beam 714 by summing the number and direction of steps the motor 704 is commanded to perform. The position sensor 734 may be located in the end effector 702 or in any other part of the instrument. The output of each of the motors 704a-704e includes a torque sensor 744a-744e for sensing force and has an encoder for sensing rotation of the drive shaft.

[0127] In one aspect, the control circuit 710 is configured to drive a firing member, such as an I-beam 714 portion of the end effector 702. The control circuit 710 provides motor settings to a motor controller 708a, which provides a drive signal to the motor 704a. The output shaft of the motor 704a is coupled to a torque sensor 744a. The torque sensor 744a is coupled to a transmission 706a, which is coupled to the I-beam 714. The transmission 706a includes movable mechanical elements, such as a rotating element and a firing member, for controlling the movement of the I-beam 714 in the distal and proximal directions along the longitudinal axis of the end effector 702. In one aspect, the motor 704a may be coupled to a knife gear assembly including a knife gear reduction set including a first knife drive gear and a second knife drive gear. The torque sensor 744a provides a firing force feedback signal to the control circuit 710. The firing force signal is indicative of the force required to fire or displace the I-beam 714. The position sensor 734 may be configured to provide the position of the I-beam 714 or the firing member along the firing stroke as a feedback signal to the control circuit 710. The end effector 702 may include additional sensors 738 configured to provide feedback signals to the control circuit 710. When ready for use, the control circuit 710 may provide a firing signal to the motor control 708a. In response to the firing signal, the motor 704a may drive the firing member distally along the longitudinal axis of the end effector 702 from a proximal start-of-stroke position to an end-of-stroke position distal to the start-of-stroke position. As the firing member translates distally, the I-beam 714 with a cutting element positioned at its distal end advances distally to cut tissue located between the staple cartridge 718 and the anvil 716.

[0128] In one aspect, the control circuit 710 is configured to drive a closure member, such as an anvil 716 of the end effector 702. The control circuit 710 provides motor settings to a motor control 708b, which provides a drive signal to a motor 704b. An output shaft of the motor 704b is coupled to a torque sensor 744b. The torque sensor 744b is coupled to a transmission 706b, which is coupled to the shaft 716. The transmission 706b includes a moving mechanical element, such as a rotating element and a closure member, for controlling the movement of the anvil 716 from the open and closed positions. In one aspect, the motor 704b is coupled to a closure gear assembly including a closure reduction gear set supported in meshing engagement with a closure spur gear. The torque sensor 744b provides a closure force feedback signal to the control circuit 710. The closure force feedback signal is indicative of the closure force applied to the anvil 716. The position sensor 734 may be configured to provide the position of the closure member as a feedback signal to the control circuit 710. An additional sensor 738 in the end effector 702 may provide a closure force feedback signal to the control circuit 710. The pivotable anvil 716 is positioned opposite the staple cartridge 718. When ready for use, the control circuit 710 may provide a closure signal to the motor control 708b. In response to the closure signal, the motor 704b advances the closure member to clamp tissue between the clamp arm 716 and the staple cartridge 718.

[0129] In one aspect, the control circuit 710 is configured to rotate a shaft member, such as the shaft 740, to rotate the end effector 702. The control circuit 710 provides motor settings to a motor controller 708c, which provides a drive signal to the motor 704c. The output shaft of the motor 704c is coupled to a torque sensor 744c. The torque sensor 744c is coupled to a transmission 706c, which is coupled to the shaft 740. The transmission 706c includes a movable mechanical element, such as a rotating element, to control the clockwise or counterclockwise rotation of the shaft 740 up to and beyond 360°. In one aspect, the motor 704c is coupled to a rotational transmission assembly including a tubular gear segment formed on (or attached to) the proximal end of the proximal closure tube to be operably engaged by a rotating gear assembly operably supported on the tool mounting plate. The torque sensor 744c provides a rotational force feedback signal to the control circuit 710. The rotational force feedback signal is indicative of the rotational force applied to the shaft 740. The position sensor 734 may be configured to provide the position of the closure member as a feedback signal to the control circuit 710. An additional sensor 738, such as a shaft encoder, may provide the rotational position of the shaft 740 to the control circuit 710.

[0130] In one aspect, the control circuit 710 is configured to articulate the end effector 702. The control circuit 710 provides motor settings to a motor controller 708d, which provides a drive signal to a motor 704d. An output shaft of the motor 704d is coupled to a torque sensor 744d. The torque sensor 744d is coupled to a transmission 706d, which is coupled to an articulation member 742a. ​​The transmission 706d includes a movable mechanical element, such as an articulation element, for controlling the articulation of the end effector 702 at ±65°. In one aspect, the motor 704d is coupled to an articulation nut, which is rotatably journaled on a proximal end portion of the distal spine portion and rotatably driven by an articulation assembly on the proximal end portion of the distal spine portion. The torque sensor 744d provides an articulation force feedback signal to the control circuit 710. The articulation force feedback signal is indicative of the articulation force applied to the end effector 702. A sensor 738 , such as an articulation encoder, may provide the articulation position of the end effector 702 to the control circuit 710 .

[0131] In another embodiment, the articulation function of the robotic surgical system 700 may include two articulation members, or linkages 742a, 742b. These articulation members 742a, 742b are driven by separate disks on a robot interface (rack) driven by two motors 708d, 708e. When a separate firing motor 704a is provided, each of the articulation linkages 742a, 742b can be driven antagonistically with respect to the other linkage to provide a resistive holding motion and load to the head when the head is not moving, and to provide an articulation motion when the head is articulating. The articulation members 742a, 742b are attached to the head at a fixed radius as the head rotates. Thus, as the head rotates, the mechanical efficiency of the push-pull linkage changes. This change in mechanical efficiency may be more pronounced with other articulation linkage drive systems.

[0132] In one aspect, one or more of the motors 704a-704e may comprise brushed DC motors with gearboxes and mechanical connections to the firing members, closure members, or articulation members. Another example includes electric motors 704a-704e operating movable mechanical elements such as displacement members, articulation connections, closure tubes, and shafts. External influences are the unmeasured and unpredictable influences of things such as tissue, surroundings, and friction on a physical system. Such external influences may be referred to as drags that act against one of the electric motors 704a-704e. External influences such as drags may cause the operation of a physical system to deviate from the desired operation of the physical system.

[0133] In one aspect, the position sensor 734 may be implemented as an absolute positioning system. In one aspect, the position sensor 734 may comprise a magnetic rotary absolute positioning system implemented as an AS5055EQFT single chip magnetic rotary position sensor available from Austria Microsystems, AG. The position sensor 734 may provide an absolute positioning system in conjunction with the control circuit 710. The position may include a number of Hall effect elements located above a magnet and coupled to a CORDIC processor, also known as the digit-by-digit method and the Boulder algorithm, which is provided to implement simple and efficient algorithms for calculating hyperbolic and trigonometric functions, requiring only addition, subtraction, bit shifting, and table lookup operations.

[0134] In one aspect, the control circuit 710 may be in communication with one or more sensors 738. The sensors 738 may be positioned on the end effector 702 and adapted to operate with the robotic surgical instrument 700 to measure various derived parameters such as gap distance versus time, tissue compression versus time, and anvil strain versus time. The sensors 738 may comprise magnetic sensors, magnetic field sensors, strain gauges, load cells, pressure sensors, force sensors, torque sensors, inductive sensors such as eddy current sensors, resistive sensors, capacitive sensors, optical sensors, and / or any other suitable sensors for measuring one or more parameters of the end effector 702. The sensors 738 may include one or more sensors. The sensors 738 may be positioned on the deck of the staple cartridge 718 to determine the position of the tissue using split electrodes. The torque sensors 744a-744e may be configured to sense forces such as firing force, closure force, and / or articulation force, among others. Thus, the control circuit 710 can sense (1) the closure load experienced by the distal closure tube and its position, (2) the firing member in the rack and its position, (3) which portion of the ultrasonic blade 718 has tissue on it, and (4) the load and position on both articulation rods.

[0135] In one aspect, the one or more sensors 738 may comprise a strain gauge, such as a micro strain gauge, configured to measure the magnitude of strain in the anvil 716 during the clamping state. The strain gauge provides an electrical signal that varies in amplitude with the magnitude of strain. The sensor 738 may comprise a pressure sensor configured to detect pressure created by the presence of compressed tissue between the anvil 716 and the staple cartridge 718. The sensor 738 may be configured to detect impedance of a tissue portion located between the anvil 716 and the staple cartridge 718, which impedance is indicative of the thickness and / or fullness of the tissue located therebetween.

[0136] In one aspect, the sensor 738 may be implemented as one or more limit switches, electromechanical devices, solid-state switches, Hall effect devices, magnetoresistive (MR) devices, giant magnetoresistive (GMR) devices, magnetometers, among others. In other implementations, the sensor 738 may be implemented as a solid-state switch that operates under the influence of light, such as a light sensor, an IR sensor, an ultraviolet sensor, among others. Additionally, the switch may be a solid-state device, such as a transistor (e.g., FET, junction FET, MOSFET, bipolar, etc.). In other implementations, the sensor 738 may include non-conductor-containing switches, ultrasonic switches, accelerometers, and inertial sensors, among others.

[0137] In one aspect, the sensor 738 may be configured to measure the force exerted by the closure drive system on the anvil 716. For example, one or more sensors 738 can be located at an interaction point between a closure tube and the anvil 716 to detect a closure force exerted by the closure tube on the anvil 716. The force exerted against the anvil 716 can represent tissue compression experienced by a tissue section captured between the anvil 716 and the staple cartridge 718. The one or more sensors 738 can be positioned at various interaction points along the closure drive system to detect the closure force exerted by the closure drive system on the anvil 716. The one or more sensors 738 may be sampled in real time during the clamping operation by a processor of the control circuit 710. The control circuit 710 receives the real time sample measurements to provide and analyze time based information to assess the closure force exerted on the clamp arm 716 in real time.

[0138] In one aspect, a current sensor 736 can be used to measure the current drawn by each of the motors 704a-704e. The force required to advance any of the moving mechanical elements, such as the I-beam 714, corresponds to the current drawn by one of the motors 704a-704e. The force is converted to a digital signal and provided to the control circuit 710. The control circuit 710 can be configured to simulate the response of the actual system of the instrument in the controller software. The displacement member can be actuated to move the I-beam 714 in the end effector 702 at or near a target velocity. The robotic surgical instrument 700 can include a feedback controller, which can be any one of any feedback controllers, including, but not limited to, a PID controller, a state feedback controller, a linear quadratic (LQR) controller, and / or an adaptive controller. The robotic surgical instrument 700 can include a power supply to convert a signal from the feedback controller into a physical input, such as, for example, a case voltage, a PWM voltage, a frequency modulated voltage, a current, a torque, and / or a force. Further details are disclosed in U.S. patent application Ser. No. 15 / 636,829, entitled "CLOSED LOOP VELOCITY CONTROL TECHNIQUES FOR ROBOTIC SURGICAL INSTRUMENT," filed Jun. 29, 2017, which is incorporated by reference in its entirety.

[0139] 18 shows a block diagram of a surgical instrument 750 programmed to control the distal translation of a displacement member, according to one embodiment of the present disclosure. In one embodiment, the surgical instrument 750 is programmed to control the distal translation of a displacement member, such as an I-beam 764. The surgical instrument 750 includes an anvil 766, an I-beam 764 (including a sharp cutting edge), and an end effector 752 that may include a removable staple cartridge 768.

[0140] The position, movement, displacement, and / or translation of a linear displacement member, such as I-beam 764, can be measured by an absolute positioning system, a sensor mechanism, and a position sensor 784. Because I-beam 764 is coupled to a longitudinally movable drive member, the position of I-beam 764 can be determined by measuring the position of the longitudinally movable drive member using position sensor 784. Thus, in the following description, the position, displacement, and / or translation of I-beam 764 can be achieved by position sensor 784 as described herein. Control circuitry 760 may be programmed to control the translation of a displacement member, such as I-beam 764. In some embodiments, control circuitry 760 may comprise one or more microcontrollers, microprocessors, or other suitable processors for executing instructions that cause a processor or processors to control a displacement member, such as I-beam 764, in the manner described. In one aspect, the timer / counter circuit 781 provides an output signal, such as an elapsed time or a digital count, to the control circuit 760 to correlate the position of the I-beam 764 determined by the position sensor 784 with the output of the timer / counter circuit 781 such that the control circuit 760 can determine the position of the I-beam 764 at a particular time (t) relative to a starting position. The timer / counter 781 may be configured to measure elapsed time, count external events, or measure the time of an external event.

[0141] The control circuitry 760 may generate a motor set point signal 772. The motor set point signal 772 may be provided to the motor controller 758. The motor controller 758 may comprise one or more circuits configured to provide a motor drive signal 774 to the motor 754 to drive the motor 754 as described herein. In some examples, the motor 754 may be a brushed DC electric motor. For example, the speed of the motor 754 may be proportional to the motor drive signal 774. In some examples, the motor 754 may be a brushless DC electric motor and the motor drive signal 774 may include a PWM signal provided to one or more stator windings of the motor 754. Also, in some examples, the motor controller 758 may be omitted and the control circuitry 760 may directly generate the motor drive signal 774.

[0142] The motor 754 may receive power from an energy source 762. The energy source 762 may be or may include a battery, a supercapacitor, or any other suitable energy source. The motor 754 may be mechanically coupled to the I-beam 764 via a transmission 756. The transmission 756 may include one or more gears or other coupling components for coupling the motor 754 to the I-beam 764. The position sensor 784 may sense the position of the I-beam 764. The position sensor 784 may be or may include any type of sensor capable of generating position data indicative of the position of the I-beam 764. In some embodiments, the position sensor 784 may include an encoder configured to provide a series of pulses to the control circuitry 760 as the I-beam 764 translates distally and proximally. The control circuitry 760 may track the pulses to determine the position of the I-beam 764. Other suitable position sensors may be used, including, for example, a proximity sensor. Other types of position sensors may provide other signals indicative of the movement of the I-beam 764. Also, in some embodiments, the position sensor 784 may be omitted. If the motor 754 is a step motor, the control circuitry 760 may track the position of the I-beam 764 by summing the number and direction of steps that the motor 754 is commanded to take. The position sensor 784 may be located in the end effector 752 or in any other part of the instrument.

[0143] The control circuitry 760 may be in communication with one or more sensors 788. The sensors 788 may be positioned on the end effector 752 and adapted to operate with the surgical instrument 750 to measure various inductive parameters, such as gap distance versus time, tissue compression versus time, and anvil strain versus time. The sensors 788 may comprise inductive sensors, such as magnetic sensors, magnetic field sensors, strain gauges, pressure sensors, force sensors, eddy current sensors, resistive sensors, capacitive sensors, optical sensors, and / or any other suitable sensors for measuring one or more parameters of the end effector 752. The sensors 788 may include one or more sensors.

[0144] The one or more sensors 788 may comprise a strain gauge, such as a micro strain gauge, configured to measure the magnitude of strain in the anvil 766 during the clamping condition. The strain gauge provides an electrical signal that varies in amplitude with the magnitude of strain. The sensor 788 may comprise a pressure sensor configured to detect pressure created by the presence of compressed tissue between the anvil 766 and the staple cartridge 768. The sensor 788 may be configured to detect the impedance of a tissue portion located between the anvil 766 and the staple cartridge 768, which impedance is indicative of the thickness and / or fullness of the tissue located therebetween.

[0145] The sensor 788 may be configured to measure the force exerted on the anvil 766 by the closure drive system. For example, one or more sensors 788 can be located at an interaction point between the closure tube and the anvil 766 to detect the closure force exerted on the anvil 766 by the closure tube. The force exerted against the anvil 766 can represent tissue compression experienced by tissue portions captured between the anvil 766 and the staple cartridge 768. The one or more sensors 788 can be positioned at various interaction points along the closure drive system to detect the closure force exerted on the anvil 766 by the closure drive system. The one or more sensors 788 may be sampled in real time during the clamping operation by a processor of the control circuit 760. The control circuit 760 receives the real time sample measurements to provide and analyze time based information to assess the closure force exerted on the clamp arm 766 in real time.

[0146] A current sensor 786 can be used to measure the current drawn by the motor 754. The force required to advance the I-beam 764 corresponds to the current drawn by the motor 754. The force is converted to a digital signal and provided to the control circuit 760.

[0147] The control circuitry 760 can be configured to simulate the response of the actual system of the instrument in the controller software. The displacement member can be actuated to move the I-beam 764 in the end effector 752 at or near a target velocity. The surgical instrument 750 can include a feedback controller, which can be any one of any feedback controllers, including, but not limited to, a PID, state feedback, LQR, and / or adaptive controller. The surgical instrument 750 can include a power supply to convert a signal from the feedback controller into a physical input, such as, for example, a case voltage, a PWM voltage, a frequency modulated voltage, a current, a torque, and / or a force.

