Performing measurements using sensors in medical device systems

Abstract

The present disclosure relates to devices, systems, and techniques for performing patient parameter measurements. In some examples, a medical device system includes an optical sensor configured to measure ambient light and a tissue oxygen saturation parameter; and a processing circuit system configured to determine that a current measurement of the tissue oxygen saturation parameter is prompted and to control the optical sensor to perform an ambient light measurement associated with the current measurement of the tissue oxygen saturation parameter. The processing circuit system is further configured to determine, based on the ambient light measurement, at least one of: whether to control the optical sensor to perform the current measurement of the tissue oxygen saturation parameter, when to control the optical sensor to perform the current measurement of the tissue oxygen saturation parameter, or whether to include the current measurement of the tissue oxygen saturation parameter in a trend of the tissue oxygen saturation parameter.

Description

Technical Field

[0001] The present disclosure relates generally to medical device systems and, more particularly, to medical device systems configured to sense one or more parameters. Background Art

[0002] Some types of medical devices can be used to monitor one or more physiological parameters of a patient. Such medical devices may include, or be part of, a system that includes a sensor that detects signals associated with such physiological parameters. Values ​​determined based on such signals can be used to help detect changes in a patient's condition, assess the efficacy of a therapy, or generally evaluate the patient's health. For example, a medical device that monitors a physiological parameter may analyze the values ​​associated with such physiological parameters to identify or monitor a patient's condition. Summary of the Invention

[0003] In general, the present disclosure relates to devices, systems, and techniques for performing measurements of at least one patient parameter to determine or monitor one or more patient conditions. For example, the present disclosure describes techniques for performing tissue oxygen saturation (StO2) measurements, pulse oximetry (SpO2) measurements, or any combination of other parameter measurements to determine whether a patient is experiencing or is about to experience an exacerbation of a patient condition such as heart failure, sleep apnea, or chronic obstructive pulmonary disease (COPD). In some instances, the present disclosure describes techniques for performing parameter measurements to track a patient's condition after an exacerbation of the condition when the patient's condition returns to a stable state. In addition to measuring oxygen saturation levels, in some instances, a medical device can use various sensors and electrodes to measure one or more of the patient's motion level, patient posture, electrocardiogram (ECG) signals, tissue impedance signals, Doppler blood flow signals, the amount of ambient light present in the target tissue, the quality of an optical sensor test signal, the temperature of the target tissue, respiratory rate, heart rate, and heart rate variability. Such measurements performed by the medical device can generate data that the processing circuitry can analyze to evaluate one or more patient conditions. Data corresponding to such parameter measurements obtained by the medical device may be analyzed by processing circuitry to determine whether the medical device should perform or withhold certain parameter measurements, such as oxygen saturation measurements.

[0004] In some instances, the present disclosure describes techniques for performing a set of assessments using a medical device, wherein each assessment in the set represents a decision on whether to perform a parameter measurement using the medical device or whether to classify the parameter measurement as high quality or low quality. In some cases, the medical device is powered by a power source with limited capacity (e.g., a battery). In some cases, the medical device is powered by a power source with self-replenishing capabilities (e.g., an energy harvester). Each parameter measurement performed by the medical device consumes a certain amount of energy (e.g., current) from the power source. In some instances, it may be beneficial to maintain the capacity of the power source by limiting the amount of energy consumed by the components of the medical device from the power source. Therefore, it may be useful to determine whether the parameter measurement will produce high-quality data before performing the parameter measurement. In some cases, the medical device will only draw energy from the power source to perform the parameter measurement if the parameter measurement produces data useful for determining a patient condition such as heart failure, sleep apnea, or COPD. In some cases, the data from the parameter measurement can be divided into high-quality and low-quality groups, wherein the high-quality data is analyzed to identify or monitor the patient condition while excluding the low-quality data. In this case, the quality of the analysis can be improved by excluding the low-quality data.

[0005] Example parameter measurements may include StO2 measurements. StO2 may be a weighted average of arterial oxygen saturation (SaO2) and venous oxygen saturation (SvO2), with SvO2 being weighted higher than SaO2. If StO2 remains stable over a period of time, this may indicate that SaO2 is also stable. However, if StO2 decreases, the processing circuitry may, in some cases, output instructions to measure SaO2 to determine whether the decrease in StO2 corresponds to a decrease in SaO2 and whether the decrease in SaO2 exceeds a clinically accepted threshold indicating a significant change in patient status. In some instances, to obtain data indicative of SaO2, the processing circuitry may output instructions to the medical device to perform an SpO2 measurement. In other instances, to obtain data indicative of SaO2, the processing circuitry may output instructions to an external pulse oximetry device to perform an SpO2 measurement. SpO2 measurements performed by a medical device may consume significantly more energy than StO2 measurements. Therefore, when it is determined that StO2 trends need to be confirmed and interpreted, instructing the medical device to perform an SpO2 measurement may be beneficial.

[0006] The techniques disclosed herein may provide one or more advantages. For example, a medical device may be configured to perform a set of determinations to determine whether a parameter measurement will produce reliable data for tracking a patient's condition. In some examples, for each assessment in the set, the medical device measures the amount of ambient light present in the target tissue and measures the patient's motion level based on an accelerometer signal. If the amount of ambient light and the patient's motion level are below a threshold ambient amount and a threshold motion level, respectively, the processing circuitry may instruct the medical device to perform the parameter measurement and / or may determine that the parameter measurement should be retained for further processing. Thus, in some cases, by monitoring ambient light and patient motion, if the amount of ambient light or the patient's motion level is high enough to compromise the parameter measurement, the processing circuitry may prevent the medical device from performing the parameter measurement, thereby preventing the medical device from drawing energy from a power source to perform a measurement that would produce inadequate data and / or improving the quality of the data used to track the patient's condition. Additionally, the processing circuitry may reduce the amount of energy consumed by the medical device by limiting the number of SpO2 measurements performed by the medical device based on the stability of the StO2 measurement. In some examples, this approach may ensure that the medical device waits for periods of low light and motion to perform reliable measurements.

