Systems and method for capnography monitoring

Abstract

Systems and methods for the capnography monitoring system utilize the sampling line identification information to transform, adjust, calibrate, or modify the patient physiological parameters detected or measured by a capnography sensor to provide more accurate capnography measurements. In addition, the smart capnography monitoring system disclosed herein may utilize connection authentication methods to automatically verify or adjust a connection between the monitoring device and stored information associated with the sampling line, thus enabling the monitoring device to automatically receive the sampling line identification information, increasing efficiency of the system.

Description

SYSTEMS AND METHOD FOR CAPNOGRAPHY MONITORINGTECHNICAL FIELD

[0001] The present technology is generally related to medical devices, particularly regarding capnography systems, methods, and devices that improve accuracy of measurements using dynamic signal modification and connection authentication.BACKGROUND

[0002] Capnography monitoring (e.g., CO2 concentration monitoring, CO2 partial pressure monitoring, end-tidal CO2 (etCO2) monitoring) of a patient involves the use of a nasal or a combined oral / nasal cannula, such as in non-intubated capnography techniques, or use of an endotracheal tube (EET), such as in intubated capnography techniques, to capture a sampling of the patient’s exhaled breath. In such instances, the patient may be connected to a capnography monitor via a capnography sampling line (e.g., Filterline®) that enables the sample of the patient’s exhaled breath, containing carbon dioxide (CO2), to travel from the cannula or endotracheal tube to the monitor.SUMMARY

[0003] Certain embodiments commensurate in scope with the originally claimed subject matter are summarized below. These embodiments are not intended to limit the scope of the disclosure. Indeed, the present disclosure encompasses a variety of forms that may be similar to or different from the embodiments set forth below.

[0004] In an embodiment, capnography monitoring system includes a sensor for sensing a physiological parameter from a patient sample, wherein the patient sample is transferred to the sensor via a sampling line. The capnography monitoring system includes a processing circuitry communicatively coupled to the sensor, and a memory storing computer-readable instructions. The computer-readable instructions, when executed by the processing circuitry, cause the processing circuitry to perform operations comprising receiving first data associated with the physiological parameter of the patient sample from the sensor, receiving sampling line identification information of the sampling line, generating second data associated with the physiological parameter of the patient sample by adjusting the first data based on the samplingline identification information, and causing a monitor to display the second data associated with the physiological parameter of the patient sample.

[0005] In an embodiment, method for capnography monitoring includes receiving, via processing circuitry of a monitoring device, first data associated with a capnography measurement of a patient breath sample, wherein the first data is received from a sensor, receiving, via the processing circuitry, sampling line identification information associated with a sampling line for transmitting the patient breath sample to the sensor, and generating, via the processing circuitry, second data associated with the capnography measurement of the patient breath sample by adjusting the first data based on the sampling line identification information. In addition, the method further includes displaying, via a monitor of the monitoring device, the second data associated with the physiological parameter of the patient sample.

[0006] Various refinements of the features noted above may exist in relation to various aspects of the present disclosure. Further features may also be incorporated in these various aspects as well. These refinements and additional features may exist individually or in any combination. For instance, various features discussed below in relation to one or more of the illustrated embodiments may be incorporated into any of the above-described aspects of the present disclosure alone or in any combination. The brief summary presented above is intended only to familiarize the reader with certain aspects and context of embodiments of the present disclosure without limitation to the claimed subject matter.BRIEF DESCRIPTION OF DRAWINGS

[0007] Advantages of the disclosed techniques may become apparent upon reading the following detailed description and upon reference to the drawings in which:

[0008] FIG. 1 is a block diagram of an embodiment of smart capnography monitoring system, in accordance with an aspect of the present disclosure;

[0009] FIG. 2 is a schematic diagram of an embodiment of a patient’s breath samples transferring within a length of a sampling line over time, in accordance with an aspect of the present disclosure;

[0010] FIG. 3 is a flow diagram of an embodiment of a method for monitoring patient physiological parameters using the smart capnography monitoring system, in accordance with an aspect of the present disclosure;

[0011] FIG. 4 is a flow diagram of an embodiment of a method for monitoring sampling line connection time patient using the smart capnography monitoring system, in accordance with an aspect of the present disclosure;

[0012] FIG. 5 is a schematic diagram of an embodiment comparing a first capnography waveform produced by conventional signal processing technique and a second capnography waveform produced by the smart capnography monitoring system, each produced from a same set of patient capnography data, in accordance with an aspect of the present disclosure;

[0013] FIG. 6 is a flow diagram of an embodiment of a method for identifying early warnings associated with patient health status via the smart capnography monitoring system, in accordance with an aspect of the present disclosure;

[0014] FIG. 7 is a schematic diagram of an embodiment of a connection authentication system of the smart capnography monitoring system, in accordance with an aspect of the present disclosure; and

[0015] FIG. 8 is a flow diagram of an embodiment of a method of authenticating a connection between the processing circuitry of the monitoring device and the chip of the connector via the connection authentication system of FIG. 7, in accordance with an aspect of the present disclosure;

[0016] FIG. 9 is a schematic diagram of an embodiment of a connection authentication system of the smart capnography monitoring system, in accordance with an aspect of the present disclosure; and

[0017] FIG. 10 is a flow diagram of an embodiment of a method of authenticating a connection between the processing circuitry of the monitoring device and the chip of the connector via the connection authentication system of FIG. 9, in accordance with an aspect of the present disclosure.DETAILED DESCRIPTION

[0018] One or more specific embodiments will be described below. In an effort to provide a concise description of these embodiments, not all features of an actual implementation are described in the specification. It should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementationspecific decisions must be made to achieve the developers’ specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another. Moreover, it should be appreciated that such a development effort might be complex and time consuming, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure.

[0019] When introducing elements of various embodiments of the present disclosure, the articles “a,” “an,” and “the” are intended to mean that there are one or more of the elements. The terms “comprising,” “including,” and “having” are intended to be inclusive and mean that there may be additional elements other than the listed elements. Additionally, it should be understood that references to “one embodiment” or “an embodiment” of the present disclosure are not intended to be interpreted as excluding the existence of additional embodiments that also incorporate the recited features.

[0020] As used herein, the terms “approximately,” “generally,” and “substantially,” and so forth, are intended to convey that the property value being described may be within a relatively small range of the property value, as those of ordinary skill would understand. For example, when a property value is described as being “approximately” equal to (or, for example, “substantially similar” to) a given value, this is intended to mean that the property value may be within + / - 5%, within + / - 4%, within + / - 3%, within + / - 2%, within + / - 1%, or even closer, of the given value.

[0021] Capnography monitoring of a patient is used to monitor CO2 concentration measurements from the patient’s exhaled breath. As such, capnography measurements detected via capnography monitoring are used to evaluate respiratory health of the patient and enable healthcare providers to quickly respond (e.g., in real-time) to the patient’s current respiratory health status based on the capnography measurements being displayed or presented, such as in a graphical waveform (e.g., capnogram), via a screen of a monitor. In particular, the patient is coupled to the monitor via a sampling line (e.g., Filterline®), or a length of hollow tube that enables a sample of the patient’s exhaled breath, containing carbon dioxide (CO2), to travelfrom the patient to the monitor. The accuracy of the capnography measurements (e.g., CO2 concentration measurements, CO2 partial pressure measurements) may be affected a length of the sampling line, inner diameter of the tubing and other factors. In particular, increasing the length of the sampling line increases a time for the breath sample to travel from the patient to the monitor, and thus decreases the accuracy of the capnography measurement at the monitor. This is due to an increase in diffusion of the breath sample over time and along the length of the sampling line. As a result, conventional capnography sampling lines are limited to a maximum or standard length, such as 2 or 4 meters, to maintain a desired accuracy of the capnography measurements. Therefore, conventional sampling lines limit continuous capnography monitoring of a patient in some medical environments. For example, as discussed above, in some medical examination techniques or diagnostic testing, such as MRI. Accordingly, improvements in capnography monitoring of patients may be desired to increase accuracy of CO2 measurements using varied lengths of sampling lines, and thus enable continuous CO2 monitoring of a patient during a wide variety of medical situations.

[0022] Thus, the present disclosure generally relates to the field of medical monitoring devices, and more particularly, to a smart capnography monitoring system. Systems and methods for the smart capnography monitoring system provide improvements in the field of capnography monitoring by increasing accuracy of capnography measurements across varied lengths of sampling lines using dynamic signal modification and connection authentication.

[0023] The smart capnography monitoring system includes a monitor (e.g., capnography monitor, monitoring device), and a sampling line that couples to the capnography monitor. The sampling line provides a pathway for a breath sample to travel from a patient coupled to one end (e.g., distal end) of the sampling line to the capnography monitor coupled to the opposite end (e.g., proximal end) of the sampling line. The monitor includes a communications component, processing circuitry, a memory, a storage, and input / output (I / O) ports. In addition, the monitor includes or is coupled to a sensor that receives the breath sample of the patient and measures (e.g., detects) patient physiological parameters, such as CO2 concentration, from the breath sample. In addition, the monitor includes a display screen for displaying the patient physiological parameters being detected and measured by the sensor.

[0024] Furthermore, the smart capnography monitoring system includes sampling line identification information stored within a data store located on the sampling line. In particular,in some embodiments, the sampling line includes a chip (e.g., microchip, integrated circuit (IC), electrically erasable programmable read-only memory (EEPROM)) that stores the sampling line identification information. The microchip is located or positioned on a connector of the sampling line. The connector is disposed at a distal end of the sampling line (e.g., opposite of a proximal end connected to a cannula or EET coupled to the patient) and used to couple the sampling line to the monitor.

[0025] The techniques of the smart capnography monitoring system disclosed herein utilize the sampling line identification information to transform, adjust, or modify (e.g., calibrate) the patient physiological parameters being detected or measured by the sensor to provide more accurate measurements, such as CO2 concentration or EtCCh concentration, and thus more accurate capnogram waveforms. In addition, the smart capnography monitoring system disclosed herein may utilize connection authentication methods to automatically verify or adjust a connection (e.g., electrical connection, coupling) between the monitor (e.g., processing circuitry) and the chip located on the connector of the sampling line. Thus, the smart capnography monitoring system enables the monitor to automatically receive the sampling line identification information. Furthermore, the smart capnography monitoring system may facilitate use of a serial line communication connection (e.g., one-wire network, one-wire communication, one-wire protocol, single-wire network, single-wire communication, singlewire protocol) to couple the chip to the monitor, increasing overall efficiency of the system.

[0026] With the foregoing in mind, FIG. 1 is a block diagram of an embodiment of a smart capnography monitoring system 10, in accordance with an aspect of the present disclosure. As illustrated, the smart capnography monitoring system 10 includes a monitoring device 12 coupled to a sampling line 14. As discussed herein, the sampling line 14 is used to facilitate travel of a breath sample of a patient 16 from the patient 16 to the monitoring device 12. In addition, the sampling line 14 includes (e.g., is coupled to) a connector 18 configured to couple the sampling line 14 to the monitoring device 12. Furthermore, the connector 18 includes a chip 20 (e.g., a data store, microchip, integrated circuit (IC), electrically erasable programmable read-only memory (EEPROM)) that stores sampling line identification information of the sampling line 14. In particular, the sampling line identification information may include sampling line parameters that are associated with the sampling line 14. For example, the sampling line identification information may include pneumatic characteristics of the sampling line 14 (e.g., pressure drop, rise time, etc.), a length measurement of the sampling line 14, aninner diameter measurement of the sampling line 14, a type of patient interface (e.g., intubated vs. non-intubated), a type of patient (e.g., adult, child, neonatal), a filter type (e.g., long-term, mid-term, short-term) of the sampling line 14, or any combination thereof. As further discussed herein, the monitoring device 12 may receive the sampling line identification information (e.g., from the chip 20 located on the connector 18) and adjust (e.g., via signal correction factors) the detected or measured patient physiological parameters based on the sampling line identification information. In some embodiments, the sampling line identification information may include an identification number, such as a unique serial number or product identification number assigned to the sampling line 14. In this case, the monitoring device 12 may receive the identification number and retrieve, using the identification number, the sampling line parameters from a local or external database.