[0148] The actual drive system of the surgical instrument 750 is configured to drive the displacement member, cutting member, or I-beam 764 by a brushed DC motor with a gearbox and mechanical linkage to the articulation and / or knife system. Another example is an electric motor 754 operating, for example, the displacement member and the articulation drive of an interchangeable shaft assembly. External influences are the unmeasured and unpredictable influences of things like tissue, surroundings, and friction on the physical system. Such external influences may be referred to as obstacles that act against the electric motor 754. External influences such as obstacles may cause the operation of the physical system to deviate from the desired operation of the physical system.

[0149] Various exemplary embodiments are directed to a surgical instrument 750 comprising an end effector 752 having a motor-driven surgical stapling and cutting means. For example, a motor 754 may drive a displacement member distally and proximally along a longitudinal axis of the end effector 752. The end effector 752 may comprise a pivotable anvil 766 and, if configured for use, a staple cartridge 768 positioned opposite the anvil 766. A clinician may grasp tissue between the anvil 766 and the staple cartridge 768 as described herein. When the instrument 750 is ready to be used, the clinician may provide a firing signal, for example, by pressing a trigger of the instrument 750. In response to the firing signal, the motor 754 may drive the displacement member distally along a longitudinal axis of the end effector 752 from a proximal start-of-stroke position to an end-of-stroke position distal to the start-of-stroke position. As the displacement member translates distally, an I-beam 764 having a cutting element positioned at its distal end may cut tissue between the staple cartridge 768 and the anvil 766 .

[0150] In various embodiments, the surgical instrument 750 may include a control circuit 760 programmed to control the distal translation of a displacement member, such as, for example, an I-beam 764, based on one or more tissue conditions. The control circuit 760 may be programmed to sense tissue conditions, such as thickness, either directly or indirectly, as described herein. The control circuit 760 may be programmed to select a firing control program based on the tissue condition. The firing control program may describe the distal motion of the displacement member. Different firing control programs may be selected to better handle different tissue conditions. For example, when thicker tissue is present, the control circuit 760 may be programmed to translate the displacement member at a slower speed and / or with lower power. When thinner tissue is present, the control circuit 760 may be programmed to translate the displacement member at a higher speed and / or with higher power.

[0151] In some embodiments, the control circuit 760 may initially operate the motor 754 in an open loop configuration for a first open loop portion of the displacement member stroke. Based on the response of the instrument 750 during the open loop portion of the stroke, the control circuit 760 may select a firing control program. The response of the instrument may include the translation distance of the displacement member during the open loop portion, the time elapsed during the open loop portion, the energy provided to the motor 754 during the open loop portion, the total pulse width of the motor drive signal, etc. After the open loop portion, the control circuit 760 may implement the selected firing control program for a second portion of the displacement member stroke. For example, during the closed loop portion of the stroke, the control circuit 760 may modulate the motor 754 in a closed loop manner based on translation data describing the position of the displacement member to translate the displacement member at a constant velocity. Further details are disclosed in U.S. patent application Ser. No. 15 / 720,852, filed Sep. 29, 2017, entitled "SYSTEM AND METHODS FOR CONTROLLING A DISPLAY OF A SURGICAL INSTRUMENT," which is incorporated by reference in its entirety.

[0152] 19 is a schematic diagram of a surgical instrument 790 configured to control various functions, according to one embodiment of the present disclosure. In one embodiment, the surgical instrument 790 is programmed to control the distal translation of a displacement member, such as an I-beam 764. The surgical instrument 790 includes an end effector 792 that may include an anvil 766, an I-beam 764, and a removable staple cartridge 768 that may be replaced with an RF cartridge 796 (shown in dashed lines).

[0153] In one aspect, the sensor 788 may be implemented as a limit switch, an electromechanical device, a solid-state switch, a Hall effect device, an MR device, a GMR device, a magnetometer, among others. In other implementations, the sensor 638 may be a solid-state switch that operates under the influence of light, such as a light sensor, an IR sensor, an ultraviolet sensor, among others. Additionally, the switch may be a solid-state device such as a transistor (e.g., FET, junction FET, MOSFET, bipolar, etc.). In other implementations, the sensor 788 may include a non-conductor-containing switch, an ultrasonic switch, an accelerometer, and an inertial sensor, among others.

[0154] In one aspect, the position sensor 784 may be implemented as an absolute positioning system with a magnetic rotary absolute positioning system implemented as an AS5055EQFT single chip magnetic rotary position sensor available from Austria Microsystems, AG. The position sensor 784 may provide an absolute positioning system in conjunction with the control circuit 760. The position may include multiple Hall effect elements located above a magnet and coupled to a CORDIC processor, also known as the digit-by-digit method and Boulder algorithm, which is provided to implement simple and efficient algorithms for calculating hyperbolic and trigonometric functions, requiring only addition, subtraction, bit shifting, and table lookup operations.

[0155] In one aspect, the I-beam 764 may be implemented as a knife member comprising a knife body operatively supporting a tissue-cutting blade thereon and may further include anvil engagement tabs or features and track engagement features or feet. In one aspect, the staple cartridge 768 may be implemented as a standard (mechanical) surgical fastener cartridge. In one aspect, the RF cartridge 796 may be implemented as an RF cartridge. These and other sensor configurations are described in U.S. Patent Application No. 15 / 628,175, filed June 20, 2017, entitled "TECHNIQUES FOR ADAPTIVE CONTROL OF MOTOR VELOCITY OF A SURGICAL STAPLING AND CUTTING INSTRUMENT," which is incorporated herein by reference in its entirety.

[0156] The position, movement, displacement, and / or translation of a linear displacement member, such as I-beam 764, can be measured by an absolute positioning system, sensor arrangement, and position sensor represented as position sensor 784. Because I-beam 764 is coupled to a longitudinally movable drive member, the position of I-beam 764 can be determined by measuring the position of the longitudinally movable drive member using position sensor 784. Thus, in the following description, the position, displacement, and / or translation of I-beam 764 can be achieved by position sensor 784 as described herein. Control circuitry 760 may be programmed to control the translation of a displacement member, such as I-beam 764. In some embodiments, control circuitry 760 may comprise one or more microcontrollers, microprocessors, or other suitable processors for executing instructions that cause a processor or processors to control a displacement member, e.g., I-beam 764, in the manner described. In one aspect, the timer / counter 781 provides an output signal, such as an elapsed time or a digital count, to the control circuitry 760 to correlate the position of the I-beam 764 determined by the position sensor 784 with the output of the timer / counter 781 such that the control circuitry 760 can determine the position of the I-beam 764 at a particular time (t) relative to a starting position. The timer / counter 781 may be configured to measure elapsed time, count external events, or measure the time of an external event.

[0157] The control circuitry 760 may generate a motor set point signal 772. The motor set point signal 772 may be provided to the motor controller 758. The motor controller 758 may comprise one or more circuits configured to provide a motor drive signal 774 to the motor 754 to drive the motor 754, as described herein. In some examples, the motor 754 may be a brushed DC electric motor. For example, the speed of the motor 754 may be proportional to the motor drive signal 774. In some examples, the motor 754 may be a brushless DC electric motor, and the motor drive signal 774 may include a PWM signal provided to one or more stator windings of the motor 754. Also, in some examples, the motor controller 758 may be omitted, and the control circuitry 760 may directly generate the motor drive signal 774.

[0158] The motor 754 may receive power from an energy source 762. The energy source 762 may be or may include a battery, a supercapacitor, or any other suitable energy source. The motor 754 may be mechanically coupled to the I-beam 764 via a transmission 756. The transmission 756 may include one or more gears or other coupling components for coupling the motor 754 to the I-beam 764. The position sensor 784 may sense the position of the I-beam 764. The position sensor 784 may be or may include any type of sensor capable of generating position data indicative of the position of the I-beam 764. In some embodiments, the position sensor 784 may include an encoder configured to provide a series of pulses to the control circuitry 760 as the I-beam 764 translates distally and proximally. The control circuitry 760 may track the pulses to determine the position of the I-beam 764. Other suitable position sensors may be used, including, for example, a proximity sensor. Other types of position sensors may provide other signals indicative of the movement of the I-beam 764. Also, in some embodiments, the position sensor 784 may be omitted. If the motor 754 is a stepper motor, the control circuit 760 may track the position of the I-beam 764 by summing the number and direction of steps the motor is commanded to take. The position sensor 784 may be located in the end effector 792 or in any other part of the instrument.

[0159] The control circuitry 760 may be in communication with one or more sensors 788. The sensors 788 may be positioned on the end effector 792 and adapted to operate with the surgical instrument 790 to measure various inductive parameters, such as gap distance versus time, tissue compression versus time, and anvil strain versus time. The sensors 788 may comprise inductive sensors, such as magnetic sensors, magnetic field sensors, strain gauges, pressure sensors, force sensors, eddy current sensors, resistive sensors, capacitive sensors, optical sensors, and / or any other suitable sensors for measuring one or more parameters of the end effector 792. The sensors 788 may include one or more sensors.

[0160] The one or more sensors 788 may comprise a strain gauge, such as a micro strain gauge, configured to measure the magnitude of strain in the anvil 766 during the clamping condition. The strain gauge provides an electrical signal that varies in amplitude with the magnitude of strain. The sensor 788 may comprise a pressure sensor configured to detect pressure created by the presence of compressed tissue between the anvil 766 and the staple cartridge 768. The sensor 788 may be configured to detect the impedance of a tissue portion located between the anvil 766 and the staple cartridge 768, which impedance is indicative of the thickness and / or fullness of the tissue located therebetween.

[0161] The sensor 788 may be configured to measure the force exerted on the anvil 766 by the closure drive system. For example, one or more sensors 788 can be located at an interaction point between the closure tube and the anvil 766 to detect the closure force exerted on the anvil 766 by the closure tube. The force exerted against the anvil 766 can represent tissue compression experienced by tissue portions captured between the anvil 766 and the staple cartridge 768. The one or more sensors 788 can be positioned at various interaction points along the closure drive system to detect the closure force exerted on the anvil 766 by the closure drive system. The one or more sensors 788 may be sampled in real time during the clamping operation by a processor portion of the control circuit 760. The control circuit 760 receives the real time sample measurements to provide and analyze time based information to assess the closure force exerted on the clamp arm 766 in real time.

[0162] A current sensor 786 can be used to measure the current drawn by the motor 754. The force required to advance the I-beam 764 corresponds to the current drawn by the motor 754. The force is converted to a digital signal and provided to the control circuit 760.

[0163] An RF energy source 794 is coupled to the end effector 792 and is applied to the RF cartridge 796 when the RF cartridge 796 is loaded into the end effector 792 in place of the staple cartridge 768. The control circuitry 760 controls the delivery of RF energy to the RF cartridge 796.

[0164] Further details are disclosed in U.S. patent application Ser. No. 15 / 636,096, filed Jun. 28, 2017, entitled "SURGICAL SYSTEM COUPLABLE WITH STAPLE CARTRIDGE AND RADIO FREQUENCY CARTRIDGE, AND METHOD OF USING SAME," which is incorporated by reference in its entirety.

[0165] Generator Hardware 20 is a simplified block diagram of a generator 800 configured to provide inductorless tuning, among other advantages. Additional details of the generator 800 are described in U.S. Patent No. 9,060,775, entitled "SURGICAL GENERATOR FOR ULTRASONIC AND ELECTROSURGICAL DEVICES," filed June 23, 2015, which is incorporated herein by reference in its entirety. The generator 800 may include a patient-isolated stage 802 in communication with a non-isolated stage 804 via a power transformer 806. A secondary winding 808 of the power transformer is housed within the isolated stage 802 and may include a tap configuration (e.g., center tap or non-center tap configuration) to define drive signal outputs 810a, 810b, 810c for delivering drive signals to various surgical instruments, such as ultrasonic surgical instruments, RF electrosurgical instruments, and multi-function surgical instruments including ultrasonic and RF energy modes that can be delivered alone or simultaneously. Specifically, the drive signal outputs 810a, 810c may output an ultrasonic drive signal (e.g., a 420V root mean square (RMS) drive signal) to the ultrasonic surgical instrument 104, and the drive signal outputs 810b, 810c may output an electrosurgical drive signal (e.g., a 100V RMS drive signal) to the RF electrosurgical instrument, with drive output 810b corresponding to the center tap of the power transformer 806.

[0166] In certain configurations, ultrasonic and electrosurgical drive signals may be provided simultaneously to separate surgical instruments and / or to a single surgical instrument, such as a multifunction surgical instrument, having the capability of delivering both ultrasonic and electrosurgical energy to tissue. It will be understood that the electrosurgical signals provided to either the dedicated electrosurgical instrument and / or the combined multifunction ultrasonic / electrosurgical instrument may be either therapeutic or sub-therapeutic level signals, and the sub-therapeutic signals may be used, for example, to monitor tissue or instrument conditions and provide feedback to the generator. For example, ultrasonic and RF signals may be delivered separately or simultaneously from a generator having a single output port to provide a desired output signal to the surgical instrument, as discussed in more detail below. Thus, the generator may combine ultrasonic and electrosurgical RF energy to deliver a combined energy to the multifunction ultrasonic / electrosurgical instrument. Bipolar electrodes may be positioned on one or both jaws of the end effector. One jaw may be driven by ultrasonic energy in addition to electrosurgical RF energy, working simultaneously. Ultrasonic energy may be used to cut tissue, while electrosurgical RF energy may be used to seal vessels.

[0167] The non-isolated stage 804 may include a power amplifier 812 having an output connected to a primary winding 814 of a power transformer 806. In certain configurations, the power amplifier 812 may include a push-pull amplifier. For example, the non-isolated stage 804 may further include a logic device 816 for providing a digital output to a digital-to-analog converter (DAC) circuit 818 that subsequently provides a corresponding analog signal to an input of the power amplifier 812. In certain configurations, the logic device 816 may include, for example, a programmable gate array (PGA), an FPGA, a programmable logic device (PLD), among other logic circuits. Thus, the logic device 816 may control any of a number of parameters (e.g., frequency, waveform, waveform amplitude) of the drive signal appearing at the drive signal inputs 810a, 810b, 810c by controlling the input of the power amplifier 812 via the DAC circuit 818. In certain embodiments, and as described below, the programmable logic 816, in conjunction with a processor (e.g., a DSP, as described below), may execute a number of DSP-based control algorithms and / or other control algorithms to control parameters of the drive signal output by the generator 800.

[0168] Power may be provided to the power rails of the power amplifier 812 by a switch mode regulator 820, e.g., a power converter. In a particular embodiment, the switch mode regulator 820 may include, for example, an adjustable buck regulator. The non-isolated stage 804 may further include a first processor 822, which in one embodiment may include, for example, a DSP processor, such as an Analog Devices ADSP-21469 SHARC DSP available from Analog Devices (Norwood, MA), although in various embodiments any suitable processor may be used. In a particular embodiment, the DSP processor 822 may control the operation of the switch-mode regulator 820 in response to voltage feedback data that the DSP processor 822 receives from the power amplifier 812 via an ADC circuit 824. In one embodiment, for example, the DSP processor 822 may receive as an input via the ADC circuit 824 the waveform envelope of a signal (e.g., an RF signal) amplified by the power amplifier 812. The DSP processor 822 may then control the switch-mode regulator 820 (e.g., a pulse-width modulated (PWM) output) so that the rail voltages supplied to the power amplifier 812 track the waveform envelope of the amplified signal. By dynamically modulating the rail voltages of the power amplifier 812 based on the waveform envelope, the efficiency of the power amplifier 812 may be significantly improved over a fixed rail voltage amplifier scheme.

[0169] In certain forms, the logic unit 816, together with the DSP processor 822, may implement a digital synthesis circuit, such as a direct digital synthesizer control scheme, to control the waveform shape, frequency and / or amplitude of the drive signal output by the generator 800. In one form, for example, the logic unit 816 may implement a DDS control algorithm by calling waveform samples stored in a dynamically updated look-up table (LUT), such as a RAM LUT that may be embedded in an FPGA. This control algorithm is particularly useful in ultrasonic applications where an ultrasonic transducer, such as an ultrasonic transducer, may be driven by a well-defined sinusoidal current at its resonant frequency. Minimizing or reducing the total distortion of the operating branch current can correspondingly minimize or reduce undesirable resonant effects, since other frequencies may excite parasitic resonances. Because the waveform of the drive signal output by the generator 800 is affected by various sources of distortion present in the output drive circuit (e.g., power transformer 806, power amplifier 812), voltage and current feedback data based on the drive signal may be input to an algorithm, such as an error control algorithm executed by the DSP processor 822, which compensates for the distortion by suitably pre-distorting or modifying the waveform samples stored in the LUT on a dynamic, on-the-fly basis (e.g., real-time). In one form, the amount or degree of pre-distortion applied to the LUT samples may be based on the error between the calculated motional branch current and the desired current waveform, the error being determined on a sample-by-sample basis. In this manner, the pre-distorted LUT samples, when processed by the drive circuit, may result in a motional branch drive signal having a desired waveform shape (e.g., sinusoidal) to optimally drive the ultrasonic transducer. In such a form, the LUT waveform samples thus do not represent the desired waveform of the drive signal, but rather the waveform required to ultimately generate the desired waveform of the motional branch drive signal when considering distortion effects.