[0007] In some examples, a medical device system includes an optical sensor configured to measure ambient light and a tissue oxygen saturation parameter. Additionally, the medical device system includes processing circuitry configured to determine that a current measurement of the tissue oxygen saturation parameter is prompted and to control the optical sensor to perform an ambient light measurement associated with the current measurement of the tissue oxygen saturation parameter. The processing circuitry is further configured to determine, based on the ambient light measurement, at least one of: whether to control the optical sensor to perform the current measurement of the tissue oxygen saturation parameter, when to control the optical sensor to perform the current measurement of the tissue oxygen saturation parameter, or whether to include the current measurement of the tissue oxygen saturation parameter in a trend of the tissue oxygen saturation parameter.

[0008] In some examples, a method includes: measuring ambient light and a tissue oxygen saturation parameter using an optical sensor of a medical device system; determining, using processing circuitry of the medical device system, that a current measurement of the tissue oxygen saturation parameter is prompted; and controlling the optical sensor to perform an ambient light measurement associated with the current measurement of the tissue oxygen saturation parameter. Based on the ambient light measurement, the method further includes performing at least one of: determining whether to control the optical sensor to perform the current measurement of the tissue oxygen saturation parameter; determining when to control the optical sensor to perform the current measurement of the tissue oxygen saturation parameter; or determining whether to include the current measurement of the tissue oxygen saturation parameter in a trend of the tissue oxygen saturation parameter.

[0009] In some examples, a non-transitory computer-readable medium stores instructions for causing a processing circuit system to perform a method comprising: measuring ambient light and a tissue oxygen saturation parameter using an optical sensor of a medical device system; determining, using the processing circuit system of the medical device system, that a current measurement of the tissue oxygen saturation parameter is prompted; and controlling the optical sensor to perform an ambient light measurement associated with the current measurement of the tissue oxygen saturation parameter. Based on the ambient light measurement, the method further comprises performing at least one of: determining whether to control the optical sensor to perform the current measurement of the tissue oxygen saturation parameter; determining when to control the optical sensor to perform the current measurement of the tissue oxygen saturation parameter; or determining whether to include the current measurement of the tissue oxygen saturation parameter in a trend of the tissue oxygen saturation parameter.

[0010] This summary is intended to provide an overview of the subject matter described in this disclosure. It is not intended to be an exclusive or exhaustive explanation of the systems, devices, and methods described in detail in the following figures and the specification. Further details of one or more embodiments of the present disclosure are set forth in the following figures and the specification. Additional features, objects, and advantages will become apparent from the description and drawings, as well as from the claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 is a conceptual diagram illustrating an example of a medical device system in conjunction with a patient in accordance with one or more techniques described herein.

[0012] Figure 2 is a demonstration of one or more techniques described herein Figure 1 Conceptual diagram of an example configuration of an IMD of a medical device system.

[0013] Figure 3 is a demonstration of one or more techniques described herein Figure 1 and Figure 2 Functional block diagram of an example configuration of an IMD.

[0014] Figure 4A and Figure 4B is to demonstrate that one or more techniques described herein can be substantially similar to Figure 1-3 Block diagrams of two additional example IMDs that may include one or more additional features.

[0015] Figure 5 is a demonstration of one or more techniques according to the present disclosure Figure 1 A block diagram of an example configuration of components of an external device.

[0016] Figure 6is a block diagram illustrating an example system including an access point, a network, an external computing device such as a server, and one or more other computing devices that can be coupled to the network according to one or more techniques described herein. Figure 1 -4 IMD, sensing devices and external devices.

[0017] Figure 7 is a flow diagram illustrating example operations for performing parameter measurements in accordance with one or more techniques of this disclosure.

[0018] Figure 8 is a flow chart illustrating another example operation for performing parameter measurement in accordance with one or more techniques of this disclosure.

[0019] Figure 9 is a method for demonstrating the use of one or more techniques described herein. Figure 1 Flowchart of example operations of an implantable medical device according to claim 1, wherein the implantable medical device may perform tissue oxygen saturation measurements.

[0020] Figure 10 is a flow diagram illustrating example operations for analyzing tissue oxygen saturation values ​​in accordance with one or more techniques of this disclosure.

[0021] Figure 11 is a graph showing a hemoglobin saturation / oxygen partial pressure graph according to one or more techniques of the present disclosure.

[0022] Like reference numerals refer to like elements throughout the specification and drawings. DETAILED DESCRIPTION

[0023] The present disclosure describes techniques for performing patient parameter measurements. For example, a processing circuit system may perform an assessment to determine whether the processing circuit system instructs a device to perform a primary parameter measurement associated with a patient. To perform the assessment, the processing circuit system may output instructions to an implantable medical device (IMD) that cause the IMD to perform a set of secondary parameter measurements. Based on data associated with the set of secondary parameter measurements, the processing circuit system may determine whether to instruct the IMD to perform the primary measurement. In some cases, the set of secondary parameter measurements may consume less energy than the primary parameter measurements. Additionally, in some cases, the data associated with the set of secondary parameter measurements may indicate whether the primary parameter measurement will produce high-quality data for identifying or monitoring patient conditions such as heart failure, sleep apnea, or chronic obstructive pulmonary disease (COPD). In this way, by instructing the IMD to perform the set of secondary parameter measurements, the processing circuit system can prevent the IMD from expending energy to obtain insufficient data or identifying data points that may have been overlooked during analysis. The techniques of the present disclosure are not limited to implantable devices or medical devices. The techniques may be used to perform an assessment to determine whether to instruct any device or combination of devices to perform parameter measurements. As used herein, the adjectives "primary" and "secondary" are not intended to indicate an order or preference between groups, but are merely used to distinguish between the groups.

[0024] In some instances, the primary parameter measurement includes tissue oxygen saturation (StO2) measurement. In some instances, StO2 can represent a weighted average between arterial oxygen saturation (SaO2) and venous oxygen saturation (SvO2). In some instances, the primary parameter measurement includes pulse oximetry (SpO2) measurement. In some cases, SpO2 can represent an approximate value of SaO2. Oxygen saturation (e.g., StO2, SaO2, SvO2, and SpO2) trends can indicate one or more patient conditions, such as heart failure, sleep apnea, or COPD. For example, a steady decrease in StO2 values ​​over a period of time can indicate an increased risk of worsening heart failure in the patient. Thus, the IMD can perform several StO2 measurements over a period of time (e.g., hours, days, weeks, or months), and the processing circuit system can use the data from the StO2 measurements to identify trends in the StO2 values. Based on the identified trends, in some cases, the processing circuit system can identify medical conditions present in the patient or monitor conditions known to be present in the patient.

