161 results about "Surgery procedure" patented technology

A robotic surgical system includes a surgeon consol coupled to a patient console and coupled to one or more surgical instruments. The surgeon consol is used by a surgeon to perform a surgical procedure. A surgeon computer is coupled to or at the surgeon console. The surgeon consol is coupled to the one or more surgical instruments. A surgical robot is coupled to a robotic surgery control system and a feedback loop. The robotic surgery control system includes or is coupled to an artificial intelligence (AI) system. The feedback loop receives data from one or more sensors at the robotic surgical system. The data is analyzed by the robotic surgery control system, and in response operation of the robotic surgical system is adjusted as needed. The surgical control system or the AI system uses intraoperative data describing a surgical procedure being performed. The feedback loop receives data from one or more sensors of the robotic surgical system regarding performance of at least a portion of the robotic surgical system. The data is analyzed by the robotic surgical control system. In response to analysis, operation of the robotic surgical system is adjusted as needed. The robotic surgical control system or AI system extracts one or more programmed steps used by the surgeon for positioning at least one of the surgical instruments during the surgical procedure.

A robotic surgical system. a surgeon console operatively coupled to a patient console and one or more surgical instruments. A surgeon computer is coupled to or integrated with the surgeon console, the surgeon computer further operatively connected to the one or more surgical instruments; A surgical robot is coupled to a robotic surgery control system and a feedback loop. The robotic surgery control system includes or is coupled to an artificial intelligence (AI) system. A feedback loop is further configured to receive performance-related data from the one or more sensors, the data analyzed by the robotic surgery control system or the AI system to dynamically adjust the robotic system's operation as needed. A data extraction module retrieves, from the robotic surgery control system or the AI system. one or more programmed steps executed by the surgeon for positioning at least one of the surgical instruments during the surgical procedure.

A robotic surgical system includes one or more robotic actuators configured to interact with biological tissue during a surgical procedure. A plurality of sensors include at least one of fiber Bragg grating sensors, piezoelectric strain sensors, or magnetostrictive sensors to capture real-time mechanical, elasticity, or deformation data from biological tissues. deep learning engine trained on a dataset comprising tissue mechanical responses across multiple tissue types, pathological states, and patient demographics. Pre-contact predictive adjustment profiles are generated for anticipated tissue interactions using preoperative imaging data registered to intraoperative coordinates. Intraoperative deviations are detected from predicted mechanical behavior and autonomously recalibrate actuator forces. Upcoming surgical maneuvers are anticipated based on prior task sequences and adjust actuator stiffness or damping properties in preparation for anticipated contact. An emergency override of actuator forces is provided via an anomaly detection module when real-time sensor data deviates beyond a threshold from the predicted safe mechanical response range. A feedback loop iteratively refines the deep learning engine during the procedure using supervised learning updates, anomaly detection, and reinforcement learning strategies. The reinforcement learning model is optionally shared across procedures to optimize distributed actuator force patterns for minimizing localized and cumulative tissue stress.

Systems and methods for designing and implementing patient-specific surgical procedures and / or medical devices are disclosed. In some embodiments, a method includes receiving a patient data set of a patient. The patient data set is compared to a plurality of reference patient data sets, wherein each of the plurality of reference patient data sets is associated with a corresponding reference patient. A subset of the plurality of reference patient data sets is selected based, at least partly, on similarity to the patient data set and treatment outcome of the corresponding reference patient. Based on the selected subset, at least one surgical procedure or medical device design for treating the patient is generated.

A robotic surgical system. a surgeon console operatively coupled to a patient console and one or more surgical instruments. A surgeon computer is coupled to or integrated with the surgeon console, the surgeon computer further operatively connected to the one or more surgical instruments; A surgical robot is coupled to a robotic surgery control system and a feedback loop. The robotic surgery control system includes or is coupled to an artificial intelligence (AI) system. A feedback loop is further configured to receive performance-related data from the one or more sensors, the data analyzed by the robotic surgery control system or the AI system to dynamically adjust the robotic system's operation as needed. A data extraction module retrieves, from the robotic surgery control system or the AI system. one or more programmed steps executed by the surgeon for positioning at least one of the surgical instruments during the surgical procedure.