[0170] The non-isolated stage 804 may further include a first ADC circuit 826 and a second ADC circuit 828 coupled to the output of the power transformer 806 via respective isolation transformers 830, 832 for sampling the voltage and current, respectively, of the drive signal output by the generator 800. In certain configurations, the ADC circuits 826, 828 may be configured to sample at a high speed (e.g., 80 megasamples per second (MSPS)) to allow for oversampling of the drive signal. In one configuration, for example, the sampling rate of the ADC circuits 826, 828 may allow for approximately 200 times oversampling of the drive signal (depending on the frequency). In certain configurations, the sampling operations of the ADC circuits 826, 828 may be performed by a single ADC circuit that receives the input voltage and current signals via a bidirectional multiplexer. The use of high speed sampling in the form of generator 800 may, among other things, allow for the calculation of complex currents flowing through the motional branches (which may be used in certain forms to implement the DDS-based waveform shape control described above), accurate digital filtering of the sampled signals, and calculation of real power consumption with high accuracy. The voltage and current feedback data output by ADC circuits 826, 828 may be received and processed by logic unit 816 (e.g., first-come, first-served (FIFO) buffers, multiplexers, etc.) and stored in a data memory for subsequent retrieval, for example, by DSP processor 822. As noted above, the voltage and current feedback data may be used as input to an algorithm to pre-distort or modify the LUT waveform samples on a dynamic and ongoing basis. In certain forms, this may require that when a voltage and current feedback data pair is obtained, each stored voltage and current feedback data pair is indexed based on or otherwise associated with the corresponding LUT sample output by logic unit 816. Synchronizing the LUT samples with the voltage and current feedback data in this manner contributes to precise timing and stability of the predistortion algorithm.

[0171] In certain forms, the voltage and current feedback data may be used to control the frequency and / or amplitude (e.g., current amplitude) of the drive signal. For example, in one form, the voltage and current feedback data may be used to determine the impedance phase. The frequency of the drive signal may then be controlled to minimize or reduce the difference between the determined impedance phase and the impedance phase set point (e.g., 0°), thus minimizing or reducing the effects of harmonic distortion and correspondingly improving impedance phase measurement accuracy. The determination of the phase impedance and frequency control signal may be implemented, for example, in the DSP processor 822, with the frequency control signal provided as an input to a DDS control algorithm implemented by the logic unit 816.

[0172] In another embodiment, for example, current feedback data may be monitored to maintain the current amplitude of the drive signal at a current amplitude set point. The current amplitude set point may be directly specified or indirectly determined based on specified voltage amplitude and power set points. In a particular embodiment, control of the current amplitude may be performed by a control algorithm, such as, for example, a proportional-integral-derivative (PID) control algorithm in the DSP processor 822. To suitably control the current amplitude of the drive signal, variables controlled by the control algorithm may include, for example, scaling of the LUT waveform samples stored in the logic device 816 and / or the full-scale output voltage of the DAC circuit 818 (which provides an input to the power amplifier 812) via the DAC circuit 834.

[0173] The non-isolated stage 804 may further include a second processor 836 to provide, among other things, user interface (UI) functionality. In one form, the UI processor 836 may include, for example, an Atmel AT91SAM9263 processor with an ARM 926EJ-S core, available from Atmel Corporation, San Jose, Calif. Examples of UI functionality supported by the UI processor 836 may include audible and visual user feedback, communication with peripherals (e.g., via a USB interface), communication with a foot switch, communication with an input device (e.g., a touch screen display), and communication with an output device (e.g., a speaker). The UI processor 836 may communicate with the DSP processor 822 and the logic device 816 (e.g., via an SPI bus). While the UI processor 836 may primarily support UI functionality, in certain forms, the UI processor 836 may also cooperate with the DSP processor 822 to provide hazard mitigation. For example, the UI processor 836 may be programmed to monitor various aspects of user input and / or other input (e.g., touch screen input, foot switch input, temperature sensor input) and may disable the drive output of the generator 800 when an erroneous condition is detected.

[0174] In certain configurations, both the DSP processor 822 and the UI processor 836 may, for example, determine and monitor the operating state of the generator 800. With respect to the DSP processor 822, the operating state of the generator 800 may represent, for example, which control and / or diagnostic processes are being executed by the DSP processor 822. With respect to the UI processor 836, the operating state of the generator 800 may represent, for example, which elements of the UI (e.g., display screen, sound) are being presented to the user. The DSP processor 822 and the UI processor 836 may each separately maintain the current operating state of the generator 800 and recognize and evaluate possible transitions from the current operating state. The DSP processor 822 may act as a master in this relationship and determine when transitions between operating states occur. The UI processor 836 may recognize valid transitions between operating states and may verify that a particular transition is appropriate. For example, when the DSP processor 822 commands the UI processor 836 to transition to a particular state, the UI processor 836 may verify that the requested transition is valid. If the requested transition between states is determined to be invalid by the UI processor 836, the UI processor 836 may place the generator 800 in a failure mode.

[0175] The non-isolated stage 804 may further include a controller 838 for monitoring input devices (e.g., capacitive touch sensors used to turn the generator 800 on and off, capacitive touch screen). In certain forms, the controller 838 may include at least one processor and / or other controller device in communication with the UI processor 836. In one form, for example, the controller 838 may include a processor (e.g., a Meg168 8-bit controller available from Atmel) configured to monitor user input provided via one or more capacitive touch sensors. In one form, the controller 838 may include a touch screen controller (e.g., a QT5480 touch screen controller available from Atmel) for controlling and managing acquisition of touch data from a capacitive touch screen.

[0176] In certain forms, when the generator 800 is in the "power off" state, the controller 838 may continue to receive operating power (e.g., via a line from a power source of the generator 800, such as the power source 854 described below). In this manner, the controller 838 may continue to monitor an input device 2150 (e.g., a capacitive touch sensor located on the front panel of the generator 800) for turning the generator 800 on and off. When the generator 800 is in the power off state, the controller 838 may activate a power source (e.g., enable operation of one or more DC / DC voltage transformers 856 of the power source 854) if activation of the "on / off" input device by a user is detected. Thus, the controller 838 may initiate a sequence to transition the generator 800 to the "power on" state. Conversely, if activation of the "on / off" input device is detected when the generator 800 is in the power on state, the controller 838 may initiate a sequence to transition the generator 800 to the power off state. For example, in certain configurations, the controller 838 may report activation of an “on / off” input device to the UI processor 836, which in turn performs the process sequence necessary for transitioning the generator 800 to a disconnected state. In such configurations, the controller 838 may not have a separate capability to remove power from the generator 800 after the powered on state of the generator 800 has been established.

[0177] In certain forms, the controller 838 may cause the generator 800 to provide audible or other sensory feedback to alert a user that a power on or power off sequence has begun. Such an alert may be provided at the start of a power on or power off sequence and prior to the start of other processes associated with the sequence.

[0178] In certain forms, the isolated stage 802 may include an instrument interface circuit 840 to provide a communications interface between, for example, the surgical instrument's control circuitry (e.g., control circuitry including handpiece switches) and components of the non-isolated stage 804, such as, for example, the logic device 816, the DSP processor 822, and / or the UI processor 836. The instrument interface circuit 840 may exchange information with components of the non-isolated stage 804 via a communications link that maintains a suitable degree of electrical isolation between the isolated stage 802 and the non-isolated stage 804, such as, for example, an IR-based communications link. For example, the instrument interface circuit 840 may be powered using a low dropout voltage regulator powered by an isolation transformer driven from the non-isolated stage 804.

[0179] In one form, the instrument interface circuit 840 may include a logic device 842 (e.g., logic circuit, programmable logic circuit, PGA, FPGA, PLD) in communication with a signal conditioning circuit 844. The signal conditioning circuit 844 may be configured to receive a periodic signal (e.g., a 2 kHz square wave) from the logic device 842 to generate a bipolar interrogation signal having the same frequency. The interrogation signal may be generated, for example, using a bipolar current source fed by a differential amplifier. The interrogation signal may be communicated to a surgical device control circuit (e.g., using a conductive pair in a cable connecting the generator 800 to the surgical device) and monitored to determine a state or configuration of the control circuit. The control circuit may include a number of switches, resistors, and / or diodes and may modify one or more characteristics (e.g., amplitude, rectification) of the interrogation signal such that the state or configuration of the control circuit is individually identifiable based on the one or more characteristics. For example, in one form, the signal conditioning circuit 844 may include an ADC circuit to generate a sample of a voltage signal appearing across an input of the control circuit resulting from the path traversed by the interrogation signal. The logic circuitry 842 (or components of the non-isolated stage 804) may then determine the state or configuration of the control circuitry based on the ADC circuit samples.

[0180] In one form, the instrument interface circuit 840 may include a first data circuit interface 846 to enable the exchange of information between the logic circuit 842 (or other elements of the instrument interface circuit 840) and a first data circuit disposed within or otherwise associated with the surgical instrument. In certain forms, for example, the first data circuit may be disposed within a cable or adapter integrally attached to a surgical instrument handpiece for interfacing with a particular surgical instrument type or model having the generator 800. The first data circuit may be implemented in any suitable manner and may communicate with the generator according to any suitable protocol, including, for example, those described herein with respect to the first data circuit. In certain forms, the first data circuit may include a non-volatile storage device, such as an EEPROM device. In certain forms, the first data circuit interface 846 may be implemented separately from the logic circuit 842 and may include suitable circuitry (e.g., separate logic, processor) to enable communication between the logic circuit 842 and the first data circuit. In other embodiments, the first data circuit interface 846 may be integral to the logic circuit 842 .

[0181] In certain configurations, the first data circuit 2006 may store information regarding the particular surgical instrument with which the first data circuit is associated. Such information may include, for example, a model number, a serial number, the number of operations the surgical instrument was used in, and / or any other type of information. This information may be read by the instrument interface circuit 840 (e.g., by the logic device 842) and communicated to components of the non-isolated stage 804 (e.g., the logic device 816, the DSP processor 822, and / or the UI processor 836) for presentation to a user via an output device and / or for control of the functions or operations of the generator 800. Additionally, any type of information may be communicated to the first data circuit for internal storage via the first data circuit interface 846 (e.g., using the logic circuit 842). Such information may include, for example, the most recent number of operations the surgical instrument was used in and / or the date and / or time of its use.

[0182] As noted above, surgical instruments may be removable from the handpiece to facilitate interchangeability and / or disposability of the instruments (e.g., multi-function surgical instruments may be removable from the handpiece). In such cases, conventional generators may be limited in their ability to recognize the particular instrument configuration being used and correspondingly optimize their control and diagnostic processes. However, adding readable data circuitry to the surgical instrument to address this issue is problematic from a compatibility standpoint. For example, designing a surgical instrument to be backward compatible with a generator that lacks the necessary data read functionality may not be practical due to, for example, different signaling schemes, design complexity and cost. The instrument forms discussed herein address these concerns by economically using data circuitry that may be implemented in existing surgical instruments and minimizing design changes to maintain compatibility of the surgical instrument with modern generator platforms.

[0183] Additionally, configurations of the generator 800 may enable communication with an instrument-based data circuit. For example, the generator 800 may be configured to communicate with a second data circuit housed within an instrument (e.g., a multifunction surgical instrument). In some configurations, the second data circuit is implemented in many configurations similar to the configurations of the first data circuit described herein. The instrument interface circuit 840 may include a second data circuit interface 848 that enables this communication. In one configuration, the second data circuit interface 848 may include a tri-state digital interface, although other interfaces may also be used. In certain configurations, the second data circuit may generally be any circuit for transmitting and / or receiving data. In one configuration, for example, the second data circuit may store information regarding the particular surgical instrument with which the second data circuit is associated. Such information may include, for example, a model number, a serial number, the number of operations the surgical instrument has been used, and / or any other type of information.

[0184] In some forms, the second data circuit may store information regarding electrical and / or ultrasonic characteristics of an associated transducer, end effector, or ultrasonic drive system. For example, the first data circuit may indicate a burn-in frequency slope, as described herein. Additionally or alternatively, any type of information may be communicated (e.g., using logic circuit 842) to the second data circuit for internal storage via second data circuit interface 848. Such information may include, for example, the most recent number of operations the instrument was used for, and / or the date and / or time of its use. In certain forms, the second data circuit may transmit data obtained by one or more sensors (e.g., instrument-based temperature sensors). In certain forms, the second data circuit may receive data from the generator 800 and provide an indication (e.g., a light emitting diode indication or other visual indication) to the user based on the received data.

[0185] In certain forms, the second data circuit and the second data circuit interface 848 may be configured such that communication between the logic circuit 842 and the second data circuit can occur without the need to provide additional conductors for this purpose (e.g., a dedicated conductor in the cable connecting the handpiece to the generator 800). In one form, information may be communicated to and from the second data circuit using a one-wire bus communication scheme implemented on existing cable wiring, for example, where one of the conductors used transmits an interrogation signal from the signal conditioning circuit 844 to the control circuitry in the handpiece. In this manner, design changes or modifications to the surgical instrument that may otherwise be required are minimized or reduced. Furthermore, because different types of communications carried out on a common physical channel can be frequency band separated, the presence of the second data circuit is "invisible" to generators that do not have the necessary data reading capabilities, thus enabling backward compatibility of the surgical instrument.

[0186] In certain configurations, the isolation stage 802 may include at least one blocking capacitor 850-1 connected to the drive signal output 810b to prevent direct current from passing through the patient. A single blocking capacitor may be required, for example, to comply with medical regulations or standards. Although failure in a single capacitor design is relatively rare, such failure may nevertheless have negative consequences. In one configuration, a second blocking capacitor 850-2 may be provided in series with the blocking capacitor 850-1, and current leakage from a point between the blocking capacitors 850-1 and 850-2 is monitored by an ADC circuit 852 for sampling a voltage induced by the leakage current. The samples may be received, for example, by the logic circuit 842. The generator 800 may determine when at least one of the blocking capacitors 850-1, 850-2 has failed based on a change in the leakage current (as indicated by a voltage sample), providing an advantage over a single capacitor design having a single point of failure.

[0187] In certain forms, the non-isolated stage 804 may include a power supply 854 for delivering DC power at a suitable voltage and current. The power supply may include, for example, a 400 W power supply for delivering a 48 VDC system voltage. The power supply 854 may further include one or more DC / DC voltage converters 856 for receiving the output of the power supply and generating a DC output at the voltage and current required by the various components of the generator 800. As described above in connection with the controller 838, one or more of the DC / DC voltage converters 856 may receive input from the controller 838 when activation of an “on / off” input device by a user is detected by the controller 838 to enable operation or activation of the DC / DC voltage converters 856.

[0188] FIG. 21 illustrates an example of a generator 900, which is a form of generator 800 (FIG. 20). The generator 900 is configured to deliver multiple energy modalities to a surgical instrument. The generator 900 provides RF and ultrasonic signals, either alone or simultaneously, for delivering energy to the surgical instrument. The RF and ultrasonic signals may be provided alone or in combination, and may be provided simultaneously. As described above, at least one generator output can deliver multiple energy modalities (e.g., ultrasonic, bipolar or monopolar RF, irreversible and / or reversible electroporation, and / or microwave energy, among others) through a single port, which signals can be delivered individually or simultaneously to an end effector to treat tissue.

[0189] The generator 900 comprises a processor 902 coupled to a waveform generator 904. The processor 902 and waveform generator 904 are configured to generate various signal waveforms based on information stored in a memory (not shown for clarity of disclosure) coupled to the processor 902. Digital information related to the waveform is provided to the waveform generator 904, which includes one or more DAC circuits to convert the digital input to an analog output. The analog output is provided to an amplifier 1106 for signal conditioning and amplification. The conditioned and amplified output of the amplifier 906 is coupled to a power transformer 908. The signal is coupled across the power transformer 908 to a secondary side on the patient isolated side. A first signal of a first energy modality is provided to the surgical instrument between terminals labeled ENERGY1 and RETURN. A second signal of a second energy modality is coupled across a capacitor 910 and provided to the surgical instrument between terminals labeled ENERGY2 and RETURN. It will be appreciated that more than two energy modalities may be output, and thus the subscript "n" may be used to indicate that up to n ENERGYn terminals are provided, where n is a positive integer greater than 1. It will also be appreciated that up to "n" return paths (RETURNn) may be provided without departing from the scope of this disclosure.

[0190] A first voltage sense circuit 912 is coupled across the terminals labeled ENERGY1 and RETURN paths and measures the output voltage therebetween. A second voltage sense circuit 924 is coupled across the terminals labeled ENERGY2 and RETURN paths and measures the output voltage therebetween. A current sense circuit 914 is disposed in series with the RETURN section on the secondary side of the illustrated power transformer 908 to measure the output current of either energy modality. If different return paths are provided for each energy modality, a separate current sense circuit must be provided in each return section. The outputs of the first voltage sense circuit 912 and the second voltage sense circuit 924 are provided to corresponding isolation transformers 916, 922, and the output of the current sense circuit 914 is provided to another isolation transformer 918. The outputs of the isolation transformers 916, 928, 922 on the primary side (non-patient isolated side) of the power transformer 908 are provided to one or more ADC circuits 926. The digitized output of the ADC circuit 926 is provided to the processor 902 for further processing and calculations. Output voltage and output current feedback information can be used to adjust the output voltage and current provided to the surgical instrument and to calculate output impedance, among other parameters. Input / output communication between the processor 902 and the patient isolation circuit is provided through an interface circuit 920. Sensors may also be in electrical communication with the processor 902 via the interface circuit 920.