[0027] Moreover, the monitoring device 12 includes various types of components that assist the monitoring device 12 in performing various types of tasks and operations. For example, the monitoring device 12 includes a communication component 22, a processing circuitry 24, a memory 26, a storage 28, input / output (I / O) port(s) 30, a display 32, sensor(s) 34, and the like. During operation, in some embodiments, the memory 26 may store a monitoring application 36 (e.g., smart capnography platform), that when executed by the processing circuitry 24, monitors and stores patient data (e.g., patient physiological parameters), receives and stores sampling line data (e.g., sampling line identification information), generates and trains algorithm(s) or models based on the stored patient data, the sampling line data, or both, adjusts alarm threshold levels, adjusts or identifies signal correction factors (e.g., calibration factors) associated with the patient data, dynamically adjusts patient data based on the algorithms or models and the signal correction factors, assesses patient’s health status or condition (e.g., patient’s physiological state) based on the patient data, determines proposed treatments or course of action based on the patient data (e.g., the patient’s current condition), adjust administered oxygen flow rate (e.g., to the patient), adjust sampled breath flow rate (e.g., to the monitoring device 12), identifies and detects early warnings (e.g., early warning patterns) associated with patient health status or condition based on the patient data, or any combination thereof. To this end, in some embodiments, the monitoring application 36 includes, accesses, or may be updated using a machine-learning routine that is trained based on other monitoring application data from other monitoring devices within a health care facility, an institution, a local region, or the like. As such, in some embodiments, the monitoring application 36 may not directly analyze thepatient data and / or learn information regarding the patient data to keep patient information confidential.

[0028] In addition, embodiments discussed herein may use a machine-learning model or trained model to establish learned relationships between inputs to the monitoring application 36, such as monitored patient parameters, patient data, sampling line data, and the like, and outputs, such as signal correction factors, identification of patient health status, alarm threshold levels, recommended treatments or adjustment of administered treatments, and the like. Rather than using a conversion equation or calibration adjustments in combination with a conversion equation, the machine learning model learns many relationships that may not be readily apparent to a human observer. A trained machine-learning model can improve result accuracy, particularly for conditions that are not well quantified through a conversion equation even when calibration is used. In order to get higher accuracy results, the machine-learning model can be trained and used as further described herein. Further, in contrast to a conversion equation or a calibration function, the machine-learning model may have unpredictable and dynamic outputs based on training data and updates.

[0029] Continuing with FIG. 1, the communication component 22 may be a wireless or wired communication component that facilitates communication between the monitoring device 12 and various other monitoring devices via a network, the Internet, virtual private networks, or the like. For example, the communication component 22 may send or receive patient data from other monitoring devices. In addition, the communication component 22 may facilitate communication between the monitoring device and the sensor 34. The sensor 34 is configured to measure (e.g., detect) one or more patient physiological parameters, such as partial pressure of CO2 within a patient’ s breath sample. In addition, the sensor 34 is configured to transmit data indicative of the measured patient physiological parameter to the monitoring device 12 (e.g., the processing circuitry 24). As such, in some embodiments, the sensor 34 may be integrated with the monitoring device 12. Alternatively, in some embodiments, the sensor 34 may be communicatively coupled to (e.g., via the communication component 22) and separate from the monitoring device 12.

[0030] The processing circuitry 24 may include any type of computer processor or microprocessor capable of executing computer-executable code. In addition, the processing circuitry 24 is communicatively coupled to the sensor 34. The processing circuitry 24 mayinclude a processor or multiple processors that may perform the operations described below. In particular, the processing circuitry 24 receives data from the sensor 34, such as data indicative of patient physiological parameters being measured or detected by the sensor 34. Furthermore, the processing circuitry 24 may be configured to communicatively couple to the data store 20 (e.g., chip, microchip) of the sampling line 14. For example, when the sampling line 14 is coupled to the monitoring device 12 (e.g., via the connector 18), the processing circuitry 24 receives (e.g., retrieves) the sampling line identification information from the data store 20 of sampling line 14. As further discussed herein, the processing circuitry 24 (e.g., via the monitoring application 36) may use the sampling line identification information to adjust or modify patient physiological parameters measured or detected by the sensor 34 to increase accuracy of the patient physiological parameters while using sampling lines of varied sampling line parameters. In fact, the smart capnography monitoring system 10 (e.g., the processing circuitry 24) may enable dynamic and adaptable adjustment of monitored patient physiological parameters by processing the measured or detected physiological parameters according to sampling line parameters that are unique to the particular sampling line being used for the patient 16. In addition, the smart capnography monitoring system 10 (e.g., the processing circuitry 24) may also utilize patient data associated with the patient 16 to further assess the more accurate monitored patient physiological parameters to yield patient-specific assessments, diagnostics, treatment recommendations, corrective actions, and the like.

[0031] For example, when the smart capnography monitoring system 10 is coupled to a patient 16, the sampling line 14 receives a patient’s breath sample from the patient and facilitates travel (e.g., through a conduit of the sampling line 14) of the patient’s breath sample to the monitoring device 12. In particular, in some embodiments, the sensor 34 may be located at a distal end of the sampling line 14, such as proximate a location where the sampling line 14 interfaces with or couples with the monitoring device 12. As such, the patient’s breath sample may travel a particular distance that is substantially equal to a length of the sampling line 14 before reaching the location of the sensor 34 (e.g., to then be measured via the sensor 34.) In addition, the patient’ s breath sample may travel for an amount of time that is dependent on the length of the sampling line 14. To this end, increasing the length of the sampling line 14 increases both the distance the patient’s breath sample travels to reach the monitoring device 12 and the amount of time the patient’ s breath sample travels within the sampling line 14 before reaching the monitoring device 12. Therefore, as further discussed herein, the patient’s breathsample may diffuse along the length of the sampling line 14 over time, and accuracy of the patient’s physiological parameter measured or detected by the sensor 34 from the patient’s breath sample may decrease as a length of the sampling line 14 being used increases.

[0032] As an example, FIG. 2 is a schematic diagram of an embodiment of patient’s breath samples 50 traveling along a length 52 of a sampling line 14 over time, in accordance with an aspect of the present disclosure. In particular, the patient’s breath samples 50 may be traveling in a first direction 54, and include a first proximal sample 56 and a second proximal sample 58 traveling within the sampling line 14. The first and second proximal samples 56, 58 are additionally illustrated in graphical form as a first proximal signal 60 and a second proximal signal 62, respectively. Specifically, the first and second proximal samples 56, 58 may be successive patient breath samples observed (e.g., measured, detected) at a proximal end 64 of the sampling line 14 (e.g., proximate the patient 16, distal the monitoring device 12.) In addition, the patient’s breath samples 50 include a first distal sample 66 and a second distal sample 68 within the sampling line 14. The first and second distal samples 66, 68 are additionally illustrated in graphical form as a first distal signal 70 and a second distal signal 72, respectively. Specifically, the first and second distal samples 66, 68 may be the first and second proximal samples 56, 58 observed (e.g., measured, detected) at a distal end 74 of the sampling line 14 (e.g., distal the patient 16, proximate the monitoring device 12, after traveling the length 52 of the sampling line 14). FIG. 2, illustrates effects of diffusion of the patient’s breath samples 50 over the length 52 of the sampling line 14 and over time. In particular, the first and second distal signals 70, 72 are less discrete than the first and second proximal signals 60, 62. In addition, an amplitude or maximum peak (e.g., used to determine end-tidal carbon dioxide concentrations (EtCO2)) of the first and second distal signals 70, 72 are less than an amplitude or maximum peak of the first and second proximal signals 60, 62. In addition, a baseline of the first and second distal signals 70, 72 are less than an amplitude of the first and second proximal signals 60, 62.

[0033] To this end, the patient physiological parameters or signals detected (e.g., measured) by a sensor (e.g., proximal to a monitoring device), for example, from the first and second distal samples 66, 68, may not accurately reflect an original or proximal breath sample signal, such as the first and second proximal signals 60, 62 that may be detected (e.g., measured) from the first and second proximal samples 56, 58. Thus, in order to correct for diffusion or other factors that may affect the accuracy of the measured patient physiological parameters (e.g., via thesensor 34), the processing circuitry 24 (e.g., the monitoring application 36) may utilize the sampling line identification information, patient data, or both to dynamically adjust or modify (e.g., calibrate) the monitored patient physiological parameters.

[0034] Returning to FIG. 1, the processing circuitry 24 may be configured to receive user input such as selections for displaying patient data, selections for disabling or enabling various alarms, selections for setting certain alarm thresholds, data (e.g., patient data, health record data) input by a healthcare professional, selections for enabling or disabling administration of remedial treatments or interventions, or any combination thereof. The I / O port(s) 30 may be interfaces that may couple to other peripheral components such as input devices (e.g., keyboard, mouse), sensors, input / output (VO) modules, sampling lines (e.g., via connectors), and the like. Furthermore, the processing circuitry 24 may be communicatively coupled to other output devices, which may include standard or special purpose computer monitors associated with the processing circuitry 24. For example, the monitoring device 12 includes the display 32 configured to display the monitored patient physiological parameters, other patient data, current patient health status, alarms or indications, such as for recommended treatments, current treatment administration information, and the like. The display 32 may operate as a human machine interface (HMI) (e.g., a graphical user interface (GUI)) to depict visualizations associated with software or executable code being processed by the processing circuitry 24. The display 32 may be any suitable type of display, such as a liquid crystal display (LCD), plasma display, or an organic light emitting diode (OLED) display, for example. Additionally, in some embodiments, the display 32 may be provided in conjunction with a touch-sensitive mechanism (e.g., a touch screen) that may function as part of a control interface for the monitoring device 12.

[0035] In addition, the monitoring device 12 may be communicatively coupled to the network 38, which may include collections of monitoring devices, the Internet, an Intranet system, or the like. The network 38 may facilitate communication between the monitoring device 12 and various other data sources. For example, the network may facilitate communication between a monitoring device located on a surgery floor and an additional monitoring device located on an outpatient floor. In another example, the network 28 may facilitate communication between the monitoring device 12 and the database 40. In particular, the monitoring device 12 may be communicatively coupled (e.g., via the network 38) to one or more databases 40 that may be configured to store patient data (e.g., historical patient data,patient health record data, patient physiological parameters), additional data associated with the monitoring application 36 (e.g., machine-learning models or algorithms, signal correction factors, alarm thresholds), or both. As such, the processing circuitry 24 may receive (e.g., retrieve) such data from the one or more databases 40. For example, the processing circuitry 24 may send a request for patient data (e.g., from a health record) associated with the patient 16 being monitored, may send a request for sampling line identification information based on receiving an identification number associated with the sampling line 14, may receive one or more patient specific and / or sampling line specific algorithms or models based on the patient data, the sampling line identification information, or both.

[0036] Although the database 40 is illustrated as separate from the monitoring device 12, in an embodiment, the database 40 may be a component within the monitoring device 12. In an embodiment, the database 40 may be local to the monitoring device 12 and store patient data, the additional data associated with the monitoring application 36, or both on the monitoring device 12. In other embodiments, as described herein, the database 40 may be a cloud service or a remote database communicatively coupled to the monitoring device 12 via the network 38.