A surgical system comprising a surgical instrument and a surgical hub is disclosed. The surgical instrument is configured to perform a surgical procedure and comprises a housing, a shaft assembly, an end effector, and a sensor configured to sense a parameter associated with a function of the surgical instrument. The surgical hub comprises a processor and a memory. The memory stores instructions executable by the processor to receive data from the sensor, wherein the data comprises the parameter associated with the function of the surgical instrument; infer a step of the surgical procedure being performed by the surgical instrument, based on the data from the sensor; receive data from a database, wherein the data from the database is associated with the step of the surgical procedure; compare a value of the parameter to the data received from the database; and control the surgical instrument based on the comparison.

An augmented reality (AR) display system for a surgical environment includes a wearable AR display device, a scope, and processing circuitry. The wearable AR display device is configured to be worn by a surgeon and provide AR imagery to the surgeon. The scope is configured to be inserted into a patient. The processing circuitry is configured to obtain real-time image data from the scope, X-ray image data of the patient, and navigation data for a surgical procedure of the patient. The processing circuitry is also configured to generate an AR environment that includes the real-time image data, the X-ray image data, and the navigation data. The processing circuitry is also configured to operate the wearable AR display device to provide the AR environment including the real-time image data, the X-ray data, and the navigation data as the AR imagery.

A surgical robot is coupled to the surgeon console. The surgical robot performs a robotic surgical procedure. The surgical robot includes one or more robotic surgical arms. A control system is coupled to the one or more robotic surgical arms. An artificial intelligence (“AI”) system includes a plurality of machine learning algorithms. The robotic surgical arms are at least partially controlled by the AI system and the control device to process intraoperative data including images captured by cameras and sensor inputs. The machine learning algorithms analyze the intraoperative data in real time, comparing it with stored images and procedural information in image recognition and procedure databases. The one or more machine algorithms enable at least partial identification of anatomical structures. In response to detection of the anatomical structures the AI system at least partially adjusts movement of the robotic surgical arms to avoid critical anatomical structures while performing the robotic surgery procedure to ensure precise targeting at the surgical site while minimizing damage to surrounding tissue at a surgical site. The AI system provides a surgeon with improved dexterity when the surgeon uses the robotic surgical arms at the surgical site, the improved dexterity resulting from at least partially analyzing the intraoperative data in real time by the one or more machine learning algorithms, enabling precise and adaptive manipulation of the robotic surgical arms at the surgical site.

A method of teaching a surgical procedure includes transmitting a first video, from a first location to a second location remote from the first location, of a surgeon in an operating room performing the surgical procedure on a patient with at least one surgical instrument. The method also includes transmitting a second video, from the first location to the second location, of the surgical instrument during the surgical procedure, annotating the second video with at least one annotation, and transmitting, from the first location to the second location, the at least one annotation overlaid on the second video.

Methods of generating a surgical operative note for a surgical procedure, such as a spinal surgical procedure, and associated systems and devices are disclosed herein. In some embodiments, a representative method includes capturing surgical procedure data of the surgical procedure with a sensor array positioned to view the surgical procedure, and identifying features in the surgical procedure data relevant to the surgical procedure. The method can further comprise processing the identified features to provide contextual information about the surgical procedure, and utilizing an artificial intelligence (AI) application to generate the operative note based on the identified features and the contextual information. The operative note can include a natural language, structured, and coherent description of the surgical procedure that summarizes the surgical procedure, including the type of surgery performed, specific surgical techniques used, intraoperative findings, and / or postoperative care instructions.

A surgical simulator for surgical training is provided. The simulator includes a frame defining an enclosure and a simulated tissue model located inside the frame. The simulated tissue model is adapted for practicing a number of surgical procedures including but not limited to transanal excisions and transvaginal hysterectomies. Portions of the frame comprises a material adhesively compatible with the material of portions of the simulated tissue model to secure and suspend the simulated tissue model within the frame. The simulated tissue model may also include simulated vasculature configured to loop through apertures in the frame to secure and suspend the simulated tissue model within the frame.