[0191] In one aspect, the impedance may be determined by the processor 902 by dividing the output of a first voltage sense circuit 912 coupled across terminals labeled ENERGY1 / RETURN or a second voltage sense circuit 924 coupled across terminals labeled ENERGY2 / RETURN by the output of a current sense circuit 914 placed in series with the RETURN section of the secondary side of the power transformer 908. The outputs of the first voltage sense circuit 912 and the second voltage sense circuit 924 are provided to separate isolation transformers 916, 922, and the output of the current sense circuit 914 is provided to another isolation transformer 916. Digitized voltage and current sense measurements from the ADC circuit 926 are provided to the processor 902 to calculate the impedance. As an example, the first energy modality ENERGY1 may be ultrasound energy and the second energy modality ENERGY2 may be RF energy. Yet, in addition to ultrasonic energy modalities and bipolar or monopolar RF energy modalities, other energy modalities include irreversible and / or reversible electroporation and / or microwave energy, among others. Also, while the example illustrated in FIG. 21 shows that a single return path (RETURN) may be provided to two or more energy modalities, in other embodiments, multiple return paths RETURNn may be provided to each energy modality ENERGYn. Thus, as described herein, the impedance of the ultrasonic transducer may be measured by dividing the output of the first voltage sensing circuit 912 by the current sensing circuit 914, and the impedance of the tissue may be measured by dividing the output of the second voltage sensing circuit 924 by the current sensing circuit 914.

[0192] As shown in FIG. 21, the generator 900, which includes at least one output port, may include a power transformer 908 with a single output and multiple taps to provide power to an end effector in the form of one or more energy modalities, such as, for example, ultrasonic, bipolar or monopolar RF, irreversible and / or reversible electroporation, and / or microwave energy, among others, depending on the type of tissue treatment being performed. For example, the generator 900 may deliver energy with either monopolar or bipolar RF electrosurgical electrodes, at high voltage and low current to drive an ultrasonic transducer, at low voltage and high current to drive an RF electrode for tissue sealing, or in a coagulation waveform for spot coagulation. The output waveform from the generator 900 may be steered, switched, or filtered to provide the frequency to the end effector of the surgical instrument. The connection of the ultrasonic transducer to the output of the generator 900 would preferably be located between the outputs labeled ENERGY1 and RETURN shown in FIG. 21. In one embodiment, the connection of the RF bipolar electrode to the output of the generator 900 would preferably be located between the output labeled ENERGY2 and the output labeled RETURN. In the case of a unipolar output, the preferred connection would be an active electrode (e.g., a pencil or other probe) to a suitable return pad connected to the ENERGY2 and RETURN outputs.

[0193] Further details are disclosed in U.S. Patent Application Publication No. 2017 / 0086914, published March 30, 2017, entitled "TECHNIQUES FOR OPERATING GENERATOR FOR DIGITALLY GENERATING ELECTRICAL SIGNAL WAVEFORMS AND SURGICAL INSTRUMENTS," which is incorporated herein by reference in its entirety.

[0194] As used throughout this description, the term "wireless" and its derivatives may be used to describe circuits, devices, systems, methods, techniques, communication channels, etc. that may communicate data through the use of modulated electromagnetic radiation over a non-solid medium. This term does not imply that the associated devices do not include any wires, although in some aspects they may not be present. The communication modules may implement any of a number of wireless or wired communication standards or protocols, including but not limited to Wi-Fi (IEEE 802.11 family), WiMAX (IEEE 802.16 family), IEEE 802.20, Long Term Evolution (LTE), Ev-DO, HSPA+, HSDPA+, HSUPA+, EDGE, GSM, GPRS, CDMA, TDMA, DECT, Bluetooth, Ethernet derivatives thereof, as well as any other wireless and wired protocols designated 3G, 4G, 5G, and beyond. The computing module may include multiple communication modules. For example, the first communication module may be dedicated to short-range wireless communication such as Wi-Fi and Bluetooth, and the second communication module may be dedicated to long-range wireless communication such as GPS, EDGE, GPRS, CDMA, WiMAX, LTE, and Ev-DO.

[0195] As used herein, a processor or processing unit is an electronic circuit that performs operations on some external data source, usually a memory or some other data stream. The term is used herein to refer to a system that combines many dedicated "processors" or a central processor (central processing unit) within a computer system, especially a system on a chip (SoC).

[0196] As used herein, a system on a chip or system on a chip (SoC or SOC) is an integrated circuit (also known as an "IC" or "chip") that integrates all the components of a computer or other electronic system. It can include digital, analog, mixed-signal, and often high-frequency functions, all on a single substrate. An SoC integrates a microcontroller (or microprocessor) with modern peripherals such as a graphics processing unit (GPU), Wi-Fi module, or co-processor. An SoC may or may not include built-in memory.

[0197] As used herein, a microcontroller or controller is a system that integrates a microprocessor with peripheral circuits and memory. A microcontroller (or MCU for microcontroller unit) may be implemented as a small computer on a single integrated circuit. This may be similar to an SoC, which may include a microcontroller as one of its components. A microcontroller may house one or more core processing units (CPUs) along with memory and programmable input / output peripherals. Program memory in the form of ferroelectric RAM, NOR flash, or OTP ROM, and a small amount of RAM are often also included on the chip. Microcontrollers may be employed for embedded applications, as opposed to microprocessors used in personal computers or other general-purpose applications that are composed of various separate chips.

[0198] As used herein, the term controller or microcontroller may be a standalone IC or chip device that interfaces with a peripheral device, or it may be the link between two parts of a computer or controller on an external device that manages the operation of (and connections with) that device.

[0199] Any of the processors or microcontrollers described herein may be any single-core or multi-core processor, such as those known under the trade name ARM Cortex manufactured by Texas Instruments. In one aspect, the processor may be an LM4F230H5QR ARM Cortex-M4F processor core available from Texas Instruments, including, for example, 256KB of on-chip memory of single-cycle flash memory or other non-volatile memory up to 40MHz, a pre-fetch buffer to improve performance above 40MHz, 32KB of single-cycle serial random access memory (SRAM), internal read-only memory (ROM) loaded with StellarisWare® software, 2KB of electrically erasable programmable read-only memory (EEPROM), one or more pulse width modulation (PWM) modules, one or more quadrature encoder input (QEI) analogs, one or more 12-bit analog-to-digital converters (ADCs) with 12 analog input channels, details of which are available in the product data sheet.

[0200] In one aspect, the processor may include a safety controller, including two controller families such as TMS570 and RM4x, also known under the trade name Hercules ARM Cortex R4, manufactured by Texas Instruments. The safety controller may be specifically configured for IEC 61508 and ISO 26262 safety limiting applications, among others, to provide advanced integrated safety mechanisms while offering scalable performance, connectivity, and memory options.

[0201] Modular devices include modules that can be received in a surgical hub (e.g., as described in connection with FIG. 3 and FIG. 9 ) and surgical devices or instruments that can be connected to various modules to connect or pair with corresponding surgical hubs. Modular devices include, for example, intelligent surgical instruments, medical imaging devices, suction / irrigation devices, smoke evacuators, energy generators, ventilators, aspirators, and displays. The modular devices described herein can be controlled by a control algorithm. The control algorithm can be executed on the modular device itself, on the surgical hub to which the particular modular device is paired, or on both the modular device and the surgical hub (e.g., via a distributed computing architecture). In some examples, the control algorithm of the modular device controls the device based on data sensed by the modular device itself (i.e., by sensors in, on, or connected to the modular device). This data can relate to the patient during surgery (e.g., tissue characteristics or injection pressure) or the modular device itself (e.g., advancing knife speed, motor current, or energy level). For example, a control algorithm for a surgical stapling and severing instrument may control the speed at which the instrument's motor drives the knife through tissue based on the resistance the knife encounters as it advances.

[0202] Cloud system hardware and function modules FIG. 22 is a block diagram of a computer-implemented interactive surgical system according to at least one aspect of the present disclosure. In one aspect, the computer-implemented interactive surgical system is configured to monitor and analyze data regarding the operation of various surgical systems, including surgical hubs, surgical instruments, robotic devices, and operating rooms or medical facilities. The computer-implemented interactive surgical system includes a cloud-based analysis system. Although the cloud-based analysis system is described as a surgical system, it is not necessarily limited to such and may be a cloud-based medical system. As shown in FIG. 22, the cloud-based analysis system includes a plurality of surgical instruments 7012 (which may be the same as or similar to the instruments 112), a plurality of surgical hubs 7006 (which may be the same as or similar to the hubs 106), and a surgical data network 7001 (which may be the same as or similar to the network 201) coupling the surgical hubs 7006 to a cloud 7004 (which may be the same as or similar to the cloud 204). Each of the plurality of surgical hubs 7006 is communicatively coupled to one or more surgical instruments 7012. The hub 7006 is also communicatively coupled to a cloud 7004 of computer-implemented interactive surgical systems via a network 7001. The cloud 7004 is a remote, centralized source of hardware and software for storing, manipulating, and communicating data generated based on the operation of various surgical systems. As shown in FIG. 22, access to the cloud 7004 is achieved via a network 7001, which may be the Internet or any other suitable computer network. The surgical hub 7006 coupled to the cloud 7004 may be considered the client side of a cloud computing system (i.e., a cloud-based analysis system). A surgical instrument 7012 is paired with the surgical hub 7006 for control and performance of various surgical procedures or operations described herein.

[0203] In addition, the surgical instrument 7012 may include a transceiver for data transmission to and from the corresponding surgical hub 7006 (which may also include a transceiver). The combination of the surgical instrument 7012 and the corresponding hub 7006 may indicate a particular location, such as an operating room within a medical facility (e.g., a hospital) for providing a medical procedure. For example, the memory of the surgical hub 7006 may store the location data. As shown in FIG. 22, the cloud 7004 includes a central server 7013 (which may be the same as or similar to the remote server 7013), a hub application server 7002, a data analysis module 7034, and an input / output ("I / O") interface 7006. The central server 7013 of the cloud 7004 collectively manages the cloud computing system, which includes monitoring requests by the client modules 7006 and managing the processing power of the cloud 7004 to execute the requests. Each of the central servers 7013 includes one or more processors 7008 coupled to a suitable memory device 7010, which may include volatile memory such as random access memory (RAM) and non-volatile memory such as magnetic storage. The memory device 7010 may include machine-executable instructions that, when executed, cause the processor 7008 to execute a data analysis module 7034 for cloud-based data analysis, actions, recommendations, and other operations described below. Additionally, the processor 7008 may execute the data analysis module 7034 independently of or in conjunction with a hub application executed independently by the hub 7006. The central servers 7013 also include an aggregated medical data database 2212, which may reside in the memory 2210.

[0204] Based on the connection to the various surgical hubs 7006 via the network 7001, the cloud 7004 may aggregate data from the various surgical instruments 7012 and the particular data generated by their corresponding hubs 7006. Such aggregated data may be stored in the aggregated medical database 7012 of the cloud 7004. In particular, the cloud 7004 may advantageously perform data analysis and operations on the aggregated data to result in functionality that an individual hub 7006 cannot achieve by itself. To this end, as shown in FIG. 22, the cloud 7004 and the surgical hubs 7006 are communicatively coupled to send and receive information. The I / O interface 7006 is connected to the multiple surgical hubs 7006 via the network 7001. In this manner, the I / O interface 7006 may be configured to transfer information between the surgical hubs 7006 and the aggregated medical data database 7011. The I / O interface 7006 may thus facilitate read / write operations of the cloud-based analysis system. Such read / write operations may be performed upon request from the hubs 7006. These requests may be sent to the hub 7006 via the hub application. The I / O interface 7006 may include one or more high speed data ports, which may include a Universal Serial Bus (USB) port, an IEEE 1394 port, and Wi-Fi and Bluetooth I / O interfaces for connecting the cloud 7004 to the hub 7006. The hub application server 7002 of the cloud 7004 is configured to host and provide shared functionality to software applications (e.g., hub applications) executed by the surgical hub 7006. For example, the hub application server 7002 may manage requests made by the hub application to control access to the aggregated medical data database 7011 and perform load balancing. The data analysis module 7034 is described in more detail with reference to FIG. 23.

[0205] The particular cloud computing system configuration described in this disclosure is specifically designed to address various problems that arise in the context of medical operations and procedures performed using medical devices such as surgical instruments 7012, 112. In particular, the surgical instruments 7012 may be digital surgical devices configured to interact with the cloud 7004 to implement techniques to improve surgical outcomes. The various surgical instruments 7012 and / or the surgical hub 7006 may include touch-controlled user interfaces such that a clinician may control aspects of the interaction between the surgical instruments 7012 and the cloud 7004. Other suitable user interfaces for control, such as an auditory controlled user interface, may also be used.

[0206] FIG. 23 is a block diagram illustrating a functional architecture of a computer-implemented interactive surgical system according to at least one aspect of the present disclosure. The cloud-based analysis system includes a number of data analysis modules 7034 that may be executed by a processor 7008 of the cloud 7004 to provide data analysis solutions to problems specifically arising in the medical field. As shown in FIG. 23, the functionality of the cloud-based data analysis module 7034 may be supported via a hub application 7014 that may be accessed in relation to the surgical hub 7006 via a hub application 7014 hosted by a hub application server 7002. The cloud processor 7008 and the hub application 7014 may work in conjunction to execute the data analysis module 7034. An application program interface (API) 7016 defines a set of protocols and routines corresponding to the hub application 7014. In addition, the API 7016 manages the storage and retrieval of data to the aggregated medical database 7012 for the operation of the application 7014. A cache 7018 is also coupled to the API 7016 for storing data (e.g., temporarily) and for more efficient retrieval of data used by the application 7014. 23 includes modules for resource optimization 7020, data collection and aggregation 7022, authorization and security 7024, control program updates 7026, patient outcome analysis 7028, recommendations 7030, and data classification and prioritization 7032. Other suitable data analysis modules may also be implemented by the cloud 7004, according to some aspects. In one aspect, a data analysis module is used to make certain recommendations based on an analysis of trends, outcomes, and other data.

[0207] For example, the data collection and aggregation module 7022 may be used to generate self-describing data (e.g., metadata), including identifying salient features or configurations (e.g., trends), managing redundant data sets, and storing data into paired data sets that may be grouped by procedure, but not necessarily matched to actual surgical procedure dates and surgeons. Specifically, paired data sets generated from the operation of the surgical instrument 7012 may include applying a binary classification, such as, for example, a bleeding or non-bleeding event. More generally, the binary classification may be characterized as either a desired event (e.g., a successful surgical procedure) or an undesired event (e.g., a misfired or misused surgical instrument 7012). The aggregated self-describing data may represent individual data received from various groups or subgroups of the surgical hub 7006. Thus, the data collection and aggregation module 7022 may generate aggregated metadata or other organized data based on the raw data received from the surgical hub 7006. To this end, the processor 7008 may be operatively coupled to the hub application 7014 and the aggregated medical data database 7011 to execute the data analysis module 7034. The data collection and aggregation module 7022 may store the aggregated, organized data in the aggregated medical data database 2212.

[0208] The resource optimization module 7020 can be configured to analyze this aggregated data to determine optimal use of resources for a particular medical facility or group of medical facilities. For example, the resource optimization module 7020 may determine optimal ordering points for surgical staplers 7012 for a group of medical facilities based on corresponding projected demand for such instruments 7012. The resource optimization module 7020 could also evaluate resource usage or other operational configurations of various medical facilities to determine whether resource usage can be improved. Similarly, the recommendation module 7030 can be configured to analyze the organized data aggregated from the data collection and aggregation module 7022 to provide recommendations. For example, the recommendation module 7030 may be able to recommend to a medical facility (e.g., a medical service provider such as a hospital) that a particular surgical instrument 7012 should be upgraded to an improved version based, for example, on a higher than expected error rate. Additionally, the recommendation module 7030 and / or resource optimization module 7020 may be able to suggest better supply chain parameters such as product reorder points, provide suggestions for different surgical instruments 7012, their use, or procedural steps to improve surgical outcomes, etc. The medical facility may receive such suggestions via the corresponding surgical hub 7006. More specific suggestions regarding parameters or configurations of various surgical instruments 7012 may also be provided. The hub 7006 and / or surgical instruments 7012 may each have a display screen that displays the data or suggestions provided by the cloud 7004.