[0037] In some embodiments, one or more machine-learning trained algorithms or models may be stored in the database 40, such as in a look-up table. For instance, multiple algorithms or models may be categorized based on a patient type, based on sampling line parameters, or both. In addition, the monitoring device 12 (e.g., the processing circuitry 24) receives patient data associated with the patient 16 and / or sampling line identification information (e.g., the sampling line parameters) of the sampling line 14, and requests a machine-learning trained algorithm or model based on the patient data and / or the sampling line identification information. Thus, the monitoring device (e.g., the processing circuitry 24) may receive the requested machine-learning trained algorithm or model and execute the requested machine-learning trained algorithm or model via the monitoring application 36 to produce more accurate patient physiological data and patient health status analysis. In other words, the monitored patient physiological parameters may be adjusted or modified (e.g., calibrated) based on the patient data and / or the sampling line identification information to generate more accurate parameters or signals that more accurately reflect actual patient physiological measurements. Therefore, the smart capnography monitoring system 10 provides for continuous monitoring and more accurate patient physiological measurements or data by accounting for differences in patient types or characteristics, and differences in characteristics of the sampling lines, such as variouslengths. For example, the smart capnography monitoring system 10 enables use of a variety of different sampling line lengths that may enable continuous and accurate monitoring of the patient during various different medical environments, medical examination techniques, and / or diagnostic testing, such as magnetic resonance imaging (MRI).

[0038] Furthermore, the smart capnography monitoring system 10 may provide for continuous training or updating of the machine-learning trained algorithms or models based on data collected from the monitoring device 12, data from one or more databases, or both (e.g., training data, real data). For example, the monitoring device 12 may execute one or more machine-trained algorithms or models and store associated data (e.g., patient data, sampling line parameters / identification information), user input, output data, or any combination thereof, of the one or more machine-learning trained algorithms or models, such as in the storage 28. In some embodiments, the associated data, user input, output data, or any combination thereof, may be stored in the one or more databases 40. In any case, the machine-learning trained algorithms or models of the smart capnography monitoring system 10 may be trained or continuously updated based on current and historical clinical data to improve the machinelearning trained algorithms or models and thus improve the accuracy of the monitored patient physiological parameters and analysis of such parameters by the monitoring device 12 (e.g., to determine or administer remedial treatment, issue warnings or alarms, etc.)

[0039] Continuing with FIG. 1, the memory 26 and the storage 28 may be any suitable articles of manufacture that can serve as media to store processor-executable code, data, or the like. These articles of manufacture may represent computer-readable media (e.g., computer- readable instructions, any suitable form of short-term memory or long-term storage) that stores the processor-executable code used by the processing circuitry 24 to perform the presently disclosed techniques. As used herein, applications may include any suitable computer software or program that may be installed onto the monitoring device 12 and executed by the processing circuitry 24. The memory 26 and the storage 28 may represent non-transitory (e.g., physical) computer-readable media (e.g., any suitable form of memory or storage) that may store the processor-executable code used by the processing circuitry 24 to perform various techniques described herein. For example, the memory 26 includes machine-learning algorithms or models configured to learn relationships between the patient data, the sampling line identification information, or both, and signal correction factors used to adjust the monitored patient physiological parameters. In addition, the machine-learning algorithms or models may beconfigured to learn relationships between the monitored patient physiological parameters and alarm thresholds, warnings (e.g., early warnings) or indications of patient health status, treatment administration recommendations, flow rates (e.g., of administered treatments, of oxygen (O2) to the patient), and the like.

[0040] As an example, and as further discussed in more detail below, the monitoring application 36 may utilize the machine-learning algorithms or models to identify early warnings associated with a patient’s health status. In particular, the machine-learning algorithms or models may be configured to identify patterns in the patient data (e.g., patient physiological parameters) that indicate a critical health status may be imminent or may occur within a threshold period of time. As such, the monitoring application 36 may be able to cause the monitoring device 12 (e.g., via the display 32) to issue or display an early warning associated with the critical health status. Thus, a healthcare provider or the monitoring device 12 may be able to respond preemptively to the health status of the patient and administer appropriate remedial action and / or treatments before the health status of the patient becomes critical.

[0041] It should be noted that the smart capnography monitoring system 10 should not be limited to include the components described above. Instead, the components described above with regard to the smart capnography monitoring system 10 are examples, and the smart capnography monitoring system 10 may include additional or fewer components relative to the illustrated embodiment.

[0042] FIG. 3 is a flow diagram of an embodiment of a method 100 for monitoring patient physiological parameters using the smart capnography monitoring system 10, in accordance with an aspect of the present disclosure. The method 100 includes various computer- implemented steps represented by blocks that may be performed by the processor-based device (e.g., the monitoring device 12, the processing circuitry 24) described with respect to FIG. 1. It should also be noted that the method 100 may be performed by other suitable processor-based devices (e.g., cloud server, webpage, tablet, mobile device, etc.) that may perform the methods described herein. For example, certain steps or portions of the method 100 may be performed by separate systems or devices, such as one or more processors, processor-based devices, and / or computers. Although the following description of the method 100 is described in a particular order, it should be noted that the method 100 is not limited to the depicted order; and, instead,the method 100 may be performed in any suitable order. Further, blocks / steps may be omitted and / or added to the method 100.

[0043] At block 102, the monitoring device (e.g., the processing circuitry) may receive sampling line identification information (e.g., sampling line properties, sampling line data) of a connected sampling line. For example, as discussed herein, the sampling line may include a connector that couples the sampling line to the monitoring device. In addition, the connector may include a chip (e.g., microchip) that stores the sampling line identification information. As such, the monitoring device may be configured to communicatively couple to the chip. In particular, in some embodiments, the chip may be configured to transmit data to the monitoring device when the connector is physically coupled to the monitoring device. Furthermore, and as discussed in more detail below with reference to FIGS. 7-9, the chip may be configured to couple to the monitoring device via a serial line communication connection (e.g., one-wire network, one-wire communication, one-wire protocol, single-wire network, single-wire communication, single-wire protocol). In addition, the monitoring device may be configured to authenticate, verify, and / or adjust a connection between the chip and the monitoring device (e.g., the processing circuitry) through a connection authentication system, as discussed in more detail below.

[0044] The sampling line identification information may include sampling line parameters that are associated with the sampling line. For example, the sampling line identification information may include pneumatic characteristics of the sampling line (e.g., pressure drop, rise time, etc.), a length measurement of the sampling line, an inner diameter measurement of the sampling line, a type of patient interface (e.g., intubated vs. non-intubated), a type of patient (e.g., adult, child, neonatal), a filter type (e.g., long-term, mid-term, short-term) of the sampling line, or any combination thereof. In some embodiments, the sampling line identification information may include an identification number, such as a unique serial number or product identification number assigned to the sampling line. In this case, the monitoring device may receive the identification number and retrieve, using the identification number, the sampling line parameters from a local or external database.

[0045] Continuing with FIG. 3, at block 104, the monitoring device may determine one or more signal correction factors (e.g., coefficients) based on the sampling line identification information. In some embodiments, the monitoring device may include one or more look-uptables, and may identify or determine the signal correction factor(s) based on the one or more look-up tables and the sampling line identification information. For example, a look-up table may store sampling line identification information along with the signal correction factors that are associated with particular sampling line identification information. In other embodiments, the monitoring device may include one or more algorithms or models to determine the signal correction factors based on the sampling line identification information. Further, in another embodiment, the monitoring device may include a monitoring application with one or more machine-learning algorithms or models (e.g., trained machine-learning algorithms or models.) In such embodiments, the monitoring application may receive the sampling line identification information and input the sampling line identification into a machine-learning algorithm or model to determine the signal correction factor(s).

[0046] At block 106, the monitoring device may receive one or more patient physiological parameters from a sensor coupled to the monitoring device. In particular, the sensor is configured to measure (e.g., detect) one or more patient physiological parameters associated with a patient being monitored by the monitoring device. For example, the sensor may measure or detect a partial pressure of CO2 within a patient’s breath sample. In addition, the sensor transmits data indicative of the measured patient physiological parameter to the monitoring device (e.g., the processing circuitry). For example, in some embodiments, the monitoring device may be coupled to a patient via the sampling line, and the sampling line may receive the patient’s breath sample and facilitate travel (e.g., through a conduit of the sampling line) of the patient’s breath sample to the monitoring device. In particular, in some embodiments, the sensor may be located at a distal end of the sampling line, such as proximate a location where the sampling line interfaces with or couples with the monitoring device. As such, the patient’s breath sample may travel a particular distance that is substantially equal to a length of the sampling line before reaching the location of the sensor. The sensor may then measure or detect the patient physiological parameter and transmit data to the monitoring device indicative of the monitored patient physiological parameter.

[0047] At block 108, the monitoring device may determine adjusted patient physiological parameters based on the signal correction factors. In particular, the monitoring device (e.g., via the processing circuitry) may calibrate or dynamically modify the patient physiological parameters received from the sensor according to the signal correction factors. As such, the monitoring device may increase accuracy of the adjusted patient physiological parameters, suchthat they more closely reflect actual physiological parameters of the patient. As discussed herein, the smart capnography monitoring system (e.g., the monitoring device) may enable dynamic and adaptable adjustment of monitored patient physiological parameters by processing the measured or detected physiological parameters according to the sampling line parameters that are unique to the particular sampling line being used for the patient. In addition, in some embodiments, the smart capnography monitoring system (e.g., the monitoring device) may also utilize patient data associated with the patient to further assess the more accurate monitored patient physiological parameters to yield patient-specific assessments, diagnostics, treatment recommendations, corrective actions, and the like.

[0048] At block 110, the monitoring device may display the adjusted patient physiological parameters via a display. For example, the displayed adjusted patient physiological parameters may include a capnography waveform. The displayed capnography waveform may provide more accurate information and / or data associated with the patient’s current medical status, such as current respiratory health status. As such, the smart capnography monitoring system (e.g., the monitoring device) may enable a healthcare provider to more accurately assess the patient and determine appropriate care for the patient.

[0049] FIG. 4 is a flow diagram of an embodiment of a method 120 for monitoring use time of different sampling line types using the smart capnography monitoring system 10, in accordance with an aspect of the present disclosure. The method 120 includes various computer-implemented steps represented by blocks that may be performed by the processorbased device (e.g., the monitoring device 12, the processing circuitry 24) described with respect to FIG. 1. It should also be noted that the method 120 may be performed by other suitable processor-based devices (e.g., cloud server, webpage, tablet, mobile device, etc.) that may perform the methods described herein. For example, certain steps or portions of the method 120 may be performed by separate systems or devices, such as one or more processors, processor-based devices, and / or computers. Although the following description of the method 120 is described in a particular order, it should be noted that the method 120 is not limited to the depicted order; and, instead, the method 120 may be performed in any suitable order. Further, blocks / steps may be omitted and / or added to the method 120.

[0050] At block 122, the monitoring device (e.g., the processing circuitry) may receive sampling line identification information of a connected sampling line as generally discussedwith respect to FIG. 3. In an example, the sampling line identification information may include a recommended use time for the sampling line 14. The monitoring device, upon detection of sampling line connection, can monitor a connection time of the sampling line 14 at block 126. For example, initial receipt of the sampling line identification information can start a clock, and the monitoring device can operate to activate an alarm or notification at block 128 when the connection time meets or exceeds a recommended connection time based on the sampling line identification information. In this manner, different sampling lines 14 may be suited for different connection situations. Some sampling lines 14 may be suited for shorter connection times (e.g., less than 6 hours) while other sampling lines 14 may be suited for longer connection times. The connection time recommendation may be based on a filter type and a recommended time of operation of the filter until the filter is full (e.g., wetted with moisture from the sampled breath) or otherwise past its use time. Thus, sampling lines 14 may be provided that are suitable for short duration procedures and that prompt a notification to alert users when the sampling line 14 should be replaced or exchanged.