Systems and methods for providing assistance to a surgeon during an implant surgery are disclosed. A method includes defining areas of interest in diagnostic data of a patient and defining a screw bone type based on the surgeon's input. Post defining the areas of interest, salient points are determined for the areas of interest. Successively, an XZ angle, an XY angle, and a position entry point for a screw are determined based on the salient points of the areas of interest. Successively, a maximum screw diameter and a length of the screw are determined based on the salient points. Thereafter, the screw is identified and suggested to the surgeon for usage during the implant surgery.

A surgical robot is coupled to the surgeon console. The surgical robot performs a robotic surgical procedure. The surgical robot includes one or more robotic surgical arms. A control system is coupled to the one or more robotic surgical arms. An artificial intelligence (“AI”) system includes a plurality of machine learning algorithms. The robotic surgical arms are at least partially controlled by the AI system and the control device to process intraoperative data including images captured by cameras and sensor inputs. The machine learning algorithms analyze the intraoperative data in real time, comparing it with stored images and procedural information in image recognition and procedure databases. The one or more machine algorithms enable at least partial identification of anatomical structures. In response to detection of the anatomical structures the AI system at least partially adjusts movement of the robotic surgical arms to avoid critical anatomical structures while performing the robotic surgery procedure to ensure precise targeting at the surgical site while minimizing damage to surrounding tissue at a surgical site. The AI system provides a surgeon with improved dexterity when the surgeon uses the robotic surgical arms at the surgical site, the improved dexterity resulting from at least partially analyzing the intraoperative data in real time by the one or more machine learning algorithms, enabling precise and adaptive manipulation of the robotic surgical arms at the surgical site.

A surgical method includes, for example, tracking, via at least one camera attached to a robotic arm of a surgical robot, a surgical site of a patient, the robotic arm having a plurality of joints and a plurality of body parts, controlling the robotic arm to perform a surgical procedure at the surgical site of the patient based on the camera tracked surgical site of the patient, and wherein the tracking comprises controlling the movement of the plurality of joints and body parts of the robotic arm to maintain a line of sight of the at least one camera directed towards the surgical site of the patient.

A surgical robot is coupled to the surgeon console. The surgical robot performs a robotic surgical procedure. The surgical robot includes one or more robotic surgical arms. A control system is coupled to the one or more robotic surgical arms. An artificial intelligence (“AI”) system includes a plurality of machine learning algorithms. The robotic surgical arms are at least partially controlled by the AI system and the control device to process intraoperative data including images captured by cameras and sensor inputs. The machine learning algorithms analyze the intraoperative data in real time, comparing it with stored images and procedural information in image recognition and procedure databases. The one or more machine algorithms enable at least partial identification of anatomical structures. In response to detection of the anatomical structures the AI system at least partially adjusts movement of the robotic surgical arms to avoid critical anatomical structures while performing the robotic surgery procedure to ensure precise targeting at the surgical site while minimizing damage to surrounding tissue at a surgical site. The AI system provides a surgeon with improved dexterity when the surgeon uses the robotic surgical arms at the surgical site, the improved dexterity resulting from at least partially analyzing the intraoperative data in real time by the one or more machine learning algorithms, enabling precise and adaptive manipulation of the robotic surgical arms at the surgical site.

Systems and methods for providing assistance to a surgeon during an implant surgery are disclosed. A method includes defining areas of interest in diagnostic data of a patient and defining a screw bone type based on the surgeon's input. Post defining the areas of interest, salient points are determined for the areas of interest. Successively, an XZ angle, an XY angle, and a position entry point for a screw are determined based on the salient points of the areas of interest. Successively, a maximum screw diameter and a length of the screw are determined based on the salient points. Thereafter, the screw is identified and suggested to the surgeon for usage during the implant surgery.

Systems and methods are provided for performing tensionable knotless surgical procedures. A suture locking device that includes a one-way locking mechanism may be utilized for tensioning and locking one or more strands of suture during the surgical procedure. The one-way locking mechanism may be established by one or more locking barbs of the suture locking device.