[0025] To perform StO2 measurements, an IMD may employ an optical sensor. In some cases, the optical sensor may include two or more light emitters and one or more light detectors. During a corresponding StO2 measurement, the light emitters may output light comprising a first set of frequency components toward a tissue region near the IMD. The one or more light detectors may sense the light comprising a second set of frequency components. The processing circuitry is configured to compare the first set of frequency components with the second set of frequency components to identify an StO2 value corresponding to the corresponding StO2 measurement, wherein the StO2 value represents a ratio of oxygen-saturated hemoglobin located in the tissue region to the total amount of hemoglobin located in the tissue region.

[0026] In some cases, the light emitter of the optical sensor may consume significantly more energy than the one or more light detectors of the optical sensor. Additionally, the IMD may be powered by a power source (e.g., a battery) that is equipped with a finite amount of charge. For these reasons, among other reasons, it may be beneficial to limit the amount of time that the light emitter is activated, thereby limiting the number of StO2 measurements performed by the IMD. As discussed above, the techniques of the present disclosure may enable a processing circuit system to determine whether a StO2 measurement performed at a particular time would result in a high-quality StO2 value (e.g., a low level of noise present in the StO2 value). In other words, the processing circuit system may be configured to direct the IMD to perform a set of secondary parameter measurements, wherein the set of secondary parameter measurements results in a set of secondary parameter values ​​that the processing circuit system may use to perform an evaluation to determine whether to instruct the IMD to perform a primary parameter measurement (e.g., a StO2 measurement).

[0027] In some instances, the set of secondary parameter measurements includes motion level measurements and ambient light measurements. To perform the motion level measurement, the IMD can use a motion sensor, such as an accelerometer, to sense data indicating the patient's motion level. For example, the motion sensor can measure the acceleration value of the IMD over a period of time. In some instances, the acceleration value includes three acceleration components (e.g., x-axis acceleration, y-axis acceleration, and z-axis acceleration). A relatively high amount of acceleration can indicate that the patient is performing physical activity, such as jogging, walking, or exercising, or is performing other forms of exercise. In some cases, motion may introduce noise into measurements performed using optical sensors (e.g., StO2 measurements), making the measurements unreliable. In this way, the processing circuit system can compare the motion level corresponding to the motion level measurement with a threshold motion level. If the motion level is greater than or equal to the threshold motion level, the processing circuit system can determine not to output instructions directing the IMD to perform StO2 measurements.

[0028] To perform ambient light measurements, an IMD may use an optical sensor, and more specifically, one or more photodetectors of the optical sensor, to obtain data indicating the amount of ambient light present in the tissue region near the IMD. Because StO2 measurements may involve emitting light using the optical sensor's light emitter and sensing the light using one or more photodetectors, ambient light may introduce noise into the light sensed by the one or more photodetectors, and thus into the StO2 value determined by the StO2 measurement. For example, ambient light can "confound" StO2 data by making a particular StO2 measurement appear as if the patient's oxygen level is changing, even if the apparent change is due to ambient light rather than a worsening of the patient's condition. Furthermore, in some instances, ambient light can "saturate" the optical sensor's photodetectors, causing the optical sensor's electrical output to reach a maximum electrical output level, rendering the optical sensor unable to provide the data necessary to accurately measure StO2 levels. Therefore, it may be beneficial to avoid performing StO2 measurements in the presence of significant ambient light in the tissue region surrounding the IMD, or to exclude StO2 measurements performed in the presence of significant ambient light from analysis. In this manner, the processing circuitry may compare the amount of ambient light corresponding to the ambient light measurement to a first threshold amount of ambient light. If the amount of ambient light is greater than or equal to the first threshold amount of ambient light, the processing circuitry may determine not to output instructions directing the IMD to perform an StO2 measurement. Additionally, in some examples, if the amount of ambient light is greater than or equal to the second threshold amount of ambient light and less than the first threshold amount of ambient light, the processing circuitry or the IMD may subtract the ambient light from the data corresponding to the StO2 measurement.

[0029] In some examples, the set of secondary parameter measurements includes a posture measurement. Based on the signal provided by the motion sensor, the IMD can determine the patient's posture (e.g., sitting or lying down). The IMD can determine whether to perform an StO2 measurement or include an StO2 measurement in the analysis of the StO2 data based on the determined posture, for example, such that an StO2 measurement is preferentially performed or not performed when the patient is in one or more postures.

[0030] If the motion level is less than a threshold motion level and the amount of ambient light is less than a threshold amount of ambient light, the processing circuitry may output instructions directing the IMD to perform a StO2 measurement. The IMD may then perform a StO2 measurement to obtain data indicating a StO2 value and output the data to the processing circuitry. Based on the StO2 value and, in some instances, other StO2 values ​​associated with previous StO2 measurements, the processing circuitry may identify a trend in the StO2 value. The processing circuitry may compare the trend in the StO2 value with one or more sample trends of StO2 values ​​to determine whether the patient is experiencing a particular patient condition or to monitor the patient condition to determine whether the patient condition is worsening or worsening. For example, a decrease in StO2 values ​​over a period of time may indicate that the patient condition is worsening or worsening. However, since StO2 can be a weighted average of SaO2 and SvO2, it may be beneficial to perform an SpO2 measurement to confirm that the cause of the StO2 value trend is more closely related to the SaO2 trend than the SvO2 trend. Similarly, if StO2 has not changed, it is unlikely that SpO2 has changed, and therefore, completing an SpO2 measurement may not be necessary. Thus, based on a comparison of the trend of the StO2 values ​​with one or more sample trends of StO2 values, the processing circuitry can output instructions directing the device to perform an SpO2 measurement to obtain an SpO2 value. In some instances, the device is an IMD. In other instances, the device is a device other than an IMD configured to perform SpO2 measurements. If the SpO2 values ​​confirm that the trend of the StO2 values ​​does indicate a worsening of the patient's condition, the processing circuitry can output an alarm.