[0051] The characteristic rise time for a particular sampling line type may be provided as part of sampling line identification information. As used herein, the term “rise time” may refer to the time required for the monitoring device to respond once CO2 has entered the sampling cell. The sampling technique can ensure that the waveform fidelity and shape of the changing CO2 concentration is kept by using generally regular laminar flow with an undisturbed wavefront. Such disturbances are magnified if the gas flow passes via rough tubing, liquid filters, or sections of varying diameter in the tubing, conduits or connectors, abrupt changes in direction and irregularities etc. A characteristic rise time of a particular sampling line 14, which may be influenced by tube diameter, a filter type, a connection type, or other structural features, may be included as part of sampling line identification information.

[0052] During sampling and after initial connection of the sampling line 14, the monitoring device may experience a rise time that may or may not be characteristic of a rise time indicative by the sampling line identification information. For example, longer sampling lines may experience longer rise times. In certain cases, the monitoring device can monitor rise time after sampling line connection and identify discrepancies between a measured rise time and the characteristic rise time. If the rise time is slower than expected, this may be indicative of a poor transfer of the breath. In an embodiment, the monitoring device may adjust operation toincrease a flow rate of the sampled breath (e.g., by adjusting pump or other flow operations) to shorten the rise time.

[0053] Different types of sampling lines 14 with different filter types and / or tube diameters or length may result in different attenuations to the CO2 signal, particularly in cases during relatively fast breathing (e.g., 100 breaths per minute or more). Rather than having a fixed rise time reconstruction coefficient, the disclosed techniques permit signal reconstruction to account for rise time using sampling-line specific characteristics based on sampling line identification information. As discussed herein, the information may be provided as a stored coefficient or may be provided as identification information that is used in a look-up table or provided as input to an algorithm stored on the monitoring device.

[0054] As an example, FIG. 5 is a schematic diagram of an embodiment comparing a first capnography waveform 150 produced by conventional signal processing technique and a second capnography waveform 152 produced by the smart capnography monitoring system, each produced from a same set of patient capnography data, in accordance with an aspect of the present disclosure. In particular, the first capnography waveform 150 is displayed via a first graphical user interface (GUI) 154 and generated from the set of patient capnography data processed by a conventional signal processing technique. In addition, the second capnography waveform 152 is displayed via a second GUI 156 and generated from the set of patient capnography data processed by the smart capnography monitoring system as discussed herein. Furthermore, the set of patient capnography data is collected via a sampling line with a length of approximately 9 meters, which is longer than the standard 2 meter or 4 meter sampling lines. As such, the first capnography waveform 150 displayed by the first GUI 154 includes an elevated baseline and a smaller amplitude when compared to the second capnography waveform 152 displayed by the second GUI 156. This is due to the longer length of the sampling line causing an increase in the diffusion effects on the patient’s breath samples within the sampling line. However, the second capnography waveform 152 is more accurate due to the set of patient capnography data being processed by the smart capnography monitoring system. In particular, the second capnography waveform 152 corresponds more closely with an actual or original (e.g., reflecting patient capnography measurements that may be taken more proximal to the patient) patient capnography measurements, than the first capnography waveform 150 that was processed or generated via the conventional signal processing techniques.

[0055] FIG. 6 is a flow diagram of an embodiment of a method 200 for identifying early warnings associated with patient health status via the smart capnography monitoring system, in accordance with an aspect of the present disclosure. The method 200 includes various computer-implemented steps represented by blocks that may be performed by the processorbased device (e.g., the monitoring device 12, the processing circuitry 24) described with respect to FIG. 1. It should also be noted that the method 200 may be performed by other suitable processor-based devices (e.g., cloud server, webpage, tablet, mobile device, etc.) that may perform the methods described herein. For example, certain steps or portions of the method 200 may be performed by separate systems or devices, such as one or more processors, processor-based devices, and / or computers. Although the following description of the method 200 is described in a particular order, it should be noted that the method 200 is not limited to the depicted order; and, instead, the method 200 may be performed in any suitable order. Further, blocks / steps may be omitted and / or added to the method 200.

[0056] At block 202, the monitoring device may receive (e.g., determine) adjusted patient physiological data associated with a patient. In particular, the adjusted patient data may be monitored patient physiological parameters processed using the smart capnography monitoring system, as discussed herein. Furthermore, at block 204, the monitoring device may receive patient data associated with the patient. In particular, the monitoring device may receive patient data from one or more external databases, a health record associated with the patient, user input (e.g., via a healthcare professional), or the like. The patient data maybe current patient data, historical patient data, or both. The patient data may also include current or historical patient physiological data, health record data, such as medications prescribed to the patient, past and / or recent treatments or surgeries, allergies, medical diagnoses, and the like.

[0057] Moreover, at block 206, the monitoring device may contextualize the adjusted patient physiological data with the patient data to produce a data pattern associated with the patient. In other words, the monitoring device may produce (e.g., generate) a data pattern based on the contextualization of the adjusted patient physiological data using the patient data. Data patterns may include a collection of datasets from various data sources (e.g., sensor / monitoring device, the external database, health record database, user input), wherein a portion of the datasets correspond to a time period (e.g., a threshold amount of time or time window) that includes a time in which the patient’ s physiological data was measured or collected via the sensor (e.g., and transmitted to the monitoring device). As such, the data patterns may providecontextualized current patient data related to a current health status of the patient being monitored.

[0058] At block 208, the monitoring device may receive one or more historical data patterns each associated with an at risk event, based on the data pattern. The historical data patterns may be stored (e.g., via the external database) by data type, by at risk event type, patient type, or any combination thereof. In particular, the monitoring device may retrieve or request the historical data patterns from an external database, based on the data pattern. For example, the received one or more historical data patterns may correspond to or be similar to the data pattern, such as contain similar data pattern structure, composition, or type of data. More specifically, in some embodiments, the similar historical data patterns may be identified as corresponding to the data pattern based on data type or patient type. Moreover, each of the historical data patterns may be associated with an at risk event. The at risk event may be a health status, health condition or particular instance in which a patient associated with the historical data pattern was in a critical or at risk health condition. Furthermore, data included in the historical data patterns may have been collected, measured, or monitored during and / or may represent a period of time immediately before the at risk event (e.g., data collected prior to the at risk event.)

[0059] At block 210, the monitoring device may compare the data pattern to the one or more historical data patterns to determine, at block 212, whether the data pattern is associated with the at risk event based on the comparison. In particular, the monitoring device may analyze the data pattern and a historical data pattern and compare data measurements and values within the respective patterns to determine an amount of similarity between the data pattern and the historical data pattern. In addition, the monitoring device may determine whether the amount of similarity is equal to or exceeds a threshold amount of similarity. If the amount of similarity is equal to or exceeds the threshold amount of similarity, the monitoring device may determine that the data pattern is associated with the at risk event.

[0060] In some embodiments, as discussed herein, the monitoring device may utilize machine-learning algorithms or models to identify early warnings associated with a patient’s health status. In particular, the monitoring device may input the data pattern and / or additional data associated with the patient into a machine-learning algorithm or model, and the monitoring device may be configured to learn, via the machine-learning algorithm or model, relationships between the data patterns and a patient’s health status and / or an indication of an imminent orhigh probability of an at risk event occurring for the patient. In other words, the machinelearning algorithm or model may be trained or configured to identify patterns in the patient data (e.g., patient physiological parameters) that indicate a critical health status may be imminent or may occur within a threshold period of time. As such, the monitoring device (e.g., via the machine-learning algorithm or model) may be able to identify an at risk event associated with the patient, based on the data pattern or patient data input into the machine-learning algorithm or model.

[0061] Furthermore, when the monitoring device determines that the data pattern is associated with the at risk event, at block 214, the monitoring device may display a notification indicating that the at risk event is imminent or probability of the at risk event is high. For example, the monitoring device may display a notification via the display, issue a visual and / or auditory alarm through lights and / or other output devices, such as speakers. In some embodiments, the monitoring device may be communicatively coupled to other external device, such as another monitoring device or mobile device. In such embodiments, the monitoring device may transmit a push notification to the external device. The notification may include information associated with the current patient health status, monitored patient physiological data, treatments and / or remedial actions associated with (e.g., specific to) the patient and / or the at risk event, administration of medications and / or fluids to the patient, or the like.

[0062] When the monitoring device determines that the data pattern is not associated with the at risk event, such as when the amount of similarity is below the threshold amount of similarity, the monitoring device may continue through blocks 202-212, to receive adjusted patient physiological data, receive patient data, contextualize the adjusted patient physiological data to produce data patterns, receive historical data patterns, and compare the data patterns to the historical data patterns to determine if the data pattern is associated with an at risk event. As such, the method 200 of the smart capnography monitoring system may enable automatic detection and identification of early warning data patterns associated with an at risk health condition for a patient. Thus, a healthcare provider or the monitoring device may be able to respond preemptively to the health status of the patient and administer appropriate remedial action and / or treatments before the health status of the patient becomes critical.

[0063] In addition, the smart capnography monitoring system disclosed herein may include connection authentication systems and methods to automatically verify or adjust connection ofthe monitoring device (e.g., processing circuitry) with the chip located on the connector of the sampling line. Thus, the smart capnography monitoring system, via the connection authentication system, enables the monitoring device to receive (e.g., automatically receive) the sampling line identification information despite a physical variation in connection (e.g., contact between the connector and the monitor). The connection authentication system may increase efficiency of the smart capnography monitoring system through use of a serial line communication connection (e.g., one-wire network, one-wire communication, one-wire protocol, single-wire network, single-wire communication, single- wire protocol). For instance, one-wire connections enable components of the chip to receive power and enables information (e.g., data) to be transmitted and received via a single signal line (e.g., one-wire and a ground). As such, the one-wire connection may decrease cost associated with powering and communicating with the chip located on the connector of the sampling line, in addition to enabling the chip and connection components to be relatively small (e.g., space saving).

[0064] It should be appreciated that although the connection authentication system is discussed herein as integrated with the smart capnography system, in some embodiments, the connection authentication system may be used in other systems or devices. For example, the connection authentication system may be used to authenticate a connection between any such connector that includes a chip with serial line communication components and any such device that includes a processor that verifies the connection and receives information from the chip via the serial line communication components.

[0065] FIG. 7 is a schematic diagram of an embodiment of a connection authentication system 250 (e.g., rotary connection system) of the smart capnography monitoring system 10, in accordance with an aspect of the present disclosure. The connection authentication system 250 includes the processing circuitry 24 (e.g., micro-processor, micro-controller) of the monitoring device 12, and the chip 20 (e.g., microchip, integrated circuit (IC), electrically erasable programmable read-only memory (EEPROM)) of the connector 18 coupled to the sampling line 14. The connection authentication system 250 may be configured to communicatively couple the processing circuitry 24 to the chip 20, such that the smart capnography monitoring system 10 may verify a connection between the processing circuitry 24 and the chip 20 and receive authentication information from the chip 20 (e.g., data, sampling line identification information). In some embodiments, as discussed herein, the connection authentication system250 may identify the sampling line 14 coupling to the monitoring device 12 based on the authentication information.

[0066] As illustrated in FIG. 7, the connection authentication system 250 includes three separate general purpose input / output (GPIO) ports (e.g., digital GPIO port). In particular, the connection authentication 250 includes a first GPIO port 252 (GPIO1), a second GPIO port 254 (GPIO2), and a third GPIO port 256 (GPIO3). The first, second, and third GPIO ports 252, 254, 256 may each be capable of transmitting and receiving data, as well as transmitting power from the processing circuitry 24. In particular, each of the first, second, and third GPIO ports 252, 254, 256 may be set to (e.g., programmed to, configured to, via the processing circuitry 24) one of three configurations (e.g., electrical states). As an example, a first configuration may be an active input / output state (e.g., logic output of “1”, set to a high state). In particular, the active input / output state may facilitate transmission and reception of signals (e.g., data) at a relatively high voltage, for example of 3.3 V, as compared to a low voltage, for example of approximately 0 V. A second configuration of the three configurations may include a passive output state (e.g., logic output of “0”, set to a low state, low impedance). In particular, the passive output state may act similar to a ground state or facilitate transmission of signals at a relatively low voltage of approximately 0 V. A third configuration of the three configurations may include an inactive input state (e.g., isolator state) with relatively high impedance. The third configuration may inhibit transmission of signals from or reception of signals to the processing circuitry 24.