[0209] The patient outcome analysis module 7028 may analyze surgical outcomes associated with the currently used operating parameters of the surgical instrument 7012. The patient outcome analysis module 7028 may also analyze and evaluate other potential operating parameters. In this connection, the suggestion module 7030 may be able to make suggestions using these other potential operating parameters based on resulting in a better surgical outcome, such as a better seal or less bleeding. For example, the suggestion module 7030 may be able to send suggestions to the surgical 7006 regarding when to use a particular cartridge with a corresponding stapling surgical instrument 7012. Thus, the cloud-based analysis system may be configured to analyze large collections of raw data and provide focused suggestions (advantageously determined based on the aggregated data) across multiple medical facilities while controlling for common variables. For example, the cloud-based analysis system may be able to analyze, evaluate, and / or aggregate geographic similarities between medical providers using similar types of instruments, types of patients, number of patients, medical providers / facilities using similar types of instruments, etc. The control program update module 7026 may be configured to implement various surgical instrument 7012 suggestions when the corresponding control program is updated. For example, the patient outcome analysis module 7028 may be able to identify correlations linking certain control parameters with successful (or unsuccessful) outcomes. Such correlations may be addressed when an updated control program is transmitted to the surgical instrument 7012 via the control program update module 7026. Updates to the instrument 7012 transmitted via the corresponding hub 7006 may incorporate aggregated performance data collected and analyzed by the data collection and aggregation module 7022 of the cloud 7004. Additionally, the patient outcome analysis module 7028 and suggestions module 7030 may be able to identify improved ways to use the instrument 7012 based on the aggregated performance data.

[0210] The cloud-based analysis system may include security features implemented by the cloud 7004. These security features may be managed by the authorization and security module 7024. Each surgical hub 7006 may have associated unique credentials, such as a username, password, and other suitable security credentials. These credentials may be stored in memory 7010 and may be associated with an authorized cloud access level. For example, based on providing accurate credentials, the surgical hub 7006 may be granted access to communicate with the cloud to a predefined extent (e.g., send or receive certain defined types of information). To this end, the aggregated medical data database 7011 of the cloud 7004 may include a database of credentials to verify the accuracy of the provided credentials. Different credentials may be associated with various levels of permission for interaction with the cloud 7004, such as a predefined access level for receiving data analysis generated by the cloud 7004. Additionally, for security purposes, the cloud may maintain a database of hubs 7006, instruments 7012, and other devices, which may include a "blacklist" of prohibited devices. In particular, surgical hubs 7006 listed on the blacklist may not be permitted to interact with the cloud, while surgical instruments 7012 listed on the blacklist may not have functional access to the corresponding hub 7006 and / or may be prevented from fully functioning when paired with the corresponding hub 7006. Additionally or alternatively, the cloud 7004 may flag instruments 7012 based on incompatibility or other specified criteria. In this manner, counterfeit medical devices and inappropriate reuse of such devices across the cloud-based analysis system may be identified and addressed.

[0211] The surgical instrument 7012 may use a wireless transceiver to transmit a wireless signal that may represent, for example, authorization credentials for access to the corresponding hub 7006 and cloud 7004. A wired transceiver may also be used to transmit the signal. Such authorization credentials may be stored in a memory device of each of the surgical instruments 7012. The authorization and security module 7024 may determine whether the authorization credentials are accurate or counterfeit. The authorization and security module 7024 may also dynamically generate authorization credentials for enhanced security. The credentials may also be encrypted, such as by using hash-based encryption. Upon transmitting the appropriate authorization, the surgical instrument 7012 may transmit a signal to the corresponding hub 7006 and ultimately the cloud 7004 to indicate that the instrument 7012 is ready to acquire and transmit medical data. In response, the cloud 7004 may transition to a state capable of receiving medical data for storage in an aggregated medical data database. This data transmission readiness may also be indicated by, for example, a light indicator on the instrument 7012. The cloud 7004 may also send signals to the surgical instruments 7012 to update their associated control programs. The cloud 7004 may send signals directed to a particular class of surgical instruments 7012 (e.g., electrosurgical instruments) so that software updates to the control programs are sent only to the appropriate surgical instruments 7012. Additionally, the cloud 7004 may be used to implement system-wide solutions to address local or global issues based on selective data transmission and authorization credentials. For example, if a group of surgical instruments 7012 are identified as having a common manufacturing defect, the cloud 7004 may change the authorization credentials corresponding to this group to implement an operational lockout of this group.

[0212] The cloud-based analytics system may enable monitoring of multiple healthcare facilities (e.g., healthcare facilities such as hospitals) to determine improved practices and suggested changes (e.g., via the suggestions module 2030). Thus, the processor 7008 of the cloud 7004 may analyze data associated with an individual healthcare facility to identify the facility and aggregate that data with other data associated with other healthcare facilities. Groups may be defined, for example, based on similar operational actions or geographic locations. In this manner, the cloud 7004 may provide broader analysis and suggestions for groups of healthcare facilities. The cloud-based analytics system may also be used for enhanced situational awareness. For example, the processor 7008 may predictively model the effect of suggestions on costs and effectiveness for a particular facility (for overall operations and / or various medical procedures). The costs and effectiveness associated with that particular facility may also be compared to the corresponding local area of ​​other facilities or any other comparable facilities.

[0213] The data classification and prioritization module 7032 may prioritize and classify data based on criticality (e.g., severity, surprise, suspiciousness of the medical event associated with the data). This classification and prioritization may be used in conjunction with other data analysis module 7034 functions described above to improve the cloud-based analysis and operations described herein. For example, the data classification and prioritization module 7032 may assign priorities to the data analysis performed by the data collection and aggregation module 7022 and the patient outcome analysis module 7028. Different priority levels may result in a specific response from the cloud 7004 (corresponding to the level of urgency), such as elevation for rapid response, special handling, exclusion from the aggregated medical data database 7011, or other suitable response. Additionally, if necessary, the cloud 7004 may send a request (e.g., push message) via the hub application server for additional data from the corresponding surgical instrument 7012. The push message may result in a notification being displayed on the corresponding hub 7006 to request support or additional data. This push message may be required in situations where the cloud detects significant irregularities or outliers and the cloud is unable to determine the cause of the irregularity. The central server 7013 may be programmed to trigger this push message in certain critical situations, such as, for example, when data is determined to differ from expected values ​​by more than a predetermined threshold, or if security is deemed to be involved.

[0214] Further exemplary details regarding the various described functions are provided in the following description. Each of the various functions may utilize a cloud architecture, as illustrated in Figures 22 and 23 as one example of a hardware and software implementation.

[0215] Healthcare facility utilization, resource, and efficiency modeling Aspects of the present disclosure are presented for a cloud-based analytics system communicatively coupled to a plurality of hubs and smart medical instruments and configured to provide customized suggestions to localized medical care facilities regarding the use of medical supplies and other resources to improve efficiency and optimize resource allocation. A medical care facility, such as a hospital or medical clinic, may develop a set of practices for the treatment, use, and disposal of various medical supplies that often stem from routines and traditions maintained over time. The behavioral patterns of medical facilities are typically risk-averse and will generally hesitate to adopt new and better practices until better practices are demonstrated. Similarly, even if a better use or efficiency model is developed at a nearby facility, it may be difficult for the local facility to adopt the improved practice because 1) the respective facility may be inherently more resistant to external changes and 2) there is often unknown as to how or why the improved practice will work at the nearby facility instead of the practice performed at the local facility. Furthermore, even healthcare facilities that desire to improve their practices may not be able to do so optimally because they lack sufficient knowledge from other similarly situated facilities in the area, either of similar size and / or with similar practices or patients, etc.

[0216] To help facilitate the dissemination of improved practices across multiple healthcare facilities, it would be desirable if a common source had contextual knowledge from multiple healthcare facilities and could determine what changes should be made for any particular healthcare facility based on knowledge of the practices of any or all of the multiple facilities.

[0217] In some aspects, a cloud-based system communicatively coupled to a knowledge center within a medical facility, such as one or more medical hubs, may be configured to aggregate medical resource usage data from multiple medical facilities. The cloud-based system may then correlate the medical resource usage data with outcomes from those facilities and may be able to derive various patterns within the data. For example, in some aspects, the cloud-based system may find which hospitals generate the least amount of waste per unit cost based on an aggregation of all waste and procurement data obtained from medical facilities in a wide geographic area (e.g., all surgery centers in Japan). The cloud-based system may be configured to identify which medical facilities generated the least amount of waste per unit cost and then analyze how to differentiate between the medical facilities. If a trend is found, the cloud-based system may distribute this information to all similarly situated medical facilities to improve their practices. This analysis may help improve inventory management, throughput efficiency, or overall efficiency of the medical facility. Improved inventory management may help surgical equipment and other medical resources to be utilized at their peak performance levels for longer periods of time than would be the case if the resources were improperly managed, and thus medical equipment may continue to be used even as they become older and more worn out.

[0218] In general, a cloud-based system may be configured to aggregate data from multiple healthcare facilities that a single facility alone would not be able to accomplish on its own. Additionally, a cloud-based system may be configured to analyze large collections of data and control for common variables, such as practice type, patient type, patient volume, geographic similarities, which facilities use similar types of equipment, etc., that a single facility alone would not be able to analyze on its own.

[0219] In this way, the cloud-based system of the present disclosure may be able to find more accurate causal relationships that result in best practices at a particular facility, which can then be distributed to all of the other facilities. Additionally, the cloud-based system may be able to provide data from all of the disparate sources that a single facility cannot do on its own.

[0220] 24, an exemplary diagram of a summary of various resources correlating to a particular type of surgical classification is shown. There are two bars for each category, with dashed bars 7102, 7106, and 7110 representing unused and / or scrap resources, and solid bars 7104, 7108, and 7112 showing the total resources in use for that category. In this example, bars 7104, 7108, and 7112 show the total amounts of endocutter cartridges, sponges, saline, fibrin sealant, sutures, and stapler buttresses for thoracic, colorectal, and bariatric procedures, respectively, compared to smaller amounts 7102, 7106, and 7110, which represent the amount of unused resources for thoracic, colorectal, and bariatric procedures, respectively.

[0221] The cloud system may be configured to identify waste products that have been collected and unused or collected and used in a manner that is not beneficial to the patient or procedure. To do this, the cloud system may record in memory all records of inventory receipts and disposals. During each receipt, inventory may be scanned and entered, and the barcode of each inventory item may identify, as an example, what type of product it is. In some aspects, smart waste receptacles may be utilized to automatically tally products as they are being discarded. The smart waste receptacles may ultimately be connected to the cloud system, either through one or more surgical hubs or through a separate facility-wide inventory management system. Each facility may be tracked by its location, for example, through set GPS coordinates, entered addresses, etc. This data may be compiled in memory using one or more databases, along with metadata associated with that data, such as date and time of use, location, type of procedure used if applicable, place of origin, cost per item, expiration date if applicable, etc.

[0222] In addition, the cloud system may be configured to identify misfired or misused products and trace where the products were used, and archive these results. For example, each surgical instrument communicatively coupled to the surgical hub may transmit a record of when the instrument was fired, such as firing a staple or applying ultrasonic energy. Each record may be transmitted through the instrument and ultimately recorded in the cloud system. The action by the instrument may be tied to a result, either at the time or an overall result indicating whether the procedure was successful or not. The action may be associated with a precise timestamp that places the action at a precise point during the procedure, and all actions of the procedure are also automatically recorded in the cloud, including the start and end time of the procedure. This allows all human medical care workers to focus on their duties during the procedure rather than worrying about the actual instance when the medical instrument actions occurred. The medical instrument records may be used to identify which products may be wasted during the procedure, and the cloud system may also be configured to identify usage trends in this way.

[0223] In some aspects, the cloud system may be configured to perform trend analysis of products tied to the overall length or volume of the product to identify short-fire or wasted products. For example, the cloud system may time-stamp the use of the product within a known period of time when a surgical procedure is occurring. The cloud system may then record the amount of resources utilized during the procedure and compare the materials used in the procedure to similarly situated procedures performed elsewhere. From this, several conclusions may be reached by the cloud system. For example, the cloud system may provide combination suggestions that provide smaller portions or alternative uses that result in less wasted product. As another example, the cloud system may provide dedicated kit suggestions or specific protocol changes that assemble the product in a manner that is adjusted by the detected amount of use of the institution. As yet another example, the cloud system may provide alternative product combination suggestions or protocol changes that are adjusted by the detected amount of use, and thus should result in less wasted product. As yet another example, based on identifying correlations or patterns in which intra-operative actions occurring within a particular time interval relative to a previous action tend to result in a wasteful action, the cloud system may provide suggestions on how to adjust intra-operative medical procedures, typically based on the timing of actions occurring before or after an event that results in a waste of resources, such as a misfire or multiple fires. These analyses may be derived in part, taking into account misfires, the inherent behavior of the surgeon, or the facility in general, etc., using algorithms that attempt to optimize available resources at the rate of their waste.

[0224] With further reference to FIG. 24, based on the aggregation of used and unused products, the cloud system can also generate several other conclusions. For example, the cloud system may be configured to generate a correlation between unused products and overhead costs. The cloud system may also generate a calculation of expired products and how it affects the rate of change with inventory. It may also generate an indication of where in the supply chain the product is unused and to what extent. It may also generate ways to reduce costs or inventory space by finding substitutes for other resources for the same procedure. This may be based on comparing similar practices in different medical facilities that use different resources to perform the same procedure.

[0225] In some aspects, the cloud system may be configured to analyze inventory usage of any and all medical products and provide procurement management when acquiring new products. The cloud system may optimize inventory space utilization in light of utilization rates of certain products compared to others to determine how to best utilize available space. Inventory may often not be closely monitored with respect to how long products are stored. If certain products are utilized at a lower rate, but there is a large amount of product, it may be determined that storage space allocation is insufficient. Thus, the cloud system may better allocate storage space to reflect actual resource usage.

[0226] To improve this area, in some aspects, the cloud system may identify missing or insufficient products in an operating room (OR), for example, for a particular procedure. The cloud system may then provide an alert or notification or send data to indicate the deficiency in the surgical hub in that OR. As another example, when a product is used in the OR, its usage information, such as sensor activation or activation identification, may be communicated to the cloud. Products may be registered with a scan or power switch. Analysis of this information for a given hospital combined with ordering information may ultimately inform supply status and enable ordering suggestions. This may occur automatically once the cloud system registers that the product is being used in the OR or via other means.

[0227] In some aspects, equipment usage within a procedure is monitored by the cloud system and compared for a given segment (e.g., individual surgeons, individual hospitals, hospital networks, regions, etc.) against equipment usage for similar procedures in other segments. Suggestions are presented to optimize usage and provide such resources based on unit resources used or consumption. In general, the cloud system may focus on comparing product usage between different institutions to which it is connected.

[0228] FIG. 25 provides an exemplary illustration of how data is analyzed by the cloud system to provide a comparison between multiple facilities to compare resource usage. In general, the cloud system 7200 may obtain usage data from all facilities, such as any of the types of data described with respect to FIG. 24, and may associate each data with various other metadata, such as time, procedure, outcome of procedure, cost, date of acquisition, etc. FIG. 25 illustrates an exemplary collection of data 7202 being uploaded to the cloud 7200, and each circle in the set 7202 representing an outcome and one or more resources and contextual metadata that may be associated with leading to the outcome. In addition, high performance outcomes 7204 and their associated resource and contextual metadata are also uploaded to the cloud 7200, although at the time of uploading, it may be unknown which data have a very good outcome or simply an average (or below average) outcome. The cloud system may identify which usage of resources is associated with a better outcome compared to the average outcome or expected outcome. As some examples, this may be based on determining whether the resource will last longer, be wasted less, and ultimately cost less per unit time or per unit resource. The cloud system may analyze the data to determine the best outcome based on any and all of these variables, or even a combination of one or more of them. Identified trends may then be used to find correlations or prompt requests for additional data associated with these data points. If patterns are found, these suggestions may be alerted to the user to consider as possible ways to improve resource usage and efficiency.

[0229] The exemplary graph 7206 provides a visual representation of an exemplary trend or pattern that the cloud may derive from reviewing the resource data and outcome data, according to some aspects. In this example, the cloud system may analyze the resource and outcome data for stapler firings and their relationship to performance in surgery. The cloud system may collect data from multiple medical facilities and multiple surgeons within each facility based on firing data automatically recorded during each surgery, which is generated directly from the operation of the surgical stapler itself. Performance results may be based on post-operative examination and evaluation, and / or immediate results during surgery, such as whether there are bleeding events or successful wound closure. Based on all of the data, trends may be determined, where it may be discovered that there is a small window of firings that results in the best performance results in interval "a," as shown. The degree of this performance compared to the most common firings is shown as interval "b." The firings that result in the best outcomes may not be what is commonly practiced, so it may not have been easy to discover these outcomes without the aggregation and analysis capabilities of the cloud system.

[0230] As another example, cartridge type, color, and adjunct usage may be monitored for sleeve gastrectomy procedures for individual surgeons within the same hospital. The data may reveal that the average procedure cost for one surgeon is higher than that of other surgeons within the same hospital, yet short-term patient outcomes remain the same. Hospitals are then notified and encouraged to consider differences in equipment utilization, techniques, etc., for potential cost optimization through the elimination of adjuncts.

[0231] In some aspects, the cloud system may also identify special situations. For example, specific cost information provided within a hospital may be identified, including hours, equipment utilization, and staff. These aspects may be specific to a particular OR or facility. For these special situations, the cloud system may be configured to suggest efficiencies in OR usage times (scheduling) across specialties (orthopedic, thoracic, colorectal, bariatric, etc.), equipment inventory, etc.