[0031] In some instances, the processing circuit system can analyze a set of StO2 values ​​that each correspond to a corresponding StO2 measurement based on any combination of a set of parameters. For example, if the IMD performs an StO2 parameter measurement, the IMD can also perform a set of measurements of other parameters to obtain a set of parameter values. In this way, the set of parameter values ​​can be associated with the corresponding StO2 measurement. In some instances, the set of parameters includes the amount of ambient light present in the target tissue, the optical sensor test signal, the temperature of the target tissue, the patient's posture, respiratory rate, respiratory volume, heart rate, heart rate variability, tissue hemoglobin index (THI), and / or subcutaneous tissue impedance. To analyze the set of StO2 values ​​associated with different postures, for example, in some cases, the processing circuit system can use the measured posture parameter values ​​to identify a first subset of StO2 values ​​corresponding to StO2 parameter measurements performed by the IMD when the patient is in a prone posture, and identify a second subset of StO2 values ​​corresponding to StO2 parameter measurements performed by the IMD when the patient is in a supine posture. In other words, in some cases, the processing circuit system can classify the StO2 value based on one or more conditions corresponding to the corresponding StO2 measurement made, and the one or more conditions are given by the respective sets of parameter values ​​measured at each StO2 measurement.

[0032] In this manner, the processing circuitry analyzes together the group of StO2 values ​​measured at different times but under similar measurement conditions with respect to other parameters. Trends in such grouped StO2 values ​​over time can indicate changes in the patient's condition due to factors unrelated to changes in the values ​​of other parameters. Comparisons between StO2 values ​​from different groups can indicate how sensitive the StO2 values ​​are to changes in other parameters, for example, how the StO2 values ​​vary with posture, which can also indicate one or more patient conditions.

[0033] Figure 1 The environment of an example medical device system 2 incorporating a patient 4 according to one or more techniques of the present disclosure is shown. The example techniques can be used with an IMD 10 that can communicate wirelessly with an external device 12 and processing circuitry 14. In some examples, IMD 10 can be implanted outside the chest of patient 4 (e.g., subcutaneously). Figure 1 The IMD 10 can be positioned near the sternum near or just below the level of the heart 6, for example, at least partially within the outline of the heart. In some examples, the IMD 10 employs a LINQ TMExternal device 12 may be in the form of an insertable cardiac monitor (ICM). External device 12 may be a computing device configured for use in an environment such as a home, clinic, or hospital, and may further be configured to communicate with IMD 10 via wireless telemetry. For example, external device 12 may be coupled to a remote patient monitoring system, such as the one available from Medtronic plc of Dublin, Ireland. In some examples, external device 12 may include a programmer, an external monitor, or a consumer device such as a smartphone or tablet computer. In some examples, processing circuitry 14 may represent processing circuitry located within any combination of IMD 10 and external device 12. Additionally, in some examples, processing circuitry 14 may include processing circuitry located within Figure 1 processing circuitry within another device or group of devices not shown.

[0034] IMD 10 may include multiple electrodes ( Figure 1 not shown) and comprising one or more optical sensors ( Figure 1 The optical sensor group (not shown) includes one or more optical sensors that collectively detect signals that enable processing circuit system 14 to determine current values ​​of at least one patient parameter associated with patient 4 and, based on such values, assess a medical condition (e.g., heart failure, sleep apnea, or chronic obstructive pulmonary disease (COPD)) of patient 4. The at least one parameter may include, for example, StO2, rSO2, SpO2, SvO2, SaO2, patient motion level, patient posture, ambient light level, optical signal quality, subcutaneous tissue impedance, heart rate, heart rate variability, respiratory rate, respiratory volume, pulse transit time, temperature, and any combination of THI.

[0035] The one or more optical sensors may include at least two light emitters and at least one light detector. In some examples, IMD 10 may perform StO2 measurements by emitting light via the light emitters and detecting the light via the at least one light detector. To determine the StO2 value, in some examples, processing circuitry 14 may compare the spectrum of light emitted from the at least two emitters with the spectrum of light received by the at least one light detector. StO2 may represent a weighted average of SaO2 and SvO2. In some examples, the StO2 value may be equal to the sum of one-quarter the SaO2 value and three-quarters the SvO2 value. Alternatively, in some examples, the StO2 value may be equal to the sum of one-third the SaO2 value and two-thirds the SvO2 value.

[0036] In some instances, to monitor patient conditions such as heart failure, sleep apnea, or COPD, the IMD 10 performs a set of StO2 measurements using one or more optical sensors. The IMD 10 may output data indicating the set of StO2 measurements to the processing circuit system 14. Based on the data indicating the set of StO2 measurements, the processing circuit system 14 may determine a StO2 value corresponding to each StO2 value in the set of StO2 values. Additionally, in some instances, the processing circuit system 14 may determine a trend in the StO2 values. In some cases, if the trend indicates that the StO2 values ​​are decreasing over a period of time (e.g., the trend is unstable), the processing circuit system 14 may determine that the patient's condition is worsening. In some such cases, the processing circuit system 14 may output an alert that recommends an action plan for the patient 4.

[0037] In some cases, certain factors may introduce noise into the StO2 data generated by the StO2 measurement or otherwise degrade the quality of the StO2 data. Such factors may include the level of ambient light present in the tissue area near the IMD 10 or the level of motion of the patient 4 when the StO2 measurement is performed by the IMD 10. Generally, low levels of ambient light and low levels of patient motion contribute to high-quality StO2 measurements. Thus, the IMD 10 may measure the amount of ambient light present in the tissue surrounding the IMD 10 and the level of motion of the patient 4 before performing the StO2 measurement.