[0067] As an example, Table 1 below includes possible combinations of the first, second, and third configurations of the first, second, and third GPIO ports 252, 254, 256. In particular, the first configuration is represented by “1W”, indicating that data is being transmitted via the respective GPIO in this first configuration. In addition, the second configuration is represented by “GND”, indicating that the respective GPIO is set to the passive output with relatively low voltage, similar to the ground state. Further, the third configuration is represented by “H.Z.”, indicating that the respective GPIO is set to the inactive input configuration with relatively high impedance.Table 1 - Connection State Combinations for GPIO1, GPIO2, and GPIO3

[0068] Returning to FIG. 7, each of the first, second, and third GPIO ports 252, 254, 256 is coupled to the processing circuitry 24 and to a respective pin via a respective signal line. In particular, the first GPIO port 252 is coupled to a first pin 258 (e.g., electrical contact surface) via a first signal line 260, the second GPIO port 254 is coupled to a second pin 262 via a second signal line 264, and the third GPIO port 256 is coupled to a third pin 266 via a third signal line 268. Furthermore, the first, second, and third GPIO ports 252, 254, 256 may each operate within a respective current limit. For instance, in some embodiments, each of the first, second, and third GPIO ports 252, 254, 256 may be coupled to a respective resistor (e.g., pull-up resistor) configured to limit a current and / or an amount of voltage output by the respective GPIO port. In particular, the connection authentication system 250 includes a first resistor 270 coupled to the first signal line 260 at a first node 272, a second resistor 274 coupled to the second signal line 264 at a second node 276, and a third resistor 278 coupled to the third signal line 268 at a third node 280. The first, second, and third resistors 270, 274, 278 may enable the connection authentication system 250 to test or adjust the connection between the processing circuitry 24 and the chip 20 by operating the respective GPIO port at a reduced power level or reduced amount of current until the connection is verified. The reduced power level or reduced amount of current may prevent relatively higher voltage output occurring at a negative connection to the chip 20 during the connection authentication process. It should be appreciated that, in some embodiments, the connection authentication system 250 (e.g., the processing circuitry 24) may include any number of GPIO ports (e.g., 2, 4, 5, 6, 7, 10) coupled to acorresponding number of pins (e.g., 2, 4, 5, 6, 7, 10). Furthermore, each of the GPIO ports may be set to any of the above mentioned configurations to enable authentication of the connection between the processing circuitry 24 and the chip 20.

[0069] In addition, the connection authentication system 250 may couple (e.g., communicatively couple, electrically couple) the processing circuitry 24 to a serial line system 282 (e.g., one-wire system, single-wire system) of the chip 20. The serial line system 282 includes a serial signal line 284 configured to couple the chip 20 to a first connection surface 286 (e.g., contact surface, electrical surface, first electrode, positive electrode) of the connector 18, and a ground signal line 288 (e.g., a ground connection) configured to couple the chip 20 to a second connection surface 290 (e.g., negative electrode) of the connector 18. In addition, as illustrated in FIG. 7, the serial line system 282 includes a negative connection element 292 (e.g., diode, opposite-diode) coupled between the serial signal line 284 and the ground signal line 288. The negative connection element 292 is configured to sink (e.g., direct, redirect) at least a portion of a signal (e.g., current, power) received at the second connection surface 290 from the ground signal line 288 to the serial signal line 284. In this way, in some embodiments, the negative connection element 292 may protect the chip 20 from receiving power via a negative connection during the connection authentication process.

[0070] FIG. 8 is a flow diagram of an embodiment of a method 300 of authenticating a connection between the processing circuitry of the monitoring device and the chip of the connector via the connection authentication system, in accordance with an aspect of the present disclosure. The method 300 includes various computer-implemented steps represented by blocks that may be performed by the processor-based device (e.g., the monitoring device 12, the processing circuitry 24) described with respect to FIGS. 1 and 7. It should also be noted that the method 300 may be performed by other suitable processor-based devices (e.g., cloud server, webpage, tablet, mobile device, etc.) that may perform the methods described herein. For example, certain steps or portions of the method 300 may be performed by separate systems or devices, such as one or more processors, processor-based devices, and / or computers. Although the following description of the method 300 is described in a particular order, it should be noted that the method 300 is not limited to the depicted order; and, instead, the method 300 may be performed in any suitable order. Further, blocks / steps may be omitted and / or added to the method 300.

[0071] The connection authentication system (e.g., via the processing circuitry) may utilize a detection algorithm to test (e.g., run, execute) multiple combinations of GPIO configurations to determine (e.g., detect) a successful combination, and thus determine a successful connection between the processing circuitry and the chip. In particular, a successful connection may be a connection that enables the processing circuitry to transmit and receive data to and from the chip, and that enables the chip (e.g., a capacitor of the chip) to receive power (e.g., a power supply) from the processing circuitry. As such, at block 302, the processing circuitry transmits data via a current GPIO configuration combination. For example, in some embodiments, the first, second, and third GPIO ports may be set to Combination No. 1 as shown in Table 1. In particular, the first GPIO port may be set to the first configuration of “1W” or an active input / output state that enables the first port GPIO to transmit and receive data. The second port GPIO may be set to the third configuration of “H.Z.” or an inactive input state with a relatively high impedance. In addition, the third GPIO port may be set to the second configuration of “GND” or a passive input state. Accordingly, in such instances, the processing circuitry may transmit data via the first GPIO port. It should be understood that the processing circuitry may utilizes any of the configuration combinations of Table 1 as an initial configuration combination, and transmit the data via the respective GPIO port that is set to the first configuration.

[0072] At block 304, the processing circuitry may determine whether the current GPIO configuration combination is a successful combination. In some embodiments, the processing circuitry may receive an indication of whether the connection between the processing circuitry and the chip is correct (e.g., true, positive connection) or false (e.g., negative connection). For example, in some embodiments, the processing circuitry may receive an indication that the connection is true or an indication that the connection is false in response to transmitting data via the current GPIO configuration combination. In particular, as in the instant example, the processing circuitry may receive or measure a response (e.g., received from the chip 20 based on transmitting the data via the first GPIO port.) For example, when the connection is true or the current GPIO configuration combination is successful, the processing circuitry may receive (e.g., measure, detect) a high analog value response (e.g., high voltage, 3.3V) via the first GPIO port in response to transmitting the data via the first GPIO port. On the other hand, when the connection is false or the current GPIO configuration combination is not successful, the processing circuitry may receive (e.g., measure, detect) a low analog value response (e.g., lowvoltage, 0.7 V) via the first GPIO port in response to transmitting the data via the first GPIO port. As such, based on the received analog value, the processing circuitry may determine whether the current GPIO configuration combination is enabling a successful connection with the chip.

[0073] If the processing circuitry determines the current GPIO configuration combination is enabling a successful connection between the processing circuitry and the chip, at block 306, the processing circuitry may receive data from the chip. In particular, as discussed herein, the processing circuitry may receive the sampling line identification information from the chip that is associated with the sampling line coupled to the monitoring device.

[0074] If the processing circuitry determines that current GPIO configuration combination is not enabling a successful connection between the processing circuitry and the chip, at block 308, the processing circuitry adjusts the current GPIO configuration combination to an additional GPIO configuration combination. In other words, the processing circuitry may reconfigure (e.g., set, change) at least two of the GPIO ports to change the current GPIO configuration combination to a different GPIO configuration combination. For example, the processing circuitry may adjust the second GPIO port to the second configuration of “GND” or a passive input state and the third GPIO port to the third configuration of “H.Z.” or an inactive input state with a relatively high impedance, as shown in Table 1 as Combination No. 2. Furthermore, the method 300 may return to block 302 and the processing circuitry may transmit data via the additional (e.g., changed, different) GPIO configuration combination, which is now the current GPIO configuration combination of the connection authentication system. The method 300 may continue through block 304 to test the current GPIO configuration combination and determine whether the current GPIO configuration combination enables a successful connection with the chip. In particular, in some embodiments, the processing circuitry (e.g., via the detection algorithm) may test each of the GPIO configuration combinations Nos. 1-6 until a successful combination is achieved and data is received from the chip 20 (e.g., block 306).

[0075] FIG. 9 is a schematic diagram of an embodiment of a connection authentication system 400 of the smart capnography monitoring system 10, in accordance with an aspect of the present disclosure. The connection authentication system 400 includes the processing circuitry 24 (e.g., micro-processor, micro-controller) of the monitoring device 12, and the chip20 (e.g., microchip, integrated circuit (IC), electrically erasable programmable read-only memory (EEPROM)) of the connector 18 coupled to the sampling line (e.g., sampling line 14, see FIG. 1). The connection authentication system 400 may be configured to communicatively couple the processing circuitry 24 to the chip 20, such that the smart capnography monitoring system 10 may verify a connection between the processing circuitry 24 and the chip 20 and receive authentication information from the chip 20 (e.g., data, sampling line identification information). In some embodiments, as discussed herein, the connection authentication system 400 may enable identification of the sampling line 14 coupling to the monitoring device 12 based on the authentication information.

[0076] As illustrated in FIG. 9, the connection authentication system 400 includes the processing circuitry 42, a first signal line 402 (e.g., first serial line, one-wire connection, singlewire connection), a second signal line 404 (e.g., second serial line), a general purpose output (GPIO) 406 (e.g., GPIO block, relay), a first switch 408 (e.g., Single Pole, Double Throw (SPDT) switch), a second switch 410, a third switch 412, and a resistor 414 (e.g., pull-up resistor). The connection authentication system 400 also includes a processing circuitry ground connection 416 coupled to the processing circuitry 24, and a power connection 418 (e.g., voltage at common collector (VCC), supply voltage) coupled to the processing circuitry 24. The power connection 416 may supply power to the processing circuitry 24.

[0077] The first signal line 402 may be capable of transmitting and receiving data, as well as transmitting power from the processing circuitry 24 (e.g., to the chip 20 of the connector 18). In particular, as illustrated in FIG. 9, the first signal line 402 may include one or more output nodes 420, wherein each respective output node 420 may be configured to be coupled to a corresponding switch (e.g., an input portion of the switch). For example, the first signal line 402 may include a first signal path 422 coupled to a first node 424. The first node 424 coupled to a second signal path 426 that couples to the first output node 428, and to a third signal path 430. In some embodiments, the first node 424 may also couple to the resister 414. The resistor 414 (e.g., pull-up resistor) may be configured to enable a state (e.g., default state) of the connection authentication system 400 (e.g., the first signal line 402). In particular, the resistor 414 may pull-up the first signal line 402 or cause the state of the first signal line 402 to be a high state (e.g., logic “1”, short pulse). In some embodiments, the resistor 414 may cause a default high state when the processing circuitry 24 is in an inactive state (e.g., open circuit mode, open-collector state, open-drain state, not driving a low state, logic “0”, wide pulse, notpulling the line (e.g., the first signal line 402) down). To this end, the resistor 414 may have a resistance value (e.g., 300 Ohms (Q), 350 , 499 , 550 , between 300-750 ) that enables the high state of the first signal line 402.