[0232] In some aspects, the cloud system may also be configured to compare the cost-effectiveness of robotic surgery versus traditional methods, such as laparoscopy, for a given procedure type. The cloud system may compare equipment costs, OR time, patient discharge time, and effectiveness of procedures performed by surgeons alone versus procedures performed robotically.

[0233] Individualized Change In accordance with some aspects of the cloud system, the disclosure above focused on determining and optimizing efficiency (i.e., value), and now this section is based on concentrating on identifying which local practices may best be distributed to other similarly situated medical facilities.

[0234] A medical care facility, such as a hospital or medical clinic, may develop a set of practices for how to utilize medical devices to assist in medical procedures that often stem from routines and traditions maintained over time. The behavioral patterns of medical facilities are typically risk-averse and will generally hesitate to adopt new and better practices until better practices are demonstrated. Similarly, even if better practices for utilizing devices or coordinating procedures are developed in nearby facilities, it may be difficult for the local facility to adopt the improved practices because 1) the respective facilities may be inherently more resistant to change from the outside, and 2) it is often unknown how or why the improved practices would work in the nearby facilities instead of the practices performed in the local facility. Furthermore, even medical facilities that wish to improve their practices may not be able to do so optimally because they lack sufficient knowledge from other similarly situated facilities in the area, either according to similar size and / or with similar practices or patients, etc.

[0235] To help facilitate the dissemination of improved practices across multiple healthcare facilities, it would be desirable if a common source had contextual knowledge from multiple healthcare facilities and could determine what changes should be made for any particular healthcare facility based on knowledge of the practices of any or all of the multiple facilities.

[0236] In some aspects, a cloud-based system communicatively coupled to a knowledge center within a medical facility, such as one or more medical hubs, may be configured to aggregate resource utilization data and patient outcomes from multiple medical facilities. The cloud-based system may then correlate the resource utilization data with outcomes from those facilities and may be able to derive various patterns within the data. For example, in some aspects, the cloud-based system may find which hospitals produce better outcomes for a particular type of procedure based on the aggregation of all patient outcome data for that particular procedure collected across a broad geographic area (e.g., all surgery centers in Germany). The cloud-based system may be configured to identify which medical facilities produced better procedure outcomes compared to the average across the geographic area and then analyze what differences were identified. The cloud-based system may disseminate this information to all of the similarly located medical facilities to improve their practices.

[0237] In general, a cloud-based system may be configured to aggregate data from multiple healthcare facilities that a single facility alone would not be able to accomplish on its own. Additionally, a cloud-based system may be configured to analyze large collections of data and control for common variables, such as practice type, patient type, patient volume, geographic similarities, which facilities use similar types of equipment, etc., that a single facility alone would not be able to analyze on its own.

[0238] In this way, the cloud-based system of the present disclosure may be able to find more accurate causal relationships that result in best practices at a particular facility, which can then be distributed to all of the other facilities. Additionally, the cloud-based system may be able to provide data from all of the disparate sources that a single facility cannot do on its own.

[0239] The cloud system may be configured to generate conclusions about the effectiveness of any local facility in many ways. For example, the cloud system may determine if the local treatment facility is using a different product combination or usage than the larger community and its outcomes. The cloud system may then correlate the differences and highlight them for use with other facilities, other surgical hubs, or clinical product sales, as some examples. In general, this information may be distributed broadly such that no single facility may have access or knowledge, including the facility implementing this improvement action.

[0240] As another example, the cloud system may determine if the local facility is performing as well or worse than the outcomes to the larger community. The cloud system may then correlate the suggestions and return that information as a recommendation to the local facility. The system may display data showing its performance against others and may also display suggestions on what the facility is doing compared to what the rest of the world is doing. Again, the local facility may not know that it has inefficiencies in that regard, nor may anyone else realize that it is utilizing their resources more efficiently, so without the cloud system having a bigger picture of all the data, no one would ever know to examine these issues.

[0241] These suggestions can be provided in a variety of forms. For example, the cloud system may provide suggestions at the purchase level suggesting cost improvements for similar outcomes. As another example, the cloud system may provide suggestions at the OR level when procedures are planned and equipment is being prepared, when less desirable products are being pulled, suggesting other techniques and product combinations that would be consistent with the broader community achieving higher outcomes. As yet another example, the cloud system may display outcome comparisons need to take into account the surgeon's experience, perhaps via counting similar cases performed by that surgeon from the cloud data. In some aspects, individual learning curves may be reported against a larger aggregated data set as improved outcomes upon obtaining a steady state outcome level, or the expectation of the surgeon's performance relative to peers.

[0242] FIG. 26 illustrates an example of how a cloud system 7300 may determine efficacy trends from aggregated data collection 7302 across all regions, according to some aspects. Here, for each circle of data collection 7302, equipment utilization for procedures, costs, and outcomes of procedures are monitored and compared for a given segment (e.g., individual surgeons, individual hospitals, hospital networks, regions, etc.) against equipment utilization, costs, and outcomes of procedures for similar procedures in other segments. These data may possess metadata linking it to a particular facility. In general, the outcome of a procedure may be linked to multiple types of data associated with the procedure, such as resources used, who performed the procedure, where the procedure was performed, etc. The data linked to the outcome may then be presented as a data pair. The data may be subdivided in various ways, such as between good and poor outcomes, filtered by a particular facility, by a particular demographic, etc. The region filter 7304 is visually illustrated as an example. The data set 7302 includes both good and poor outcomes, with the poor outcomes being blackened for contrast.

[0243] FIG. 26 also shows an example of a chart where these distinctions are made, which may be derived from the aggregated data set 7302 using one or more data pairs. Chart 7306 shows a global analysis in one embodiment, while a regionally segmented analysis is provided in another chart 7308. Statistical analysis may be performed to determine whether the outcomes are statistically significant. In chart 7306, the cloud system may determine that no statistical difference was found between good and poor outcomes based on incidence. In contrast, in chart 7308, the cloud system may determine that when filtering a particular region, there is a statistically higher occurrence of poor outcomes for a given region. According to some embodiments, suggestions are presented to share outcomes vs. cost vs. device utilization and all combinations therein to help inform optimization of outcomes vs. procedure costs with device utilization potentially being the primary driver of variance.

[0244] As another example, cartridge types and colors are monitored for lobectomy procedures for individual surgeons within the same hospital. The data reveals that the average cost for one surgeon is higher than average for this surgeon, but the average length of stay is less. Hospitals are notified by the cloud system and encouraged to consider differences in equipment utilization, techniques, etc., in search of improved patient outcomes.

[0245] In some aspects, the cloud system may also be configured to provide predictive modeling of variations to treatments, product combinations, and timing for a given localized population, or for the general population as a whole. Predictive modeling may be used to assess the impact on resource utilization, resource efficiency, and resource performance, as some examples.

[0246] FIG. 27 provides an exemplary illustration of several types of analyses, according to some embodiments, that the cloud system may be configured to perform to provide predictive modeling. The cloud system may combine cloud knowledge of the steps required and the instruments to perform the procedure, and may compare different means through various numerical indicators such as resources utilized, time, procedure cost, etc. In this example of chart 7400, a thoracic lobectomy is analyzed using two different types of methods to perform the same procedure. Option A describes a disposable ultrasonic instrument as the method to perform the procedure, while option B shows a combination of different methods to perform the same procedure in the aggregate. The graph may be useful for a surgeon or administrator to know how resources are utilized and their costs. Option B is divided into several sections, including sterilization costs, reusable dissectors, and additional time to perform the procedure. The cloud system may be configured to convert these somewhat abstract concepts into quantitative cost values ​​based on cloud knowledge of time spent in the OR, staff salaries, and resource costs per unit time in the OR, as well as resources utilized for sterilization and reusable dissectors and their associated costs. The cloud system may be configured to associate any amount of resources and costs with the cloud's knowledge of the steps required to perform a thoracic lobectomy using the predetermined method in option B.

[0247] As another example, chart 7404 in FIG. 27 shows a comparison between performing various portions of a procedure using an ultrasonic long dissector and a monopolar reusable dissector. Chart 7404 shows the comparison in terms of the time required to perform each portion of the procedure for each instrument. The surgeon may then be able to select which instrument may be desired for a particular procedure. Breakout times may be automatically recorded during the procedure being performed empirically, using the time for each portion of the overall procedure due to the cloud system's knowledge of the expected sequence for performing the procedure. The boundaries between each portion may be set by the surgeon providing input to manually indicate when each change occurs. In other cases, the cloud system may utilize situational awareness to determine when a portion of the procedure is finished based on how the device is and is not used. The cloud system may aggregate the number of these procedures performed across multiple surgeons and multiple facilities, and then calculate the average time for each section, as an example.

[0248] As another example, chart 7402 of FIG. 27 illustrates an exemplary graphical interface for comparing the relative costs of utilizing an ultrasonic long dissector or a monopolar reusable dissector, according to some embodiments. The value of each instrument per unit time is displayed for a particular procedure. As some examples, the data used to generate these values ​​may be similar to the data obtained in charts 7400 and 7404. The graphic display may allow for a concise explanation of key points of efficiency that would be most useful in making a decision. This analysis may help the surgeon ascertain how valuable each instrument is for a given procedure.

[0249] In general, to perform predictive modeling, the cloud system may combine the cloud system's knowledge of the exact steps to perform a procedure, which instruments may be used to perform each step, and the cloud system's aggregated data on how each instrument performs each particular step. A surgeon may not have to have such a combination of knowledge to provide such an assessment alone. Thus, predictive modeling may be the result of continuous monitoring and acquisition of data across multiple facilities, something like predictive modeling would not be possible without the cloud system.

[0250] In some embodiments, the cloud system may also derive abstraction information from multiple sources (e.g., hub data collection sources, literature, etc.) to identify optimal treatment techniques. Various other examples of how predictive modeling may be utilized include: (1) Sigmoid resection: multi-quadrant surgery, best sequence of operations, etc. (2) RYGB: Ideal limb length based on this patient's situation, etc. (3) Lobectomy: the number and method of lymph nodes to be removed; (4) VSG: bougie size and distance from the pylorus are included.

[0251] In some aspects, once a suggestion is made to the surgeon, the surgeon is given the option to reject or continue with such future recommendations. Additionally, through an interface with the hub, the surgeon may query the cloud system for additional information to inform his or her decision. For example, the surgeon may wish to isolate the situation to a more localized set of data, such as a particular facility, or a particular demographic that better suits the patient undergoing surgery. Data may change, for example, if the patient is a child or if the patient is female.

[0252] Modification of device setup (pre-op) based on surgeon, region, hospital, or patient parameters Similar to the section above, the cloud-based system may also be configured to monitor smart instrument configurations, or more generally, configurations utilizing multiple smart instruments, such as an operating room being prepared for surgery. For similar reasons as discussed above, such as to improve clinical effectiveness and efficiency, it may be useful to compare procedure setups at any particular medical facility and aggregate data related to procedure setups at multiple other medical facilities.

[0253] The cloud-based system of the present disclosure may be configured to aggregate data related to smart medical instrument configurations and operating rooms (ORs) utilizing a plurality of smart medical instruments. The smart medical instruments may include manual instruments communicatively coupled to a medical data tower and configured to generate sensor data, and robotic instruments to perform procedures in a more automated fashion. The cloud-based system may be configured to detect irregularities in the OR setup related to which instruments are present in the room and / or which materials are being used to generate product combinations for medical procedures. The irregularities may be based on comparing materials and instruments present in the OR with other setups from other medical facilities for similar situations. The cloud system may then generate firmware, software, or other configuration changes and transmit those changes to the surgical instruments as the equivalent of a device update.

[0254] In this way, the cloud-based system of the present disclosure may be able to identify errors and find more precise causal relationships that result in best practices at a particular facility, which can then be distributed to all other facilities. Additionally, the cloud-based system may be able to provide data from all of the disparate sources that a single facility cannot do on its own. This can result in safer and more efficient operating room procedures and medical practice in general.

[0255] In some aspects, the cloud system may be configured to provide appliance configuration suggestions and generate appropriate appliance setting changes to customize a pre-specified user's performance.

[0256] For example, the cloud system may focus on a surgical device user or surgeon based on a comparison of the device's current usage with the historical trends of a larger data set. As some examples, the cloud system may provide suggestions on what type of cartridge to use based on what the user has previously used for a particular procedure or what a particular surgeon typically wants. The cloud system may have access to data based on the particular surgeon, the type of procedure, and the type of instrument used to make this determination.

[0257] As another example, the cloud system may provide suggestions based on identified anatomical structures shown on the cartridge display. As another example, the cloud system may provide suggestions by referencing baseline surgical device clamp and firing rates based on local prior usage data stored in its memory.

[0258] As yet another example, the cloud system may perform a comparison of the tissue interaction of the current device against the historical average for the same step in the same procedure for the same surgeon or for a segment of surgeons in the database. The cloud system may have access to all steps used to perform the surgery and may have access to a catalog of all data when performing a particular step in a particular procedure across all surgeons who have ever performed that procedure in its network. Suggestions may also come from an analysis of how the current surgical device has been observed to interact with tissue historically. This type of analysis may be useful because it is often not possible to collect a large amount of actual patient data on how exactly a surgical device interacts with tissue. Furthermore, surgeons typically only know their own experience and have no knowledge of what other surgeons have experienced for the same procedure. The cloud, on the other hand, can collect all of this data and provide new insights that any individual surgeon alone would not know.

[0259] As another example, in stapling, two or more of the following are known: cartridge color, stapler type, procedure, procedure step, patient information, clamp force over time, pre-fire information, end effector deformation, etc. This information is compared against a historical average of similar data sets. The current situation is compared against this average and the user is informed of the nature of the current fire.

[0260] FIG. 28 provides a graph of an example type of analysis, according to some embodiments, that the cloud system may execute to provide these suggestions. In this example, chart 7500 shows data for a parenchymal staple firing analysis. In bar graph 7502, the various types of staples used, with each color of the staple reflecting a different amount of force applied to the surgical site. The y-axis (left side) associated with bar graph 7502 reflects the percentage usage of that type of stapler color, with each color showing a bar graph of three different categories: regional average usage (Japan in this case), overall average usage with best outcomes, and local facility average usage. Based on this data, the cloud system may be configured to develop a recommendation of which staples to change for a given situation. A series of suggested actions are shown in chart 7506 as a result. Chart 7500 also shows a set of line graphs 7504 reflecting the percentage of lingering air leaks (right y-axis) for each color used, as well as for each type of category (region, global average, facility average). If the staple is too thick and does not match the tissue thickness level, there may be holes in the staple that result in undesirable air leakage. Here, the cloud system may provide suggestions based on all of the represented and non-represented data, according to some embodiments. The cloud system may simply provide the suggestions in the form of text as a label, and the surgeon may verify whether the data supports such trials and decisions to accept the cloud system's suggestions.

[0261] As another example, the cloud system may be configured to provide ultrasonic blade length or capacity suggestions based on the likelihood of encountering vascular structures in a procedure. Similar to that described above with reference to FIG. 28, the cloud system may collect relevant data regarding blade lengths and their outcomes obtained from multiple surgical hubs and may show various outcomes for using different blade lengths in a particular procedure. Suggestions may be provided in a graphical display where the surgeon can verify the suggestions using the graphical display by the cloud system.

[0262] In some aspects, the cloud system is also configured to provide suggestions to staff regarding devices to assist with the next procedure. These suggestions may be based on a combination of surgeon selection tendencies (pick lists) versus historical device utilization for the same procedure performed by several segments of a larger database, as well as average suggestions or utilization across different facilities that produce the best results. Data may be obtained by pairing successful outcomes with metadata, such as which devices were used to achieve those successful outcomes. Suggestions may be influenced by other factors, including patient information, demographic data, etc.

[0263] Relatedly, in some aspects, the cloud system may also provide identification of withdrawn instruments that may not be the preferred device for a given procedure. Blacklisting sorting can more specifically eliminate any obviously flawed uses of the device to help the surgeon make the best decision. This data may come from manufacturer input, analysis of poor outcomes, specific input provided to the cloud system, etc.

[0264] Additionally, based on querying the database for tissue characteristics (elasticity, impedance, perfusion rate), a particular device with a given set of parameters (clamp preload) may be suggested by the cloud system to be used from the current inventory in the inventory. Some of the metadata associated with past procedure outcomes may include a description of the type of tissue operated on and an associated description of the physical characteristics of that tissue. The cloud system may then draw trends or patterns based on different types of procedures, but generally have all procedures addressing similar types of tissue. This type of analysis may be used as a secondary suggestion when a new or unknown procedure needs to be performed and new suggestions are welcome. If the suggestion is accepted, the cloud system may be configured to generate the changes in the parameters and send the parameters to the interconnected medical devices via the surgical hub to make them readily available for use in the coordinated procedure.

[0265] In some aspects, the device setup suggestions may include suggestions of adjuncts for the device based on data collected locally during pre-operative imaging or at the beginning of the procedure. That is, the adjunct suggestions may be for use on or with the device based on local correlation of use to device effectiveness. As an example, based on a given procedure, surgeon, and patient information, the bleeding in that case needs to be tightly controlled, and therefore the cloud system may conclude that buttressing is recommended for all staple firings.