[0038] For example, processing circuitry 14 may be configured to determine whether to output instructions directing IMD 10 to perform StO2 measurements using an optical sensor based on the level of motion associated with patient 4 and based on the amount of ambient light present in tissue surrounding IMD 10 of patient 4. To determine whether to output instructions to IMD 10, processing circuitry 14 may output instructions directing IMD 10 to use a motion sensor ( Figure 1Instructions for performing motion level measurements (not shown) may be provided for the motion sensor 10 to perform motion level measurements. In some cases, the motion sensor is an accelerometer. The accelerometer may be configured to determine acceleration values ​​of the IMD 10 over a period of time, the acceleration values ​​including acceleration components in any one of three dimensions (e.g., x-axis, y-axis, and z-axis). The IMD 10 may output data indicating the motion level measurements to the processing circuit system 14. The acceleration of the IMD 10 measured by at least one motion sensor of the IMD 10 may indicate the motion level of the patient 4. For example, if the patient 4 is walking, running, exercising, or moving in another manner, the data from the one or more motion sensors may indicate a greater acceleration value and therefore a higher patient motion level than if the patient 4 is sitting or lying still. In addition, the data from the at least one motion sensor may indicate a posture of the patient 4 such as sitting, standing, or lying down (e.g., supine, prone, left side, and right side). In some instances, patient motion may affect the accuracy of StO2 measurements, such that StO2 measurements performed by IMD 10 when patient 4 moves more may be less valuable for assessing the patient's condition than StO2 measurements performed by IMD 10 when patient 4 moves less.

[0039] Additionally, processing circuitry 14 may output instructions directing the medical device to perform an ambient light measurement using the optical sensor. IMD 10 may activate the optical sensor's light emitter to perform an StO2 measurement or an SpO2 measurement. However, in some instances, to perform an ambient light measurement, it is sufficient for IMD 10 to activate at least one light detector of the optical sensor—no light emitter activation is required. In this manner, performing an ambient light measurement may consume less energy than performing an StO2 measurement. In some cases, IMD 10 may output data corresponding to the ambient light measurement to processing circuitry 14 for analysis.

[0040] After receiving data corresponding to a motion level, processing circuitry 14 may be configured to determine a motion level associated with patient 4. Processing circuitry 14 may determine the motion level based on acceleration data, where greater acceleration values ​​indicate greater patient motion levels. Additionally, after receiving data corresponding to an ambient light measurement, processing circuitry 14 may be configured to determine the amount of ambient light present in a portion of tissue surrounding IMD 10. Ambient light may be detected by a light detector of IMD 10. However, in some cases, IMD 10 may not need to activate a light emitter to detect ambient light. Thus, ambient light measurement may consume less energy than StO2 or SpO2 measurements, which utilize light emitters at different time periods. Processing circuitry 14 may compare the motion level to a threshold motion level and the amount of ambient light to a threshold amount of ambient light. The threshold motion level and the threshold amount of ambient light may be stored in a memory device of IMD 10, in an external device 12, in another memory device in communication with processing circuitry 14, or in any combination thereof.

[0041] In some cases, if the motion level is below a threshold motion level and the amount of ambient light is below a threshold amount of ambient light, processing circuitry 14 may output an instruction to IMD 10 to perform an optical test measurement. Subsequently, IMD 10 may perform the optical test measurement to obtain an optical test signal. IMD 10 may output the optical test signal to processing circuitry 14 for analysis. In some instances, the optical test measurement includes activating an optical sensor (e.g., a light emitter and a light detector) of IMD 10. In some instances, the optical test signal generated by the optical test measurement may include a sequence of data points having a duration between one second and ten seconds. The sequence may include a set of frequency components ranging between 4 Hertz (Hz) and 55 Hz. Processing circuitry 14 may be configured to determine whether the optical test signal quality is sufficient. For example, processing circuitry 14 may analyze the set of frequency components of the optical test signal to determine whether the optical sensor of IMD 10 is currently capable of generating high-quality optical data.

[0042] In some instances, if the motion level is greater than or equal to a threshold motion level, if the amount of ambient light is greater than or equal to a threshold amount of ambient light, or if processing circuitry 14 determines that the optical test signal is insufficient, processing circuitry 14 is configured to determine output instructions directing IMD 10 to perform a StO2 measurement. However, in such instances, processing circuitry is configured to indicate that the StO2 measurement was performed under adverse conditions that could potentially compromise data collected during the StO2 measurement. Subsequently, IMD 10 may perform the StO2 measurement and output data corresponding to the StO2 measurement to processing circuitry 14. In some instances, processing circuitry 14 is configured to determine a StO2 value based on the data indicating the StO2 measurement. Processing circuitry 14 may add the StO2 value to a set of StO2 values ​​as part of a set of low-quality StO2 values ​​because the StO2 measurement that produced the StO2 value was performed under suboptimal conditions.

[0043] Additionally, in such instances, if the motion level is less than a threshold motion level, if the amount of ambient light is less than a threshold amount of ambient light, and if processing circuitry 14 determines that the optical test signal is sufficient, processing circuitry 14 is configured to output instructions directing IMD 10 to perform a StO2 measurement. Processing circuitry 14 may determine that a StO2 measurement performed under such conditions can predict a high-quality StO2 value. Subsequently, IMD 10 may perform the StO2 measurement and output data corresponding to the StO2 measurement to processing circuitry 14. Processing circuitry 14 is configured to determine the StO2 value based on the data indicating the StO2 measurement. Processing circuitry 14 may add the StO2 value to a set of StO2 values ​​as part of a set of high-quality StO2 values ​​because the StO2 measurement that produced the StO2 value was performed under optimal conditions.

[0044] In some cases, it may be beneficial to categorize the StO2 values ​​into a set of high-quality StO2 values ​​and a set of low-quality StO2 values, so that processing circuitry 14 can analyze the set of high-quality StO2 values ​​to identify or monitor a patient condition while excluding the set of low-quality StO2 values. Additionally, in some cases, it may be beneficial to avoid using IMD 10 to perform StO2 measurements that may result in low-quality StO2 values. In other words, processing circuitry 14 may output instructions to perform StO2 measurements after performing an evaluation to determine that conditions are favorable for obtaining high-quality StO2 values.

[0045] In some examples, if the motion level is greater than or equal to a threshold motion level, if the amount of ambient light is greater than or equal to a threshold amount of ambient light, or if processing circuitry 14 determines that the optical test signal is insufficient, processing circuitry 14 is configured to determine not to output instructions directing IMD 10 to perform an StO2 measurement. In some examples, if the motion level is less than the threshold motion level, if the amount of ambient light is less than the threshold amount of ambient light, and if processing circuitry 14 determines that the optical test signal is sufficient, processing circuitry 14 is configured to determine to output instructions directing IMD 10 to perform an StO2 measurement. In this manner, if the amount of ambient light is sufficiently low and the patient motion level is sufficiently low, processing circuitry 14 is configured to direct IMD 10 to proceed with the StO2 measurement, thereby preventing IMD 10 from using energy to produce a less accurate StO2 value. Additionally, processing circuitry 14 may determine whether to output instructions directing IMD 10 to perform an StO2 measurement based on one or more patient parameters other than the amount of ambient light present in tissue and the patient motion level. The one or more patient parameters may include temperature of a tissue region, patient posture, respiratory rate, heart rate, impedance associated with electrodes of IMD 10, or any combination thereof. By analyzing additional parameters when evaluating whether to proceed with an StO2 measurement, the processing circuitry may reduce variability in the conditions under which the StO2 measurement is made, thereby reducing the amount of noise in the StO2 measurement made by IMD 10.