[0078] Continuing with reference to FIG. 9, the third signal path 430 is coupled, via a second node 432, to a fourth signal path 434 that couples to the second output node 436 and to a fifth signal path 438, via a third node 440 that couples to the third output node 442. As further discussed herein, the connection authentication system 400 is configured to adjustably couple one or more pins 444 to the processing circuitry 24 (e.g., via the first signal line 402) to verify or enable a successful connection between the monitoring device 12 and the chip 20 (e.g., when a connector 18 is coupled to the monitoring device 12).

[0079] To this end, the connection authentication system 400 includes a first pin 446 (e.g., spring loaded pin, pogo pin), a second pin 448, and a third pin 450. In particular, each of the first, second, and third pin 446, 448, 450 is coupled (e.g., in parallel, in series) to the processing circuitry 24 via the first signal line 402. Furthermore, the processing circuitry 24 is adjustably coupled to the first, second, and third pins 446, 448, 450 via the first signal line 402 (e.g., via the respective first, second, and third switches 408, 410, 412). The processing circuitry 24 is also coupled to the GPO 406 via the second signal line 404. In particular, the first switch 408 adjustably couples the first pin 446 to the first signal line 402 and a first ground connection 452. For example, the first switch 408 may adjustably switch a coupling (e.g., connection, electrical connection) of the first pin 446 to either the first signal line 402 or the first ground connection 452. Furthermore, the second switch 410 adjustably couples the second pin 448 to the first signal line 402 and a second ground connection 454. For example, the second switch 410 may adjustably switch a coupling (e.g., connection, electrical connection) of the second pin 448 to either the first signal line 402 or the second ground connection 454. Additionally, the third switch 412 adjustably couples the third pin 450 to the first signal line 402 and a third ground connection 456. For example, the third switch 412 may adjustably switch a coupling (e.g., connection, electrical connection) of the third pin 450 to either the first signal line 402 or the third ground connection 456.

[0080] The connection authentication system 400 may be configured to adjust (e.g., set, configure, select) a switch state of each of the first, second, and third switch 408, 410, 412 to enable a successful connection (e.g., enable transmission and reception of data) and / orsuccessful transfer of data between the processing circuitry 24 and the chip 20, such as when a connector 18 is coupled to the monitoring device 12. The switch states may include a first switch state, which enables a respective pin (e.g., the first, second, third pin 446, 448, 450) to couple (e.g., electrically couple) to the processing circuitry 24 (e.g., to the respective first, second, third output node 428, 436, 442, via the first signal line 402), and a second switch state, which enables the respective pin to couple to a respective ground connection (e.g., the first, second, third ground connection 452, 454, 456). In particular, the processing circuitry 24 may instruct the GPO 406 to select or set the switch state (e.g., the first switch state or the second switch state) of each of the first, second, and third switch 446, 448, 450.

[0081] In some embodiments, the processing circuitry 24 may instruct the GPO 406 to adjust (e.g., continuously adjust) the switch states of the first, second, and third switch 408, 410, 412 until a successful connection is achieved (e.g., established, determined, sensed, detected, reached). In particular, the processing circuitry 24 may receive (e.g., from the chip 20) an indication of a successful connection in response to a successful combination or configuration of the switch states. For example, in some embodiments, a particular combination or configuration of the switch states of the first, second, and third switch 408, 410, 412 may enable data, sampling line identification information, authentication information, or any combination thereof to be received from the chip 20 (e.g., by the processing circuitry 24). Receiving such data from the chip 20 may be indicative of a verified and / or successful connection (e.g., between the chip 20 and the monitoring device 12).

[0082] In some embodiments, the processing circuitry 24 may drive (e.g., transit, hold, execute) a low state pulse (e.g., logic “0”, wide pulse, reset pulse) for a period of time (e.g., 400 microseconds (ps), 500 ps, 480 ps). The low state may synchronize or reset the connection authentication system 400. When the chip 20 is present and successfully coupled (e.g., via a successful combination or configuration of the switch states) to the processing circuity 24, then the chip 20 may respond to the low state pulse with a presence pulse or logic-low pulse (e.g., logic “0”). In particular, the processing circuitry 24 may detect the presence pulse in response to (e.g., following, after) driving the low state pulse. The presence pulse may indicate a successful connection to the chip 20. The processing circuitry 24 may store (e.g., in memory 26) the successful combination or configuration of the switch states in response to detecting the presence pulse (e.g., indicating successful connection to the chip 20). On the other hand, when the chip 20 is not coupled to the processing circuitry 24 (e.g., not present), no chip (e.g., nodevice) is coupled to the processing circuitry 24, or the chip 20 is coupled to the processing circuitry 24 with an unsuccessful combination or configuration of the switch states, then a high state (e.g., logic “1”, short pulse) is detected by the processing circuitry 24 in response to the low state pulse.

[0083] Additionally or alternatively, in some embodiments, the processing circuitry 24 may drive (e.g., transit, hold, execute) a low state pulse (e.g., logic “0”, wide pulse, reset pulse, discovery response state) for a period of time (e.g., 400 microseconds (ps), 500 ps, 480 ps, 48 ps). The low state may synchronize or reset the connection authentication system 400. Then, the processing circuitry 24 may drive (e.g., transit, hold, execute) a discovery response state (e.g., logic “0”, low state) for a period of time. The discovery response state may request a response from a device and / or chip coupled to the processing circuitry 24, such as the chip 20, for example. When the chip 20 is present and successfully coupled (e.g., via a successful combination or configuration of the switch states) to the processing circuity 24, then the chip 20 may drive (e.g., concurrently drive) a low state (e.g., logic “0”, low state) in response to the discovery response state. The processing circuitry 24 may then sample or detect the low state of the chip 20. The detected low state of the chip during the discovery response state may indicate a successful connection to the chip 20. The processing circuitry 24 may store (e.g., in memory 26) the successful combination or configuration of the switch states in response to detecting the low state of the chip 20 (e.g., indicating successful connection to the chip 20). On the other hand, when the chip 20 is not coupled to the processing circuitry 24 (e.g., not present), no chip (e.g., no device) is coupled to the processing circuitry 24, or the chip 20 is coupled to the processing circuitry 24 with an unsuccessful combination or configuration of the switch states, then no low state is detected by the processing circuitry 24 in response to the discovery response state.

[0084] As such, in some embodiments, the switch states or verified switch states of the first, second, and third switch 408, 410, 412 that enable a successful connection may be based on a respective output (e.g., sensed, detected, determined output connection, via the processing circuitry 24) of the first, second, and third switch 408, 410, 412. For example, an output of each of the first, second, and third switch 408 may be coupled to the respective first, second, and third pin 446, 448, 450, and an input of each of the first, second, and third switch 408 may be adjustably coupled to the first signal line 402 (e.g., to the processing circuitry 24) or to the respective first, second, or third ground connection 452, 454, 456. As such, when a connector18 is coupled to the monitoring device 12, the connection authentication system 400 may receive, sense, or detect (e.g., via the processing circuitry 24) the output of each of the first, second, and third switch 408, 410, 412. In addition, the processing circuitry 24 (e.g., via the GPO 406) may set (e.g., adjust or change) the respective input (e.g., via adjusting the switch state) of each of the first, second, and third switch 408, 410, 412 based on the respective output. In particular, the processing circuitry 24 (e.g., via the GPO 406) may continuously adjust the input of each of the first, second, and third switch 408, 410, 412 (e.g., by setting the switch state) until a verified or successful connection is established. In addition, in some embodiments, the processing circuitry 24 may be configured to not adjust the input (e.g., stop adjusting, remain in the current switch state) at the first, second, and third switch 408, 410, 412 in response to a verified or successful connection. When the connector 18 is uncoupled from the monitoring device 12, and a verified or successful connection is no longer established and / or an indication of the verified or successful connection is no longer present (e.g., data is not being received by the processing circuitry 24), the processing circuitry 24 may resume adjusting the input of the first, second, and third switch 408, 410, 412 until a verified or successful connection (e.g., another successful connection, a subsequent successful connection) is established.

[0085] As an example, Table 2 below includes possible combinations of the inputs for the first, second, and third switches 408, 410, 412. In particular, the default configuration is represented in the first row and includes a first input of “GND” or ground for the first switch 408, a second input of “GND” for the second switch 410, and a third input of “GND” for the third switch 412. In addition, a first trial input configuration is represented in the second row and includes a first trial input of “GND” for the first switch 408, a first trial input of “GND” for the second switch 410, and a first trial input of “Serial Line 1” or coupling to the first signal line 402 for the third switch 412. Furthermore, a second trial input configuration is represented in the third row and includes a second trial input of “GND” for the first switch 408, a second trial input of “Serial Line 1” or coupling to the first signal line 402 for the second switch 410, and a second trial input of “GND” for the third switch 412. A third trial input configuration is represented in the fourth row and includes a third trial input of “GND” for the first switch 408, a third trial input of “Serial Line 1” or coupling to the first signal line 402 for the second switch 410, and a third trial input of “Serial Line 1” for the third switch 412. A fourth trial input configuration is represented in the fifth row and includes a fourth trial input of “Serial Line 1” for the first switch 408, a fourth trial input of “GND” for the second switch 410, and a fourthtrial input of “GND” for the third switch 412. A fifth trial input configuration is represented in the sixth row and includes a fourth trial input of “Serial Line 1” for the first switch 408, a fourth trial input of “GND” for the second switch 410, and a fourth trial input of “Serial Line 1” for the third switch 412. A sixth trial input configuration is represented in the seventh row and includes a sixth trial input of “Serial Line 1” for the first switch 408, a fourth trial input of “Serial Line 1” for the second switch 410, and a fourth trial input of “GND” for the third switch 412.Table 2 - Input Connection Configuration Combinations for First, Second, and Third Switch 408, 410, 412

[0086] It should be appreciated that, in some embodiments, the connection authentication system 400 (e.g., the processing circuitry 24) may include any number of switches coupled to a corresponding any number of pins (e.g., 2, 4, 5, 6, 7, 10). Furthermore, each of the switches may be set to any of the above mentioned configurations or states to enable authentication of the connection between the processing circuitry 24 and the chip 20.

[0087] Returning to FIG. 9, the connection authentication system 400 may couple (e.g., communicatively couple, electrically couple) the processing circuitry 24 to a serial line system458 (e.g., one-wire system, single-wire system) of the chip 20. In the illustrated example, the coupling is via contact with a conductive ring printed circuit board (PCB) 459 of the connector 18. The serial line system 458 includes a serial signal line 460 configured to couple the chip 20 to a first surface 462 of or semi-circle of the PCB 459 (e.g., contact surface, electrical surface, first electrode, positive electrode, pad, printed circuit board (PCB) conductive surface) of the connector 18, and a ground signal line 464 (e.g., a ground connection) configured to couple the chip 20 to a second surface 466 or of semi-circle of the conductive PCB 459 (e.g., negative electrode, second electrode, conductive surface) or semi-circle of the connector 18. The first and second surfaces 462, 466 are separated by a first gap 468 (e.g., isolation gap, air gap, space) and a second gap 470. The first and second surfaces 462, 466, separated by the first and second gaps 468, 470, together form a conductive surface 472 of the connector 18. While the PCB 459 is illustrated as a ring, other implementations are also contemplated. In particular, the connector 18 may electrically couple to a monitoring device via the conductive surface 472. In some embodiments, a shape of the conductive surface 472 may be substantially circular or ring-shaped. For example, the first and second surfaces 462, 466 may each form approximately 160° of the conductive surface 472, and the first and second gaps 468, 470 may each form approximately 20° of the conductive surface 472. Furthermore, the first and second gaps 468, 470 may be situated approximately 180° from each other about the conductive surface 472. In other words, the first gap 468 may be opposite the second gap 470 and the first surface 462 may be opposite the second surface 466 with respect to the circular shape of the conductive surface 472.