A surgical method is provided for use with a teleoperated surgical system (surgical system), the method comprising: recording surgical instrument kinematic information indicative of surgical instrument motion produced within the surgical system during the occurrence of the surgical procedure; determining respective kinematic signatures associated with respective surgical instrument motions; producing an information structure in a computer readable storage device that associates respective kinematic signatures with respective control signals; comparing, during a performance of the surgical procedure surgical instrument kinematic information during the performance with at least one respective kinematic signature; launching, during a performance of the surgical procedure an associated respective control signal in response to a match between surgical instrument kinematics during the performance and a respective kinematic signature.

Systems and methods for medical imaging and spectroscopy analysis arc disclosed. Some embodiments relate to digital staining. Some embodiments relate to digital staining using hyperspectral or multispectral imaging. Some embodiments relate to digital staining using RGB imaging. Some embodiments relate to analysis of other types of medical imaging and spectroscopy. Some embodiments relate to platform for performing analysis of medical imaging and spectroscopy data. Some embodiments relate to approaches for analyzing digitally stained images for use in surgical procedures.

An interactive and dynamic surgical simulation system may be used in the context of a computer-implemented interactive surgical system. An operating-room-based surgical data system may aggregate surgical activity data that is indicative of a performance of a live surgical procedure. The surgical simulation device may receive the surgical activity data from the operating-room-based surgical data system. And the surgical simulation device may simulate a surgical task based on surgical activity data. The surgical activity data may be structured by a procedure plan data structure. The procedure plan data structure may be common to the operating-room-based surgical data system and the surgical simulation device. The procedure plan data structure may be configured to covey information indicative of equipment, technique, and surgical steps in a structured format such that the equipment, technique, and surgical steps of the live surgical procedure are reflected in the simulated surgical procedure.

Systems and methods are provided for performing tensionable knotless surgical procedures. A suture locking device that includes a one-way locking mechanism may be utilized for tensioning and locking one or more strands of suture during the surgical procedure. The one-way locking mechanism may be established by one or more locking barbs of the suture locking device.

A robotic surgical system includes a surgeon consol coupled to a patient console and coupled to one or more surgical instruments. The surgeon consol is used by a surgeon to perform a surgical procedure. A surgeon computer is coupled to or at the surgeon console. The surgeon consol is coupled to the one or more surgical instruments (manipulators). A surgical robot is coupled to a robotic surgery control system and a feedback loop. The feedback loop monitors and collects data from one or more sensors used to provide feedback to the robotic surgical system. An AI system has an AI architecture that uses input data for producing an AI model. A surgical robot is coupled to a robotic surgical control system that is coupled to or includes: the feedback loop, and the artificial intelligence AI system. The control system is coupled to the surgeon consol, one or more of the feedback loop, the AI system and the control unit configured to determine a spatial configuration data of at least a portion of the one or more manipulators using image or location information of one or more of vascular or nervous structures and organs relative to the surgical intervention. One or more of the: feedback loop; AI system; and spatial configuration data used singularly or in combination to provide enhanced navigation; identification of vascular or nervous structures and organs, and manipulation of the manipulators.

Provided herein are bone hemostatic and adhesive compositions for use in surgical procedures comprising a variety of disclosed particles. Also provided are related compositions, including surgical hardware, surgical kits and packages, as well as methods of making and using the compositions.

Improved allografts having controlled and consistent properties and useful for soft tissue repair, including breast reconstruction, and other surgical procedures, are disclosed. In one embodiment, an improved acellular dermal matrix (ADM) is produced from a skin sample, where the ADM consists essentially of a single dermal tissue type (e.g., papillary or reticular) and comprises a collagen matrix having substantially uniform density and porosity. In another embodiment, two ADMs are produced from the same dermal tissue type (e.g., papillary or reticular) of the same skin sample, each of which consists essentially of reticular dermis, and comprises a collagen matrix having substantially uniform density and porosity. All such improved ADMs are suitable for use in breast reconstruction and other tissue repair and modification surgery procedures.