[0046] In some such instances where the motion level is below a threshold motion level, the amount of ambient light is below a threshold amount of ambient light, and processing circuitry 14 determines that the optical test signal is sufficient, processing circuitry 14 may be configured to output instructions to IMD 10 to perform a StO2 measurement, thereby causing IMD 10 to perform the StO2 measurement. IMD 10 may then perform the StO2 measurement and export data corresponding to the StO2 measurement to processing circuitry 14.

[0047] In some instances, to perform an StO2 measurement, the IMD 10 may obtain a sequence of StO2 samples using an optical sensor at a sampling frequency in the range of 2 Hz to 10 Hz. In some instances, the duration of the sequence is in the range of 2 seconds to 15 seconds. Subsequently, the processing circuit system of the IMD 10 may calculate the standard deviation of the samples and calculate an accuracy value based on the standard deviation. In addition, the IMD 10 may determine the number of StO2 samples (N) associated with the calculated accuracy value, where N represents the minimum number of StO2 samples that the IMD 10 must take during the StO2 measurement in order for the IMD 10 to determine that the StO2 measurement is sufficient. In some instances, the IMD 10 may associate a lower number N with a lower accuracy value and a higher number N with a higher accuracy value. If the sequence length of the StO2 samples is greater than or equal to N samples, the IMD 10 may determine that the StO2 measurement is sufficient and send the sequence of StO2 samples to the processing circuit system 14. If the sequence length of the StO2 samples is less than N samples, IMD 10 may determine that the StO2 measurement is insufficient, and IMD 10 may obtain another sequence of StO2 samples, wherein the additional sequence of StO2 samples comprises N samples. IMD 10 may then send the additional sequence of StO2 samples to processing circuitry 14 for analysis. In some cases, IMD 10 may store the value of N in a memory device of IMD 10 for future reference. IMD 10 may perform subsequent StO2 measurements such that the initial sequence length of the StO2 samples employed during the subsequent StO2 measurements is N samples.

[0048] After receiving data corresponding to a StO2 measurement (e.g., a sequence of StO2 samples deemed sufficient by IMD 10), processing circuitry 14 is configured to determine a StO2 value associated with patient 4. In some instances, processing circuitry 14 determines the StO2 value by calculating a mean or median of the sequence of StO2 samples corresponding to the respective StO2 measurements. In some cases, the StO2 value may be one of a set of StO2 values ​​that each correspond to a separate StO2 measurement. Processing circuitry 14 may add the StO2 value to the tissue oxygen saturation value, which may be stored in a memory device of IMD 10, in external device 12, in another device in communication with processing circuitry 14, or in any combination thereof.

[0049] The set of StO2 values ​​can be analyzed to identify or monitor a patient condition. For example, based on the set of StO2 values, the processing circuitry 14 can identify a trend in the StO2 values. In some cases, the trend can be a linear best-fit curve, an exponential best-fit curve, a logarithmic best-fit curve, or another type of best-fit model. In some cases, the trend in the StO2 values ​​can be represented by an indication of whether the StO2 values ​​are increasing, decreasing, or generally remaining constant over a period of time. Because the processing circuitry is, in some cases, configured to categorize the StO2 values ​​into a set of high-quality StO2 values ​​and a set of low-quality StO2 values, it can be beneficial to identify the trend in the StO2 values ​​based on the set of high-quality StO2 values ​​while excluding the set of low-quality StO2 values. In this way, the processing circuitry 14 can reduce the amount of variation in the trend of the StO2 values ​​caused by conditions such as ambient light and patient motion, and increase the likelihood that the trend in the StO2 values ​​can be used to identify or monitor a patient condition. After the processing circuitry 14 adds the new high-quality StO2 value to the set of StO2 values, the processing circuitry 14 can be configured to determine whether the trend in the StO2 values ​​is stable. To determine trend stability, processing circuitry 14 may be configured to compare the trend of the StO2 values ​​to a threshold trend to identify whether the set of high-quality StO2 values ​​has changed over a period of time (or other means of detecting meaningful changes). Additionally, in some cases, processing circuitry 14 may determine trend stability by comparing the most recent high-quality StO2 value to a threshold StO2 value. If the most recent high-quality StO2 value is below the threshold StO2 value, processing circuitry 14 may determine that the trend is unstable. In some instances, the threshold StO2 value represents an average StO2 value over a period of time (e.g., a week or a month).

[0050] If the processing circuit system 14 determines that the trend of the StO2 values ​​is stable, indicating that the set of high-quality StO2 values ​​has not changed meaningfully, then it is unlikely that SpO2 has changed, and the processing circuit system 14 can return to evaluating whether it is time to perform an evaluation to monitor for conditions that may be caused by noise.

[0051] If processing circuitry 14 determines that the trend of the StO2 values ​​is unstable, thereby indicating a meaningful change in the set of high-quality StO2 values, processing circuitry 14 may output an instruction to perform an SpO2 measurement. In some instances, processing circuitry 14 outputs the instruction to perform an SpO2 measurement to confirm that the instability in the trend of the StO2 values ​​is due to instability in patient 4's SaO2—and not instability in other parameters such as SvO2. In some instances, processing circuitry 14 outputs the instruction to perform an SpO2 measurement to IMD 10. In some such instances, IMD 10 performs the SpO2 measurement and sends data corresponding to the SpO2 measurement to processing circuitry 14. In other instances, processing circuitry 14 outputs the instruction to perform an SpO2 measurement to a device other than IMD 10 that is configured to perform an SpO2 measurement (e.g., a fingertip pulse oximeter, a smartphone, or a desktop base station). The device may perform the SpO2 measurement and send data corresponding to the SpO2 measurement to processing circuitry 14. In either case, processing circuitry 14 may receive data corresponding to the SpO2 measurement. Based on the data corresponding to the SpO2 measurement, processing circuitry 14 may determine an SpO2 value.