[0088] In addition, the connector 18 includes the chip 20. The chip 20 may be disposed or located on the connector 18 on a surface of the ring-shaped PCB 459 opposing the conductive surface 472, and may be coupled to opposing surfaces of both the first and second surfaces 462, 466. That is, the ring-shaped PCB 459 may have a top conductive surface 472 and an opposing bottom surface (not shown) to which the chip 20 is coupled. It should be understood that in some embodiments the connector could be any suitable shape (e.g., oval, square, rectangle, octagonal) and that the conductive surface may be any suitable corresponding shape. In addition, in some embodiments, a size and a shape of the first and second surfaces may be any suitable size and / or shape such that the first and second surfaces facilitate coupling (e.g., electrical coupling) of the chip with the processing circuitry of the monitoring device.

[0089] In addition, it should be appreciated that the pins of the connection authentication system 400 may couple to the conductive surface of the connector in any suitable configuration. In particular, although FIG. 9 illustrates the first pin 446 contacting the first surface 462 and the second and third pins 448, 450 contacting the second surface 466, in other embodiments, the pins may contact the conductive surface in another combinations. For example, the first and second pins 446, 448 may contact the first surface 462 and the third pin 450 may contact the second surface 450, etc. As further discuss herein, a contact position (e.g., electrical contact, electrical connection) between the conductive surface of the connector and the pins may vary due to the connector being physically rotated (e.g., via a user or healthcare professional) when coupling or inserting (e.g., physical coupling, electrical coupling, contact) the connector to / into a port of the monitoring device. As such, the conductive surface of the connector may randomly contact the pins. Thus, a position of contact between the connection authentication system 400 of the monitoring device and the chip may vary.

[0090] In addition, as illustrated in FIG. 9, the serial line system 458 includes a connection element 469 (e.g., diode, opposite-diode) coupled between the serial signal line 460 and the ground signal line 464. The connection element 468 is configured to sink (e.g., direct, redirect) at least a portion of a signal (e.g., current, power) received at the second connection surface 466 from the ground signal line 464 to the serial signal line 460. In this way, in some embodiments, the connection element 469 may protect the chip 20 from receiving power via a negative, unverified, or unsuccessful connection during the connection authentication process.

[0091] As discussed herein, the connection authentication system 400 is configured to automatically verify or adjust a connection between the processing circuitry 24 of the monitoring device 12 and the chip 20 of the connector 18 (e.g., of the sampling line 14). Thus, the connection authentication system 400 enables the monitoring device to receive (e.g., automatically receive) data (e.g., the sampling line identification information) stored on the chip 20 despite a physical or positional variation in the connection (e.g., contact between the conductive surface 472 and the first, second, and third pins 446, 448, 450 of the connection authentication system 400). In other words, as discussed herein, a particular contact position (e.g., electrical contact, electrical connection) between the conductive surface 472 of the connector 18 and the first, second, third pins 446, 448, 450 may vary due to the connector 18 being physically rotated (e.g., via a user or healthcare professional of the smart capnography system 10) when coupling (e.g., physical coupling, electrical coupling, contact) the connector18 to a port of the monitoring device 12. As such, each of the first and second surfaces 462, 466 of the connector 18 may randomly contact the first, second, or third pin 446, 448, 450 (e.g., randomly coupled to the first, second, or third output nodes 428, 436, 442). Thus, a point or position of contact between the connection authentication system 400 of the monitoring device 12 and the serial line system 458 of the chip 20 may vary.

[0092] With the foregoing in mind, FIG. 10 is a flow diagram of an embodiment of a method 600 of authenticating a connection between the processing circuitry of the monitoring device and the chip of the connector via the connection authentication system, in accordance with an aspect of the present disclosure. The method 600 includes various computer- implemented steps represented by blocks that may be performed by the processor-based device (e.g., the monitoring device 12, the processing circuitry 24) described with respect to FIGS. 1 and 9. It should also be noted that the method 600 may be performed by other suitable processor-based devices (e.g., cloud server, webpage, tablet, mobile device, etc.) that may perform the methods described herein. For example, certain steps or portions of the method 600 may be performed by separate systems or devices, such as one or more processors, processor-based devices, and / or computers. Although the following description of the method 600 is described in a particular order, it should be noted that the method 600 is not limited to the depicted order; and, instead, the method 600 may be performed in any suitable order. Further, blocks / steps may be omitted and / or added to the method 600.

[0093] The connection authentication system (e.g., via the processing circuitry) may test (e.g., run, execute) multiple combinations of input configurations to determine (e.g., detect) a verified or successful combination (e.g., combination of switch states, input configuration), and thus determine a successful connection between the processing circuitry and the chip. In particular, a successful connection may be a connection that enables the processing circuitry to transmit and receive data to and from the chip, and that enables the chip (e.g., a capacitor of the chip) to receive power (e.g., a power supply) from the processing circuitry. As such, at block 602, the processing circuitry transmits data via a current input configuration combination. In particular, in some embodiments, the processing circuitry may attempt to establish a connection with the chip by transmitting data via a transmission or communication protocol associated with the chip. For example, the first, second, and third switches may be set to or be initially in (e.g., via the processing circuitry instructing the GPO) the first trial input configuration as shown in Table 2. In particular, the first switch may be set to the second switch state or be coupled tothe first ground connection. The second switch may be set to the second switch state or be coupled to the second ground connection. In addition, the third switch may be set to the first switch state or be coupled to the processing circuitry via the first signal line. In such embodiments, the processing circuitry may transmit data via the third pin (e.g., via the third switch). It should be understood that the processing circuitry may utilizes any of the input configurations of Table 2 as an initial input configuration, and transmit the data via the respective pin or pins that is set to the “Serial Line 1” input.

[0094] At block 604, the processing circuitry may receive an indication of whether the current input configuration is a verified or successful configuration. In some embodiments, the processing circuitry may receive an indication of whether the connection between the processing circuitry and the chip is correct (e.g., true, positive connection) or false (e.g., negative connection). For example, in some embodiments, the processing circuitry may receive an indication that the connection is true or an indication that the connection is false in response to transmitting data via the current input configuration. In particular, as in the instant example, the processing circuitry may receive or measure a response (e.g., received from the chip 20) based on transmitting the data via the first trial input configuration. For example, when the connection is true or the current input configuration is successful, the processing circuitry may receive (e.g., measure, detect) a zero, off, or down response (e.g., from the chip). On the other hand, when the connection is false or the current input configuration is not successful, the processing circuitry may not receive (e.g., measure, detect) zero, off, or down response (e.g., from the chip) in response to transmitting the data via the first trial input configuration. As such, based on the received indication in response to transmitting data via a current input configuration, the processing circuitry may determine whether the current input configuration is enabling a verified or successful connection with the chip.

[0095] If the current input configuration combination is enabling a successful connection between the processing circuitry and the chip, at block 606, the processing circuitry may receive data from the chip. In particular, as discussed herein, the processing circuitry may receive the sampling line identification information from the chip that is associated with the sampling line coupled to the monitoring device. In addition, in some embodiments, the processing circuitry may cause or instruct the GPO to remain in (e.g., not adjust, stop adjusting) the current input configuration in response to the indication of a verified or successful connection to the chip.

[0096] If the current input configuration is not enabling a verified or successful connection between the processing circuitry and the chip, at block 608, the processing circuitry adjusts the current input configuration to an additional input configuration. In particular, at discussed herein, the processing circuitry may cause or instruct the GPO to adjust (e.g., set, change) the current input configuration to an additional (e.g., successive, sequential) input configuration in response to receiving an indication of an unverified or unsuccessful connection. Additionally or alternatively, in some embodiments, the processing circuitry may instruct the GPO to adjust or change the current input configuration to an additional input configuration in response to not receiving the indication of a verified or successful connection. In particular, the processing circuitry may be configured or programmed to include a predetermined period of time (e.g., 10 microseconds (ps), 20 ps, 100 ps, 2 milliseconds (ms), between 10 ps and 10 ms) between adjusting or changing the current input configuration to an additional input configuration. In such embodiments, in absence of an indication of a successful connection, the processing circuitry may be configured to continuously adjust the input configuration of the switches until an indication of a verified or successful connection is received.

[0097] Continuing with the present example, the processing circuitry may cause the GPO to set the switches to the second trial input configuration in response to receiving an indication of an unverified or unsuccessful connection, or in response to not receiving a verified or successful connection (e.g., within the predetermined period of time). In particular, the first switch may be set to or remain in the second switch state or be coupled to the first ground connection. The second switch may be set to the first switch state or be coupled to the processing circuitry via the first signal line. In addition, the third switch may be set to the second switch state or be coupled to the third ground connection. In such embodiments, the processing circuitry may transmit data via the second pin (e.g., via the second switch). It should be understood that the processing circuitry may utilizes any of the input configurations of Table 2 as an additional input configuration, and transmit the data via the respective pin or pins that is set to the “Serial Line 1” input.

[0098] Furthermore, the method 600 may return to block 602 and the processing circuitry may transmit data via the additional (e.g., changed, different) input configuration, which is now the current input configuration of the connection authentication system. The method 600 may continue through block 604 for an indication of whether the current input configuration enables a successful connection with the chip. In particular, in some embodiments, the processingcircuitry may cause or instruct the GPO to test each of the input configurations Nos. r'-6lhtrial input configurations until a successful combination is achieved and data is received from the chip 20 (e.g., block 606).

[0099] It should be understood that various aspects disclosed herein may be combined in different combinations than the combinations specifically presented in the description and accompanying drawings. It should also be understood that, depending on the example, certain acts or events of any of the processes or methods described herein may be performed in a different sequence, may be added, merged, or left out altogether (e.g., all described acts or events may not be necessary to carry out the techniques). In addition, while certain aspects of this disclosure are described as being performed by a single module or unit for purposes of clarity, it should be understood that the techniques of this disclosure may be performed by a combination of units or modules associated with, for example, a medical device.

[0100] In one or more examples, the described techniques may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored as one or more instructions or code on a computer-readable medium and executed by a hardware-based processing unit. Computer-readable media may include non- transitory computer-readable media, which corresponds to a tangible medium such as data storage media (e.g., RAM, ROM, EEPROM, flash memory, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer).

[0101] Instructions may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors, application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Accordingly, the term “processor” as used herein may refer to any of the foregoing structure or any other physical structure suitable for implementation of the described techniques. Also, the techniques could be fully implemented in one or more circuits or logic elements.

[0102] The following examples are illustrative of the techniques described herein.

[0103] Example 1. A capnography monitoring system, comprising: a sensor for sensing a physiological parameter from a patient sample, wherein the patient sample is transferred to thesensor via a sampling line; a processing circuitry communicatively coupled to the sensor; and a memory storing computer-readable instructions that when executed by the processing circuitry, cause the processing circuitry to perform operations comprising: receiving first data associated with the physiological parameter of the patient sample from the sensor; receiving sampling line identification information of the sampling line; generating second data associated with the physiological parameter of the patient sample by adjusting the first data based on the sampling line identification information; and causing a monitor to display the second data associated with the physiological parameter of the patient sample.

[0104] Example 2. The capnography monitoring system of Example 1, wherein the processing circuitry is configured to receive one or more signal correction factors based on the sampling line identification information.

[0105] Example 3. The capnography monitoring system of Example 2, wherein the processing circuitry is configured to receive the one or more signal correction factors by inputting the sampling line identification information into an algorithm or machine-learning model.

[0106] Example 4. The capnography monitoring system of Example 1, wherein the sampling line identification information comprises an expiration of use of the sampling line, and wherein the processing circuitry is configured to track a time of use of the sampling line and activate an alarm or display indicator based on the expiration of use of the sampling line.

[0107] Example 5. The capnography monitoring system of Example 1, comprising: a connector port for receiving a connector of the sampling line, wherein the sampling line transmits the patient sample from a patient towards the sensor, and wherein the connector comprises a chip for storing the sampling line identification information.