[0266] In some aspects, the cloud system may also be configured to provide awareness of any newly launched products that are available and suitable for operation, as well as instructions for use (IFUs). Data may be collected from one or more surgical hubs or from direct factory input for newly launched products. The cloud system can download information and make it displayable to multiple medical hubs across multiple facilities.

[0267] In some aspects, with respect to any of the above examples for suggestions being provided by the cloud system, the cloud system may also provide an alert or other signal when a device or suggested setup is followed or ignored. The cloud system may be configured to access procedure data from the surgical hub, for example, during a surgical procedure. The surgical hub may collect data regarding what types of devices are being used during the procedure. The cloud system may monitor the progress of the procedure by verifying whether approved methods or devices are being used in the correct or predetermined order for the procedure. As an example, if there is a deviation where a particular device is not expected or a step is missing, the cloud system may send an alert to the surgical hub that the particular device is not being used properly. This would occur in real time as the timing of the procedure is critical to patient safety.

[0268] Medical facilities with segmented individualized equipment functions In some aspects, the cloud-based system may also be configured to provide suggestions or automatically adjust surgical instrument settings to account for specific differences in a medical facility. While there are many similarities that can be normalized across multiple facilities, there may also be specific differences that should be considered. For example, patient demographic differences, patient physiological differences that are inherent to local populations, procedural differences such as each individual surgeon's preference preferences, and area-specific instrument availability or other differences may cause specific adjustments to be made at any particular medical facility.

[0269] The cloud-based system of the present disclosure may be configured to aggregate data regarding smart medical instrument configurations and data related to operating room (OR) setups utilizing multiple smart medical instruments, as well as data highlighting specific differences that may be unique to the area or that particular medical facility. The cloud-based system may then factor adjustments to device settings or suggestions for treatment changes based on these differences. For example, the cloud-based system may first provide baseline suggestions for how smart instruments should be used based on best practices found in the aggregated data. The cloud-based system may then augment the suggestions to account for one or more unique differences specific to the medical facility. Examples of these differences are provided above. The cloud-based system may recognize which demographic and patient data produced the optimal baseline treatment and then compare the local facility's demographic and patient data against that data. The cloud-based system may identify or estimate correlations with that baseline setting to develop adjustments or offsets that account for differences in demographic and patient data.

[0270] In this manner, the cloud-based system of the present disclosure may be able to make optimal adjustments specific to each medical facility, or even specific to each operating room or surgeon. The adjustments may provide improved performance that takes into account observed best practices, as well as any inherent variations.

[0271] In some embodiments, the cloud system may be configured to provide changes in instrument usage variability to improve outcomes. For example, the cloud system may determine localized undesirable effects resulting from a particular technique utilizing a surgical device. FIG. 29 provides an explanation of how the cloud system may perform analysis to identify statistical correlations to local issues tied to how the device is used in a localized setting. The cloud 7600 may aggregate usage data for all types of devices and record their outcomes. The data set may be filtered to only those outcomes utilizing the particular device in question. The cloud system may then perform statistical analysis to determine if there are trends in how procedures are performed at a particular facility when utilizing that device. Patterns may emerge that suggest consistent deficiencies in how the device is used at that facility, represented as data points 7602 showing statistical correlations. Additional data may then be examined to see if a second pattern may occur in comparison to how others are using the device in the aggregate. Once patterns are identified and local outliers 7604 are addressed, suggestions may be provided. In other cases, the cloud system may provide facility-specific updates to the device to offset local practices of how the device is used.

[0272] In some forms, the cloud system may be configured to communicate deviations to a particular user, or may be configured to make suggestions for different techniques or uses to improve results from a particular device. The cloud system may send data for display to the surgical hub to indicate what changes should be made.

[0273] As an example, a stapler configured with a means to sense the force required to clamp the device transmits data indicating that the clamping force is still changing rapidly (viscoelastic creep) when the surgeon begins firing the staples, resulting in more bleeding than expected from the staple line. The cloud system and / or device can communicate the need to wait longer (e.g., 15 seconds) before firing the device to improve outcomes. This may be based on performing the statistical analysis described in FIG. 29 using data points from similar procedures aggregated from multiple surgeons and multiple facilities. At the time of surgery, it would be impossible or impractical for anyone on the surgical team to reach these conclusions without the assistance of a cloud system aggregating such knowledge and reaching such conclusions.

[0274] In some aspects, the cloud system may also be configured for purposeful deployment of control algorithms to devices that have usage criteria that meet certain criteria. For regional differences, the cloud system may adjust the control algorithms of various surgical devices. Different amounts of force may be applied to devices for patients of different demographics, for example. As another example, surgeons may have different uses for certain types of surgical devices, and the control algorithms can be adjusted to account for this. The cloud system may be configured to send wide area updates to devices, targeting regions and specific instrument IDs that allow targeted updates to their control programs.

[0275] In some aspects, the cloud system may provide encoding of sales units and / or serial numbers of individual devices, allowing updated control programs to be pushed to specific devices or groups of devices based on meeting certain criteria or thresholds.

[0276] Additionally, according to some aspects, the cloud system may be configured to perform analysis of perioperative data against outcome data for correlations that identify exceptional results (positive and negative). Analysis may be performed at multiple levels (e.g., individual, hospital, and geographic (e.g., city, county, state, country, etc.) filters). Furthermore, regional validation of improved outcomes may only target limited geographic areas since changes are known to occur only within the limited area. The ability to tune the device to regional selection trends, techniques, and surgical selection trends may allow for nuanced improvements to region-specific areas.

[0277] In addition to directly modifying appliance settings, the cloud system may also be configured to provide suggestions regarding suggestions of different appliances or equivalent devices due to local availability, i.e., equivalent suggestions for devices to perform a particular function may be suggested by the cloud system when an appliance is lacking and a particular region has an excess or general availability of different appliances that may be used to serve an equivalent purpose.

[0278] For example, the cloud system may determine that a PPH hemorrhoid stapling device or curved cutter 30 device is only available in Italy due to teachings of a unique procedure configuration or hospital procedure design. As another example, the cloud system may determine that there is an Asia-specific use of TX and vascular open staplers due to teachings of cost sensitivity, lack of laparoscopic adoption, and hospital preferred techniques and patient chest cavity sizes. As another example, the cloud system may provide an awareness message to OR staff of sub-standard knock-off products available in a particular region. This data may come from the ingestion of information from multiple sources, such as input provided by experts and physicians, and may use machine learning and natural language processing to interpret trends and news relevant to the local area. FIG. 30 provides an illustration of one example of how some devices may meet comparable use compared to the intended device. Here, a circular stapling device 7702 is compared to a compression ring 7704 for use with a PPH stapler 7700 for a hemorrhoidopexy procedure. The type of analysis performed to arrive at a recommendation by the cloud system may be similar to that described in FIG. 29. The cloud system may provide a representation of this suggestion, as well as an analysis of its efficiency and resource utilization, for example, a representation 7706 that may be shown on a display in the surgical hub. In this case, the cost of instruments is compared, as well as the time and effectiveness of each type of instrument. The cloud system may derive these suggestions by obtaining usage examples from different facilities and by observing how other facilities and physicians handle the same procedures.

[0279] In some aspects, the cloud system may also be configured to provide surgical hub decision trees and local suggestions for post-operative care based on data processed during the procedure and cloud analysis trends of device outcomes or performance aggregated from larger population sets.

[0280] In some aspects, the cloud system may provide an updatable decision tree for post-operative care suggestions based on device measurement status usage. Post-operative care decisions may initially be derived from previously known responses that a physician would normally suggest. As additional data becomes available, the decisions can be updated by the cloud system, for example, by aggregating types of post-operative care from other facilities or analyzing new types of care from the literature or from research on new surgical devices. The decision tree may be viewable in graphical form in the surgical hub.

[0281] When using this decision tree, feedback can be provided for each node to indicate how effective the current solution is. Data can be entered based on what feedback the patient is likely to provide. The doctor or data manager does not need to do any analysis at that point, but the cloud system can aggregate all the data and observe what trends may emerge. Feedback can then be provided to update the decision tree.

[0282] In some aspects, the cloud system may incorporate operational data and device performance to suggest post-operative monitoring and actions. For example, various patient measurements may change which decisions should be taken in post-operative care. These measurements may include, but are not limited to, (a) blood pressure, (b) low hematocrit, (c) PTT (partial thromboplastin time), (d) INR (international normalized ratio), (e) oxygen saturation, (f) changes in ventilation, and (g) x-ray data.

[0283] As another example, anesthesia protocols may influence which post-operative decisions should be taken, which may consider (a) any fluids administered, (b) anesthesia time, and (3) medications, as some non-limiting examples.

[0284] As another example, the type of medication may also play a role. Administration of warfarin is one prominent example. A patient has, for example, abnormal PTT and INR post-op. Because the patient is receiving warfarin, potential treatments may include delivery of vitamin K, factor 7, or plasma (fpp). Plavix could be another example. A patient has abnormal PTT and INR post-op. Because the patient is receiving Plavix, potential treatment of warfarin would not be effective. Alternatively, delivering platelets may be a suggestion in the decision tree.

[0285] As a fourth example, post-operative instructions may be provided that depend on the type of procedure. Some non-limiting examples include (a) colorectal time (motility) versus solid foods, and (b) time to physical activity and PT. These various decisions may be reflected in a decision tree, and all of the branching decision types may be stored in the cloud system and updated as additional data is obtained from any connected facilities.

[0286] FIG. 31 provides various examples of how some data may be used as variables in determining how a post-operative decision tree may branch. As shown, some factors 7802 may include parameters used in a surgical device, such as the firing force (FTF) used in the procedure, or the closing force (FTC) used in the surgical device. Graph 7800 shows a visual depiction of how the FTC and FTF curves may correlate with each other. Other factors include compression speed, latency, and staple compatibility. Based on some of these variables, the type of post-operative care needs to be adjusted. In this case, a multi-factor analysis is applied, which may be too complex to calculate or modify without the assistance of the processing power of a system such as a cloud system. This example suggests that the decision tree 7804 provided by the cloud system may be larger than a simple two-dimensional decision tree. To consider multiple variables to make a single decision, the decision tree generated by the cloud may be visually available, perhaps only in parts, and the final conclusion may need to be displayed without a complete display of all the other branches that were not considered. Chart 7806 may be an example that provides additional information of how to respond within the decision tree.

[0287] Situational Awareness Situational awareness is the ability of some aspects of a surgical system to determine or infer information relevant to a surgical procedure from data received from a database and / or an instrument. The information may include the type of procedure being performed, the type of tissue being operated on, or the body cavity that is the subject of the procedure. Contextual information related to a surgical procedure may enable a surgical system to, for example, improve the manner in which it controls modular devices (e.g., robotic arms and / or robotic surgical tools) connected thereto and provide contextual information or suggestions to the surgeon during the course of a surgical procedure. Situational awareness may be applied, for example, to perform and / or improve any of the functions described in Figures 22-31.

[0288] 32, there is shown a timeline 5200 illustrating the situational awareness of a hub, such as the surgical hub 106 or 206. The timeline 5200 illustrates an exemplary surgical procedure and the contextual information that the surgical hub 106, 206 can derive from data received from data sources at each step of the surgical procedure. The timeline 5200 illustrates typical steps that may be taken by nurses, surgeons, and other medical personnel during the course of a lung segmentectomy surgery, beginning with setting up the operating room and ending with transporting the patient to a post-operative recovery room.

[0289] The situation-aware surgical hub 106, 206 receives data from data sources throughout the course of a surgical procedure, including data generated each time medical personnel use a modular device paired with the surgical hub 106, 206. The surgical hub 106, 206 receives this data from the paired modular devices and other data sources to continually derive inferences (i.e., contextual information) regarding the ongoing procedure as new data is received, such as which step of the procedure is being performed at any given time. The situational awareness system of the surgical hub 106, 206 can, for example, record data regarding the procedure to generate a report, verify steps being taken by medical personnel, provide data or prompts (e.g., via a display screen) that may be relevant to a particular procedure step, adjust the modular device based on the context (e.g., activate a monitor, adjust the field of view (FOV) of a medical imaging device, or change the energy level of an ultrasonic surgical instrument or RF electrosurgical instrument), and any other such actions described above.

[0290] As a first step 5202 in this exemplary procedure, hospital personnel retrieve the patient's EMR from the hospital's EMR database. Based on selected patient data in the EMR, the surgical hub 106, 206 determines that the procedure to be performed is a thoracic procedure.

[0291] In a second step 5204, personnel scan the incoming medical supplies for the procedure. The surgical hub 106, 206 cross-references the scanned supplies with a list of supplies utilized in various types of procedures to verify that the mix of supplies is compatible with the thoracic procedure. Additionally, the surgical hub 106, 206 may also determine that the procedure is not a wedge procedure (either because the incoming supplies do not include certain supplies required for a thoracic wedge procedure or are not otherwise compatible with a thoracic wedge procedure).

[0292] In a third step 5206, medical personnel scan the patient's band via a scanner communicatively connected to the surgical hub 106, 206. The surgical hub 106, 206 can then verify the patient's identity based on the scanned data.

[0293] In a fourth step 5208, the medical staff turns on the auxiliary devices. The auxiliary devices utilized may vary according to the type of surgical procedure and the technology used by the surgeon, but in this exemplary case, they include smoke evacuators, aspirators, and medical imaging devices. Once activated, the auxiliary device, which is a modular device, may automatically pair with the surgical hub 106, 206 located within a certain proximity of the modular device as part of its initialization process. The surgical hub 106, 206 may then derive contextual information regarding the surgical procedure by detecting the type of modular device that is paired with it during this pre-operative or initialization phase. In this particular example, the surgical hub 106, 206 determines that the surgical procedure is a VATS procedure based on this particular combination of paired modular devices. Based on a combination of data from the patient's EMR, a list of medical supplies used in the procedure, and the type of modular devices that connect to the hub, the surgical hub 106, 206 may roughly deduce the particular procedure that the surgical team will be performing. Once the surgical hub 106, 206 knows what particular procedure is being performed, the surgical hub 106, 206 can then retrieve the steps of that procedure from memory or from the cloud and then cross-reference data subsequently received from connected data sources (e.g., modular devices and patient monitoring devices) to estimate which steps of the surgical procedure the surgical team is performing.

[0294] In a fifth step 5210, personnel attach EKG electrodes and other patient monitoring devices to the patient. The EKG electrodes and other patient monitoring devices may be paired with the surgical hub 106, 206. Once the surgical hub 106, 206 begins receiving data from the patient monitoring devices, the surgical hub 106, 206 confirms that the patient is in the operating room.

[0295] In a sixth step 5212, medical personnel induce anesthesia in the patient. The surgical hub 106, 206 can estimate that the patient is under anesthesia based on data from the modular devices and / or patient monitoring devices, including, for example, EKG data, blood pressure data, ventilator data, or a combination thereof. Once the sixth step 5212 is completed, the pre-operative portion of the lung segmentectomy is complete and the operative portion begins.

[0296] In a seventh step 5214, the patient's lung being operated on is collapsed (while ventilation is switched to the contralateral lung). The surgical hub 106, 206 can, for example, infer that the patient's lung has been collapsed from ventilator data. Because the surgical hub 106, 206 can compare the detection of the patient's lung being collapsed to the expected steps of the procedure (which may be accessed or retrieved in advance), it can infer that the surgical portion of the procedure has begun, thereby determining that collapsing the lung is the first surgical step in this particular procedure.

[0297] In an eighth step 5216, a medical imaging device (e.g., a scope) is inserted and video feed from the medical imaging device is initiated. The surgical hub 106, 206 receives the medical imaging device data (i.e., video or image data) through a connection to the medical imaging device. Upon receiving the medical imaging device data, the surgical hub 106, 206 may determine that the laparoscopic portion of the surgical procedure has begun. Additionally, the surgical hub 106, 206 may determine that the particular procedure being performed is a segmentectomy as opposed to a lobectomy (note that the wedge procedure has already been discounted by the surgical hub 106, 206 based on the data received in the second step 5204 of the procedure). Data from the medical imaging device 124 (FIG. 2) may be used to determine contextual information regarding the type of procedure being performed among many different methods, including by determining the angle at which the medical imaging device is oriented with respect to visualization of the patient's anatomy, by monitoring the number or medical imaging devices being used (i.e., activated and paired with the surgical hub 106, 206), and by monitoring the type of visualization device being used. For example, one technique for performing a VATS lobectomy places the camera above the diaphragm in the anterior inferior corner of the patient's thoracic cavity, while one technique for performing a VATS segmentectomy places the camera in an anterior intercostal position relative to the segmental fissure. For example, using pattern recognition or machine learning techniques, a situational awareness system may be trained to recognize the location of the medical imaging device based on visualization of the patient's anatomy. As another example, one technique for performing a VATS lobectomy utilizes a single medical imaging device, while another technique for performing a VATS segmentectomy utilizes multiple cameras. As yet another example, one technique for performing a VATS segmentectomy uses an infrared light source (which may be communicatively coupled to the surgical hub as part of the visualization system) to visualize the segmental fissure, which is not used in a VATS lobectomy. By tracking any or all of this data from the medical imaging device, the surgical hub 106, 206 can determine the particular type of surgical procedure being performed and / or the technique being used for the particular type of surgical procedure.