[0052] In instances where the IMD 10 uses an optical sensor to perform SpO2 measurements, the SpO2 measurement may consume significantly more energy than the StO2 measurement. For example, the SpO2 measurement may consume up to three orders of magnitude (1,000 times) more energy than the StO2 measurement. As such, it may be important to limit the number of SpO2 measurements performed by the IMD 10. For example, when the processing circuitry 14 determines that the patient's condition is likely worsening, the processing circuitry 14 may instruct the IMD 10 to perform an SpO2 measurement. (For example, when the processing circuitry 14 identifies an unstable or declining trend in the StO2 value). In some instances, the processing circuitry 14 may instruct a pulse oximetry device other than the IMD 10 to perform the SpO2 measurement to conserve charge in the power supply of the IMD 10.

[0053] After processing circuitry 14 determines the SpO2 value corresponding to the SpO2 measurement, processing circuitry 14 may determine whether the trend of the StO2 value is unstable due to instability of SaO2 in patient 4, or whether the trend of the StO2 value is unstable due to a parameter other than SaO2 (e.g., SvO2). If the trend of the StO2 value is unstable due to a parameter other than SaO2, and if the trend of the StO2 value is unstable due to instability of SaO2 in patient 4, processing circuitry 14 may determine that the trend of the StO2 value indicates a worsening of the patient's condition (e.g., heart failure). In turn, processing circuitry 14 may output an alert that the patient's condition is worsening. In some examples, processing circuitry 14 may output an alert to external device 12 or another external device accessible by patient 4 or a clinician.

[0054] External device 12 can be used to program commands or operating parameters into IMD 10 to control its operation (e.g., when configured as a programmer for IMD 10). In some instances, external device 12 can be used to interrogate IMD 10 to retrieve data, including device operating data as well as physiological data accumulated in IMD memory. Such interrogation can occur automatically according to a schedule, or can occur in response to a remote or local user command. Programmers, external monitors, and consumer devices are examples of external devices 12 that can be used to interrogate IMD 10. Examples of communication technologies used by IMD 10 and external device 12 include radio frequency (RF) telemetry, which can be performed via An RF link established by near field communication (NFC), WiFi, or Medical Implant Communication Service (MICS). In some examples, external device 12 may include a user interface configured to allow a clinician to interact with IMD 10 remotely.

[0055] IMD 10 can be configured to monitor more periodic signals indicative of patient status and use these signals to identify "template" or "signature" periods during which the optical signal is most reproducible and indicative of trends in the overall state and / or pathology of patient 4. For example, the temperature of patient 4's subcutaneous space, relatively close to the skin, can be regulated by the external environment and by thermoregulation through vasodilation to control blood flow. For example, in a hot environment, patient 4's autonomic nervous system may dilate blood vessels to increase blood flow, thereby increasing heat transfer from the core body to the environment. Similarly, in a cold environment, patient 4's autonomic nervous system may constrict blood vessels near the skin to limit heat flow to the environment and maintain core body temperature. Vasodilation and vasoconstriction alter both the overall net flow of blood and the metabolic oxygen exchange balance, which may affect measurements performed using the optical sensors of IMD 10. In some cases, vasodilation and vasoconstriction can be determined at least in part based on THI. Furthermore, patient 4's surface temperature can vary based on daily cycles corresponding to sleep and wakefulness, as well as other physiological factors.

[0056] After IMD 10 is implanted in patient 4, the temperature sensor of IMD 10 may measure the temperature of patient 4 at intervals (e.g., every 1-30 minutes) for a period of time, for example, between 1 and 8 weeks. IMD 10 may aggregate and analyze the temperature data to determine a representative temperature baseline. In some instances, processing circuitry 14 may use the representative temperature baseline when performing an assessment to determine whether to output an instruction to IMD 10 directing IMD 10 to perform an StO2 measurement. For example, to perform the assessment, processing circuitry 14 may instruct IMD 10 to measure the temperature of patient 4 and compare the measured temperature to the representative temperature baseline. Based on the comparison, processing circuitry 14 may determine whether to output an instruction to perform an StO2 measurement. The representative temperature baseline may include one of several random measurements. For example, the representative temperature baseline may be represented by a range around a mean or median baseline temperature. In some instances, it is known that optical sensor signals produce better SNR at elevated temperatures due to increased blood flow. Thus, in some cases, the representative temperature baseline may be represented by a range around a higher temperature, such as the 80th percentile temperature.

[0057] In some instances, an infection may cause the core body temperature of the patient 4 to increase over time. Additionally, in some instances, conditions such as internal bleeding or progressive heart failure may cause peripheral vasoconstriction. In these instances, temperature trends can be reported as diagnostic information and can also be used to adjust the criteria measured by the optical sensor.

[0058] Signals such as patient posture, respiration, heart rate, heart rate variability, and impedance can be used individually or in combination to determine whether to perform a measurement using the optical sensor of IMD 10. For example, processing circuit system 14 can instruct IMD 10 to take a set of StO2 measurements, wherein patient 4 is under substantially the same conditions each time each StO2 measurement of the set of StO2 measurements is taken. In other words, processing circuit system 14 can evaluate one or more of patient posture, respiration, heart rate, heart rate variability, and impedance, as well as THI indicating vasodilation or vasoconstriction, before each StO2 measurement to ensure that the values ​​of such parameters remain relatively constant throughout the set of StO2 measurements. In some instances, processing circuit system 14 can automatically monitor periods when patient 4 is resting (indicated by respiration, heart rate, and heart rate variability), periods when patient 4 is supine, periods when patient 4 is prone (indicated by posture sensing), similar interstitial fluid states (indicated by impedance), similar temperatures, or any combination thereof. In some instances, processing circuit system 14 can output instructions to perform a measurement using the optical sensor at the same point during each respiratory cycle of a set of respiratory cycles.