[0108] Example 6. The capnography monitoring system of Example 5, wherein the processing circuitry is configured to communicatively couple to the chip via a set of input / output (I / O) ports, and wherein the set of I / O ports are configured to be set to one or more configuration states.

[0109] Example 7. The capnography monitoring system of Example 6, wherein each of the I / O ports of the set of I / O ports comprises a general purpose input / output port, and wherein the processing circuitry is communicatively coupled to the chip via a one-wire connection.

[0110] Example 8. The capnography monitoring system of Example 6, wherein the processing circuitry is configured to: set the set of I / O ports to a first configuration state of the one or more configuration states; transmit data via the set of I / O ports to the chip; receive anindication of a successful configuration state via the set of I / O ports; and receive the sampling line identification information from the chip.

[0111] Example 9. The capnography monitoring system of Example 8, wherein the processing circuitry is configured to: receive an additional indication of an unsuccessful configuration state via the set of I / O ports; and set the set of VO ports to a second configuration state of the one or more configuration states based on the additional indication.

[0112] Example 10. The capnography monitoring system of Example 9, wherein the indication of the successful configuration state comprises a high analog value response, and the additional indication of the unsuccessful configuration state comprises a low analog value response that is a lower voltage than the high analog value response.

[0113] Example 11. The capnography monitoring system of Example 5, comprising a set of switches, wherein each switch of the set of switches is configured to communicatively couple the processing circuitry to the chip based on a first switch state or a second switch state, wherein the processing circuitry is configured to cause one or more switches of the set of switches to be set to the first switch state or the second switch state based on an input configuration.

[0114] Example 12. The capnography monitoring system of Example 11, wherein the first switch state is configured to couple an input of a respective switch to the processing circuitry and the second switch state is configured to couple the input of the respective switch to a ground connection.

[0115] Example 13. The capnography monitoring system of Example 11, wherein the processing circuitry is configured to communicatively couple to the chip via one or more pins, wherein a first pin of the one or more pins is coupled to an output of a first switch of the set of switches, and wherein the processing circuitry is configured to: cause the first switch to be set to the first switch state; transmit data via the first pin; receive an indication of a successful input configuration via the first pin; and receive the sampling line identification information from the chip.

[0116] Example 14. The capnography monitoring system of Example 13, wherein the processing circuitry is configured to: receive an additional indication of an unsuccessful input configuration; and cause the first switch to be set to the second switch state based on the additional indication.

[0117] Example 15. The capnography monitoring system of Example 1, wherein the sampling line identification information comprises one or more pneumatic characteristics associated with the sampling line, a length of the sampling line, a diameter of the sampling line,a type of sampling line, a filter type associated with the sampling line, or any combination thereof.

[0118] Example 16. A method for capnography monitoring, comprising: receiving, via processing circuitry of a monitoring device, first data associated with a capnography measurement of a patient breath sample, wherein the first data is received from a sensor; receiving, via the processing circuitry, sampling line identification information associated with a sampling line for transmitting the patient breath sample to the sensor; generating, via the processing circuitry, second data associated with the capnography measurement of the patient breath sample by adjusting the first data based on the sampling line identification information; and displaying, via a monitor of the monitoring device, the second data associated with the capnography measurement of the patient breath sample.

[0119] Example 17. The method of Example 16, comprising receiving, via the processing circuitry, one or more signal correction factors based on the sampling line identification information, wherein the one or more signal correction factors are determined, via the processing circuitry, based on inputting the sampling line identification information into an algorithm.

[0120] Example 18. The method of Example 16, wherein the sampling line identification information is stored on a chip associated with the sampling line, and wherein the processing circuitry is configured to communicatively couple to the chip via a set of input / output (I / O) ports, the method further comprising: setting the set of I / O ports to a first configuration state of one or more configuration states; transmitting a signal via the set of I / O ports to the chip; receiving a response indicating whether a connection between the processing circuitry and the chip is successful based on the signal; receiving the sampling line identification information from the chip based on the response indicating a successful connection; and setting the set of I / O ports to a second configuration state of the one or more configuration states based on the response indicating an unsuccessful connection.

[0121] Example 19. The method of Example 16, wherein the sampling line identification information is stored on a chip associated with the sampling line, and wherein the processing circuitry is configured to communicatively couple to the chip via a set of switches, the method further comprising: setting the set of switches to a first input configuration of one or more input configurations; transmitting a signal via the set of switches to the chip; receiving a response indicating whether a connection between the processing circuitry and the chip is successful based on the signal; receiving the sampling line identification information from the chip basedon the response indicating a successful connection; and setting the set of switches to a second input configuration of the one or more input configurations based on the response indicating an unsuccessful connection.

[0122] Example 20. The method of Example 19, wherein each input configuration of the one or more input configurations comprises an indication of a first switch state or a second switch state associated with each switch of the set of switches, wherein the first switch state is configured to couple a pin associated with a respective switch to the processing circuitry and the second switch state is configured to couple the pin associated with the respective switch to a ground connection.

[0123] Example 21. The method of Example 16, wherein the sampling line identification information comprises one or more pneumatic characteristics associated with the sampling line, a length of the sampling line, a diameter of the sampling line, a type of sampling line, a filter type associated with the sampling line, or any combination thereof.

[0124] Example 22. The method of Example 21, wherein the filter type is a short duration filter type, and comprising monitoring a connection time of the sampling line and activating a notification when the connection time exceeds a use time associated with the short duration filter type.

Claims

WHAT IS CLAIMED IS:

1. A capnography monitoring system (10), comprising: a sensor (34) for sensing a physiological parameter from a patient sample, wherein the patient sample is transferred to the sensor (34) via a sampling line (14); a processing circuitry (24) communicatively coupled to the sensor (34); and a memory (26) storing computer-readable instructions that when executed by the processing circuitry (24), cause the processing circuitry (24) to perform operations comprising: receiving first data associated with the physiological parameter of the patient sample from the sensor (34); receiving sampling line identification information of the sampling line (14); generating second data associated with the physiological parameter of the patient sample by adjusting the first data based on the sampling line identification information; and causing a monitor (12) to display the second data associated with the physiological parameter of the patient sample.

2. The capnography monitoring system of claim 1 , wherein the processing circuitry is configured to receive one or more signal correction factors based on the sampling line identification information, optionally wherein the one or more signal correction factors are received by providing the sampling line identification information to an algorithm or machinelearning model.

3. The capnography monitoring system of claim 1, wherein the sampling line identification information comprises an expiration of use of the sampling line, and wherein the processing circuitry is configured to track a time of use of the sampling line and activate an alarm or display indicator based on the expiration of use of the sampling line.

4. The capnography monitoring system (10) of claim 1, comprising: a connector (18) of the sampling line for coupling to a connector port, wherein the sampling line transmits the patient sample from a patient (16) towards the sensor, and wherein the connector (18) comprises a chip (20) for storing the sampling line identification information.

5. The capnography monitoring system of claim 4, wherein the processing circuitry is configured to communicatively couple to the chip via a set of input / output (I / O) ports (30), and wherein the set of I / O ports (30) are configured to be set to one or more configuration states, optionally wherein each of the I / O ports of the set of I / O ports comprises a general purpose input / output port (252), and wherein the processing circuitry is communicatively coupled to the chip via a one-wire connection (282).

6. The capnography monitoring system of claim 5, wherein the processing circuitry is configured to: set the set of I / O ports to a first configuration state of the one or more configuration states; transmit data via the set of I / O ports to the chip; receive an indication of a successful configuration state via the set of I / O ports, optionally wherein the indication of the successful configuration state comprises a high analog value response; and receive the sampling line identification information from the chip.

7. The capnography monitoring system of claim 6, wherein the processing circuitry is configured to: receive an additional indication of an unsuccessful configuration state via the set of I / O ports, optionally wherein the additional indication of the unsuccessful configuration state comprises a low analog value response that is a lower voltage than the high analog value response; and set the set of I / O ports to a second configuration state of the one or more configuration states based on the additional indication.

8. The capnography monitoring system of claims 4-7, comprising one or more switches (408), wherein each switch of the one or more switches (408) is configured to communicatively couple the processing circuitry to the chip based on a first switch state or a second switch state, wherein the processing circuitry is configured to cause the one or more switches (408) to be set to the first switch state or the second switch state based on an input configuration, optionally wherein the first switch state is configured to couple an input of arespective switch to the processing circuitry and the second switch state is configured to couple the input of the respective switch to a ground connection (452).

9. The capnography monitoring system of claim 8, wherein the processing circuitry is configured to communicatively couple to the chip via one or more pins (444), wherein a first pin (446) of the one or more pins (444) is coupled to an output of a first switch (408) of the one or more switches, and wherein the processing circuitry is configured to: cause the first switch (408) to be set to the first switch state; transmit data via the first pin (446); receive an indication of a successful input configuration via the first pin (446); and receive the sampling line identification information from the chip.

10. The capnography monitoring system of claim 9, wherein the processing circuitry is configured to: receive an additional indication of an unsuccessful input configuration; and cause the first switch to be set to the second switch state based on the additional indication.

11. The capnography monitoring system of claim 1, wherein the sampling line identification information comprises one or more pneumatic characteristics associated with the sampling line, a length of the sampling line, a diameter of the sampling line, a type of sampling line, a filter type associated with the sampling line, or any combination thereof.

12. A method for capnography monitoring, comprising: receiving, via processing circuitry (24) of a monitoring device (12), first data associated with a capnography measurement of a patient breath sample, wherein the first data is received from a sensor (34); receiving, via the processing circuitry (24), sampling line identification information associated with a sampling line (14) for transmitting the patient breath sample to the sensor (34); generating, via the processing circuitry (24), second data associated with the capnography measurement of the patient breath sample by adjusting the first data based on the sampling line identification information; anddisplaying, via a monitor of the monitoring device (12), the second data associated with the capnography measurement of the patient breath sample.

13. The method of claim 12, comprising receiving, via the processing circuitry, one or more signal correction factors based on the sampling line identification information, wherein the one or more signal correction factors are determined, via the processing circuitry, based on inputting the sampling line identification information into an algorithm.

14. The method of claim 12 or 13, wherein the sampling line identification information is stored on a chip (20) associated with the sampling line, and wherein the processing circuitry is configured to communicatively couple to the chip via a set of input / output (I / O) ports (30), the method further comprising: setting the set of I / O ports (30) to a first configuration state of one or more configuration states; transmitting a signal via the set of I / O ports (30) to the chip (20); receiving a response indicating whether a connection between the processing circuitry and the chip (20) is successful based on the signal; receiving the sampling line identification information from the chip (20) based on the response indicating a successful connection; and setting the set of I / O ports (30) to a second configuration state of the one or more configuration states based on the response indicating an unsuccessful connection.

15. The method of claim 14, wherein the sampling line identification information is stored on a chip (20) associated with the sampling line, and wherein the processing circuitry is configured to communicatively couple to the chip (20) via one or more switches (408), the method further comprising: setting the one or more switches (408) to a first input configuration of one or more input configurations; transmitting a signal via the one or more switches (408) to the chip (20); receiving a response indicating whether a connection between the processing circuitry and the chip (20) is successful based on the signal; receiving the sampling line identification information from the chip (20) based on the response indicating a successful connection; andsetting the one or more switches (408) to a second input configuration of the one or more input configurations based on the response indicating an unsuccessful connection, optionally wherein each input configuration of the one or more input configurations comprises an indication of a first switch state or a second switch state associated with each switch of the one or more switches, wherein the first switch state is configured to couple a pin (444) associated with a respective switch to the processing circuitry and the second switch state is configured to couple the pin (444) associated with the respective switch to a ground connection (452).

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