A method for guiding bone removal during a surgical procedure includes receiving a two-dimensional image of at least a portion of a joint during a surgical procedure; determining an alignment of a pre-generated three-dimensional model of the at least a portion of the joint with the two-dimensional image based on one or more features in the two-dimensional image related to the at least a portion of the joint, wherein the pre-generated three-dimensional model contains a representation of planned bone removal; generating an overlay image containing an overlay of at least a portion of the representation of the planned bone removal on the two-dimensional image based on the determined alignment; and displaying the overlay image to guide the bone removal during the surgical procedure.

The invention discloses a compact robotic surgical device having capabilities to perform more than one type of surgical procedure. The compact surgical device comprises at least two modes, where, in a first mode, the compact surgical device is configured to perform over-the-wire procedures, while, in a second mode, the compact surgical device is configured to perform rapid exchange-like procedures.

A pre-surgical analytical system including a plurality of images gathered from a CT scan, a classification unit that classifies the identifies landmark images from the plurality of images, a segmentation unit that segments each of the landmark image; an image analysis unit that calculates a plurality of predetermined angles and measurements of anatomical structures in each image where the image analysis unit compares each measurement and angle to predetermined thresholds and determines the number of angles and measurements are outside the predetermined threshold, and the image analysis unit weighs each of the angles and measurements outside the predetermined thresholds and calculates a score indicating a potential outcome of a surgical procedure.

FIELD: medical equipment.SUBSTANCE: method for control of hemorrhage with a tourniquet in case of injuries to the extremities of the arms and legs and in case of complete abruption of one of them. The tourniquet contains a plastic tie with slots for fixation and the head of the fixing device. The tourniquet has a nichrome wire, designed with the ability to cut the plastic tie, freeing the limb for surgical procedures. The tourniquet includes a green square handle for cutting the plastic tie with nichrome wire. The tourniquet contains a red ring-shaped handle sealed with adhesive tape for tightening the tourniquet. The tourniquet has a fabric cover for sewing onto the inside of clothing or over underwear. The tourniquet includes a Velcro fastener for closure from external influences and a plate attached to the Velcro fastener for marking the start time of the tourniquet use. In the method for control of hemorrhage, the red ring-shaped handle is pulled to tighten the tourniquet until the bleeding from the limb stops and the start time of using the tourniquet is marked on the plate.EFFECT: rapid stop of bleeding with a tourniquet.3 cl, 5 dwg

The present invention provides an amniotic membrane-loaded contact lens, its preparation method, and its application. This invention innovates the bonding method between amniotic membrane and contact lens, replacing the previous method of simply bonding the amniotic membrane and contact lens with medical biological glue. This simplifies the bonding process between amniotic membrane and contact lens, making it suitable for industrial application. It also addresses the issues of traditional sutured amniotic membranes, which suffer from decreased mechanical support, rupture, and uneven coverage over time as they cover the ocular surface. The optimization and selection of materials not only meet the basic requirements of a non-toxic and harmless adhesive, but also take into account biocompatibility and the cornea's requirements for contact lens oxygen permeability. The use of amniotic membranes is more comfortable, eliminating the need for complex surgical procedures and the irritation associated with sutures. The design of using a contact lens as an amniotic membrane support allows amniotic lenses to provide superior support and protection for the covered ocular surface.

Compositions including a first soft tissue-derived matrix and a second soft tissue-derived matrix are provided, as well as methods of making such compositions. In some embodiments, the composition comprises delipidated, decellularized adipose tissue-derived matrix and delipidated, decellularized fascial tissue-derived matrix, which may be combined in various proportions. Such adipose-fascia matrix compositions provide improved volume retention when implanted into a patient. The composition may further include exogenous cells or other substances, and / or a carrier. The composition is suitable for use in plastic surgery procedures, including reconstructive or cosmetic surgery procedures, as well as procedures for wound treatment and tissue regeneration. The methods for making the compositions may involve separation of first and second soft tissues from one another, followed by performing one or more treatments on the separated soft tissues, then combining the treated soft tissues and, optionally, performing one or more additional treatments on the combined soft tissues.