[0298] At a ninth step 5218, the surgical team begins the dissection step of the procedure. Because the surgical hub 106, 206 receives data from the RF or ultrasonic generator indicating that an energy instrument is being fired, it can infer that the surgeon is in the process of dissecting and separating the patient's lungs. The surgical hub 106, 206 can cross-reference the received data with the retrieved steps of the surgical procedure to determine that the energy instrument being fired at this point in the process (i.e., after the steps of the procedure described above have been completed) corresponds to the dissection step. In a particular example, the energy instrument can be an energy tool attached to a robotic arm of a robotic surgical system.

[0299] At a tenth step 5220, the surgical team proceeds to the ligation step of the procedure. Because the surgical hub 106, 206 receives data from the surgical stapling and severing instrument indicating that the instrument is being fired, the surgical hub 106, 206 can infer that the surgeon is ligating the artery and vein. As with the previous step, the surgical hub 106, 206 can derive this inference by cross-referencing the receipt of data from the surgical stapling and severing instrument with the step in the retrieved process. In a particular example, the surgical instrument may be a surgical tool attached to a robotic arm of a robotic surgical system.

[0300] In an eleventh step 5222, the segmental resection portion of the procedure is performed. The surgical hub 106, 206 can infer that the surgeon is transecting parenchymal tissue based on data from the surgical stapling and cutting instrument, including data from its cartridge. The cartridge data can correspond to, for example, the size or type of staples fired by the instrument. Because different types of staples are utilized on different types of tissue, the cartridge data can indicate the type of tissue being stapled and / or transected. In this case, the type of staples fired is utilized on parenchymal tissue (or other similar tissue type), which allows the surgical hub 106, 206 to infer that the segmental resection portion of the procedure is being performed.

[0301] Then, at a twelfth step 5224, a node dissection step is performed. The surgical hub 106, 206 may infer that the surgical team is dissecting the node and performing a leak test based on data received from the generator indicating that an RF or ultrasonic instrument is being fired. For this particular procedure, the RF or ultrasonic instrument used after the parenchymal tissue is transected corresponds to the node dissection step, which allows the surgical hub 106, 206 to make this inference. It is noted that the surgeon will periodically alternate between a surgical stapling / cutting instrument and a surgical energy (i.e., RF or ultrasonic) instrument depending on the particular step during the procedure, as different instruments are better suited for certain tasks. Thus, the particular sequence in which the stapling / cutting instrument and the surgical energy instrument are used may indicate which step of the procedure the surgeon is performing. Additionally, in certain examples, a robotic tool may be used for one or more steps during the surgical procedure, and / or a handheld surgical instrument may be used for one or more steps during the surgical procedure. The surgeon(s) can, for example, alternate between the robotic tool and the handheld surgical instrument and / or can use the devices simultaneously, for example. Once the twelfth step 5224 is completed, the incision is closed and the post-operative portion of the procedure begins.

[0302] In a thirteenth step 5226, the patient's anesthesia is reversed. The surgical hub 106, 206 may estimate that the patient is emerging from anesthesia based on, for example, ventilator data (i.e., the patient's breathing rate begins to increase).

[0303] Finally, the fourteenth step 5228 is for the medical personnel to remove the various patient monitoring devices from the patient. Thus, the surgical hub 106, 206 can presume that the patient is being transferred to a recovery room when the hub loses EKG, BP, and other data from the patient monitoring devices. As can be seen from this exemplary procedure description, based on data received from various data sources communicatively coupled to the surgical hub 106, 206, the surgical hub 106, 206 can determine or presume when each step of a given surgical procedure is occurring.

[0304] Situational awareness is further described in U.S. Provisional Patent Application No. 62 / 611,341, entitled "INTERACTIVE SURGICAL PLATFORM," filed December 28, 2017, which is incorporated by reference in its entirety. In certain examples, the operation of a robotic surgical system, including, for example, the various robotic surgical systems disclosed herein, may be controlled by the hub 106, 206 based on its situational awareness and / or feedback from its components and / or based on information from the cloud 102.

[0305] Various aspects of the subject matter described herein are illustrated in the following numbered examples.

[0306] Example 1. A cloud-based analytical medical system, comprising: at least one processor; at least one memory communicatively coupled to the at least one processor; an input / output interface configured to access data from a plurality of medical hub communication devices, each communicatively coupled to at least one surgical instrument; and a database resident in the at least one memory and configured to store data, wherein the at least one memory aggregates patient outcome data from the plurality of medical hubs, the patient outcome data including data regarding steps performed in a patient procedure and corresponding timing of each step, data regarding outcomes of each patient procedure performed, and data regarding the outcomes of each patient procedure used in the patient procedure. aggregating the medical resource acquisition data from a plurality of medical hubs; determining a correlation between the positive outcomes from the patient outcome data and the resource acquisition data; generating medical suggestions for modifying medical resource acquisition practices based on the correlation; and displaying the medical suggestions to a plurality of medical hubs located in different medical facilities.

[0307] Example 2. The cloud-based analytical medical system of Example 1, wherein at least one memory stores instructions executable by at least one processor to evaluate patient outcome data and resource acquisition data of a particular medical facility, determine that the particular medical facility has a below average level of performance compared to other medical facilities based on a comparison of the evaluated patient outcome data and resource acquisition data of the particular medical facility to the aggregated patient outcome data, and generate targeted suggestions for modifying practices at the particular medical facility.

[0308] Example 3. The cloud-based analytical medical system of any one of Examples 1-2, wherein the targeted suggestions include instructions to reassess the medical procedure to take into account the experience level of the surgeon.

[0309] Example 4. The cloud-based analytical medical system of any one of Examples 1 to 3, wherein the localized suggestion includes an instruction to review resource inventory management to reduce inventory of the first product and increase inventory of the second product.

[0310] Example 5. The cloud-based analytical medical system of any one of Examples 1 to 4, wherein at least one memory stores instructions executable by at least one processor to: evaluate patient outcome data and resource acquisition data of medical facilities belonging to a geographic region; determine that a level of performance of the medical facilities in the geographic region is below average compared to a global average of medical facilities based on a comparison of the evaluated patient outcome data and resource acquisition data of the medical facilities in the geographic region with the aggregated patient outcome data; and generate regionalized suggestions for modifying practices at the medical facilities belonging to the geographic region.

[0311] Example 6. The cloud-based analytical medical system of any one of Examples 1 to 5, wherein the at least one memory stores instructions executable by at least one processor to perform a trend analysis indicating expected changes in demographics of a population, and based on the trend analysis, generate predictive modeling suggestions indicating instructions to modify medical procedures or inventory of one or more medical products over a period of time to address the expected changes in the demographics.

[0312] Example 7. The cloud-based analytical medical system of any one of Examples 1 to 6, wherein the at least one memory stores instructions executable by at least one processor to compare performance metrics of a first method for performing a medical procedure with performance metrics of a second method for performing the same medical procedure, and generate, based on the performance comparison, a predictive modeling suggestion indicating instructions for executing the first method for performing the medical procedure.

[0313] Example 8. A non-transitory computer-readable medium storing computer-readable instructions executable by at least one processor of a cloud-based analysis system, the computer-readable instructions being executable by at least one processor of the cloud-based analysis system to: aggregate patient outcome data from a plurality of medical hubs, the patient outcome data including data regarding steps performed in a patient treatment and corresponding timing of each step, data regarding an outcome of each patient treatment performed, data regarding medical resources used in the patient treatment, and, for each data item related to the medical resources, location data describing the medical facility to which the medical resource was assigned, and, for each data item related to the outcome of the patient treatment, data regarding an indication of whether the outcome is successful or unsuccessful; aggregate medical resource acquisition data from the plurality of medical hubs; determine a correlation between positive outcomes from the patient outcome data and the resource acquisition data; generate medical suggestions for modifying medical resource acquisition practices based on the correlation; and display the medical suggestions to a plurality of medical hubs located in different medical facilities.

[0314] Example 9. The non-transitory computer-readable medium of Example 8, wherein the instructions are further executable to: evaluate patient outcome data and resource acquisition data of the particular medical facility; determine that the particular medical facility has a below average level of performance compared to other medical facilities based on a comparison of the evaluated patient outcome data and resource acquisition data of the particular medical facility to the aggregated patient outcome data; and generate limited suggestions for modifying practices at the particular medical facility.

[0315] Example 10. The non-transitory computer readable medium of any one of Examples 8-9, wherein the localized suggestions include instructions to review the medical procedure to take into account the surgeon's experience level.

[0316] Example 11. A non-transitory computer-readable medium according to any one of Examples 8 to 10, wherein the localized proposal includes instructions for reviewing resource inventory management to reduce inventory of a first product and increase inventory of a second product.

[0317] Example 12. A non-transitory computer-readable medium according to any one of Examples 8 to 11, wherein the instructions are further executable to: evaluate patient outcome data and resource acquisition data of medical facilities belonging to the geographic region; determine that the level of performance of medical facilities in the geographic region is below average compared to a global average of medical facilities based on a comparison of the evaluated patient outcome data and resource acquisition data of the medical facilities in the geographic region with the aggregated patient outcome data; and generate regionalized suggestions for modifying practices at medical facilities belonging to the geographic region.

[0318] Example 13. The non-transitory computer-readable medium of any one of Examples 8 to 12, wherein the instructions are further configured to perform a trend analysis indicating expected changes in demographics of a population, and based on the trend analysis, generate predictive modeling suggestions indicating instructions to modify medical procedures or inventory of one or more medical products over a period of time to address the expected changes in the demographics.

[0319] Example 14. The non-transitory computer-readable medium of any one of Examples 8 to 13, wherein the instructions are further configured to: compare performance metrics of a first method for performing a medical procedure with performance metrics of a second method for performing the same medical procedure; and generate, based on the performance comparison, a predictive modeling suggestion indicative of instructions for performing the first method for performing the medical procedure.

[0320] Example 15. A cloud-based analytical medical system, comprising: at least one processor; at least one memory communicatively coupled to the at least one processor; an input / output interface configured to access data from a plurality of medical hub communication devices, each communicatively coupled to at least one surgical instrument; and a database resident in the at least one memory and configured to store data, wherein the at least one memory aggregates medical instrument data from the plurality of medical hubs, the medical instrument data including data relating to physical and performance parameters of the medical instruments, and for each data relating to the medical instruments, usage data relating to medical procedures utilizing the medical instruments, and usage data relating to each medical procedure. determining a correlation between the outcomes of the medical procedures and a status of a state of the medical devices utilized in each medical procedure; accessing live medical procedure data for the current medical procedure, the live medical procedure data including a description of the medical devices in the operating room where the current medical procedure is being performed; determining irregularities in the description of the medical devices in the current medical procedure based on the determined correlation between the outcomes and the medical devices utilized; and providing an alert to a medical communication hub utilized in the operating room of the current medical procedure.

[0321] Example 16. The cloud-based analytical medical system of Example 15, wherein the medical devices in the operating room include manual medical instruments and robotic medical instruments.

[0322] Example 17. A cloud-based analytical medical system as described in any one of Examples 15 to 16, wherein at least one processor is further configured to generate firmware or software changes to a medical device in an ongoing medical procedure in conjunction with the provided alert.

[0323] Example 18. A cloud-based analytical medical system as described in any one of Examples 15 to 17, wherein the irregularity includes use of medical resources of a medical device in a current medical procedure that is inconsistent with aggregated medical instrument data regarding the medical procedure.

[0324] Example 19. A cloud-based analytical medical system as described in any one of Examples 15 to 18, wherein the alert includes an instruction to change the firing or clamping speed of a medical device in a current medical procedure.

[0325] Example 20. A cloud-based analytical medical system described in any one of Examples 15 to 19, wherein the alert includes an instruction to change the length of an ultrasonic blade of a medical device in a current medical procedure.

[0326] While several embodiments have been illustrated and described, it is not the applicant's intention to restrict or limit the appended claims to such details. Numerous modifications, variations, changes, substitutions, combinations, and equivalents of these embodiments can be implemented and will occur to those skilled in the art without departing from the scope of the present disclosure. Moreover, the structure of each element associated with the described embodiments can alternatively be described as a means for providing the function performed by the element. Also, although materials are disclosed with respect to specific components, other materials may be used. It is therefore to be understood that the above description and the appended claims are intended to cover all such modifications, combinations, and variations as falling within the scope of the disclosed embodiments. The appended claims are intended to cover all such modifications, variations, changes, substitutions, modifications, and equivalents.

[0327] The above detailed description has described various aspects of the apparatus and / or process using block diagrams, flow charts, and / or examples. To the extent that such block diagrams, flow charts, and / or examples include one or more functions and / or operations, it should be understood by one of ordinary skill in the art that each function and / or operation included in such block diagrams, flow charts, and / or examples can be individually and / or collectively implemented by a variety of hardware, software, firmware, or virtually any combination thereof. It should be understood by one of ordinary skill in the art that all or a portion of some aspects of the embodiments disclosed herein can be equivalently implemented on an integrated circuit as one or more computer programs running on one or more computers (e.g., as one or more programs running on one or more computer systems), as one or more programs running on one or more processors (e.g., as one or more programs running on one or more microprocessors), as firmware, or virtually any combination thereof, and that designing circuitry and / or writing software and / or firmware code is within the skill of one of ordinary skill in the art in view of the present disclosure. Moreover, those skilled in the art will appreciate that the subject matter described herein may be distributed as one or more program products in a variety of forms, and that a particular form of the subject matter described herein may be used regardless of the particular type of signal-bearing medium used to actually effect the distribution.

[0328] The instructions used to program the logic to perform the various disclosed aspects may be stored in a system memory such as dynamic random access memory (DRAM), cache, flash memory, or other storage. Additionally, the instructions may be distributed over a network or by other computer readable media. Thus, a machine readable medium may include any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computer), including, but not limited to, a floppy diskette, an optical disk, a compact disk, a read only memory (CD-ROM), as well as a magneto-optical disk, a read only memory (ROM), a random access memory (RAM), an erasable programmable read only memory (EPROM), an electrically erasable programmable read only memory (EEPROM), a magnetic or optical card, a flash memory, or a tangible machine readable storage used to transmit information over the Internet via an electrical, optical, acoustical, or other form of propagated signal (e.g., carrier wave, infrared signal, digital signal, etc.). Accordingly, non-transitory computer-readable media includes any type of tangible machine-readable medium suitable for storing or transmitting electronic instructions or information in a form readable by a machine (eg, a computer).

[0329] The term "control circuitry" as used in any aspect of the present specification can refer to, for example, hardwired circuitry, programmable circuitry (e.g., a computer processor including one or more individual instruction processing cores, a processing unit, a processor, a microcontroller, a microcontroller unit, a controller, a digital signal processor (DSP), a programmable logic device (PLD), a programmable logic array (PLA), or a field programmable gate array (FPGA)), a state machine circuit, firmware that stores instructions execut...

Claims

1. 1. A cloud-based analytical medical system, comprising: At least one processor; at least one memory communicatively coupled to the at least one processor; an input / output interface configured to access data from a plurality of medical hub communication devices, each communicatively coupled to at least one surgical instrument; a database resident in the at least one memory and configured to store the data; The at least one memory includes: aggregating medical instrument data from the plurality of medical hubs, the medical instrument data comprising: Data regarding physical and performance parameters of the medical device; For each data item relating to the medical device, usage data relating to a medical procedure utilizing the medical device; For each medical procedure, an outcome of the medical procedure associated with the medical device; and a status of the medical device during the medical procedure; and determining a correlation between outcomes of the medical procedures and a status of a condition of the medical device utilized in each of the medical procedures, the status of the condition of the medical device being associated with a predetermined desired or undesired outcome of the medical procedure; accessing live medical procedure data relating to a current medical procedure, the live medical procedure data including a current state status of the medical equipment in an operating room performing the current medical procedure; determining an irregularity in the current state status of the medical device in the current medical procedure based on the determined correlation between the outcome and the medical device utilized, determining whether the current state status is associated with the undesirable event; and if the irregularity is determined to exist, providing an alert to a medical communication hub utilized in the operating room of the current medical procedure.

2. The cloud-based analytical medical system of claim 1 , wherein the medical devices in the operating room include manual medical instruments and robotic medical instruments.

3. 2. The cloud-based analytical medical system of claim 1, wherein the at least one processor is further configured to generate firmware or software changes to the medical device in the current medical procedure in coordination with the provided alert.

4. The cloud-based analytical medical system of claim 1 , wherein the irregularity comprises a usage of medical resources of the medical device in the current medical procedure that is inconsistent with the aggregated medical instrument data for the medical procedure.

5. The cloud-based analytical medical system of claim 1 , wherein the alert comprises an instruction to change a firing or clamping rate of the medical device in the current medical procedure.

6. The cloud-based analytical medical system of claim 1 , wherein the alert includes an instruction to change a length of an ultrasonic blade of the medical device in the current medical procedure.

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