[0059] In addition, these signals (e.g., patient posture, respiration, heart rate, heart rate variability, impedance, and / or THI) can be used to classify the StO2 measurements performed by the IMD 10. For example, at approximately the time that the IMD 10 performs the StO2 measurement, the IMD 10 can additionally measure a set of parameter values ​​(e.g., signals) and associate the set of parameter values ​​with the StO2 measurement. In some cases, each StO2 measurement of a set of StO2 measurements can be associated with a set of corresponding parameter values. In this manner, the processing circuit system 14 can analyze the set of StO2 measurements based on the set of corresponding parameter values ​​to reduce the variability of the conditions associated with the StO2 measurements. In some instances, the set of parameter values ​​and the set of StO2 measurements can be inputs to a machine learning algorithm that outputs an analysis of the set of StO2 measurements based on the set of corresponding parameter values.

[0060] In some examples, if patient 4 suffers from COPD or sleep apnea, medical device system 2 may monitor for an increased heart rate over a period of time. However, in some cases, physical activity, stress, or other factors may induce a similar increase in heart rate. In such cases, the optical sensor of IMD 10 may be interrogated to determine whether the increase in heart rate is related to COPD or sleep apnea.

[0061] Generally speaking, reducing the effects of physiological variability by monitoring several patient parameters may enhance the ability of the medical device system 2 to identify or monitor a patient condition.

[0062] Medical device system 2 is an example of a medical device system configured to identify or monitor one or more conditions of patient 4. At least some of the techniques described herein may be performed by processing circuitry 14 of a device of medical device system 2. In some examples, processing circuitry 14 may include processing circuitry of IMD 10, processing circuitry of external device 12, and / or processing circuitry of one or more other implantable devices or external devices or servers not shown. Examples of the one or more other implantable devices or external devices may include a transvenous, subcutaneous, or extravascular pacemaker or implantable cardioverter-defibrillator (ICD), a blood analyzer, an external monitor, a drug pump, or an external pulse oximetry device. The communication circuitry of each of the devices of medical device system 2 allows the devices to communicate with each other. Additionally, although optical sensors and electrodes are described herein as being positioned on the housing of IMD 10, in other examples, such optical sensors and / or electrodes may be positioned on a device implanted in patient 4, such as a transvenous, subcutaneous, or extravascular pacemaker or ICD. Figure 1 The device may be mounted on a housing of another device not shown in the drawings, or coupled to such a device via one or more leads.

[0063] Additionally or alternatively, in some instances, the optical sensor and / or electrodes may be positioned on a device external to the patient 4, such as A fingertip pulse oximeter, an activity watch, a smart phone, or any combination thereof. The external device may also include a blood gas analyzer or chemical sensor that requires a blood sample to be drawn from the patient, or an invasive monitor such as an arterial line or Swan-Ganz catheter for measuring blood pressure. In such instances, one or more of IMD 10 and external device 12 may include a device configured to (e.g., The IMD 10 may include a housing (e.g., an antenna) and processing circuitry for receiving signals from the electrodes or optical sensors. In some examples, the IMD 10 may include a longer housing and may be configured to measure a patient's ECG. In other examples, the IMD 10 may include a shorter housing and measure optical signals.

[0064] In some instances, medical device system 2 may be configured to monitor one or more parameters in addition to or in lieu of: StO2, SpO2, patient motion level, patient posture, ambient light level, optical signal quality, impedance, heart rate, heart rate variability, respiratory rate, pulse transit time, and temperature. For example, sensors on IMD 10 or one or more other implantable or external devices may be configured to sense signals related to such parameters. Such one or more parameters may be associated with a physiological function of patient 4, such as renal function, which may change when the patient's condition (e.g., heart failure) changes. For example, one or more implantable or external devices of medical device system 2 (e.g., IMD 10) may include one or more sensors configured to sense blood or tissue levels of one or more compounds related to patient 4's renal function, such as creatinine or blood urea nitrogen. In some instances, such one or more parameters may not be directly correlated to a change in the state of the patient's condition, but may instead provide other information about patient 4's health, such as motion level or sleep patterns.

[0065] Figure 2-4B Shown Figure 1 Various aspects and example arrangements of the IMD 10. For example, Figure 2 Example physical configurations of IMD 10 are conceptually illustrated. Figure 3 is a block diagram illustrating an example functional configuration of IMD 10. Figure 4A and 4B Additional views of example physical and functional configurations of IMD 10 are shown. It should be understood that the following descriptions of Figure 2-4B Any of the described examples of the IMD 10 can be used to implement the techniques described herein for determining whether to perform parameter measurements using the IMD 10. The IMD 10 can simultaneously collect sensor signals and parameter measurements. For example, the compiled data can be used for model fitting and other artificial intelligence techniques to assess and predict the trajectory of a patient's condition. Additionally, the compiled data can be used to classify or group parameter measurements made by the IMD 10. Some measurements made by the IMD 10 can be used to classify or group other measurements.

[0066] Figure 2 is a demonstration of one or more techniques described herein Figure 1 A conceptual diagram of an example configuration of an IMD 10 of a medical device system 2 is shown. Figure 2In the example shown, IMD 10 can include a leadless, subcutaneously implantable monitoring device having a housing 15, a proximal electrode 16A, and a distal electrode 16B. Housing 15 can further include a first major surface 18, a second major surface 20, a proximal end 22, and a distal end 24. In some examples, IMD 10 can include one or more additional electrodes 16C, 16D positioned on one or both of major surfaces 18, 20 of IMD 10. Housing 15 encloses electronic circuitry positioned within IMD 10 and protects the circuitry contained therein from fluids such as bodily fluids. In some examples, electrical leads provide electrical connection of electrodes 16A-16D and antenna 26 to the circuitry within housing 15. In some examples, electrode 16B can be formed from an uninsulated portion of conductive housing 15.

[0067] exist Figure 2 In the example shown, IMD 10 is defined by a length L, a width W, and a thickness or depth D. In this example, IMD 10 is in the form of an elongated rectangular prism, wherein length L is significantly greater than width W, and wherein width W is greater than depth D. However, other configurations of IMD 10 are contemplated, such as those in which the relative proportions of length L, width W, and depth D are greater than those of FIG. Figure 2 In some examples, the geometry of IMD 10, such as width W being greater than depth D, can be selected to allow IMD 10 to be inserted under the patient's skin using a minimally invasive procedure and maintained in a desired orientation during insertion. Additionally, IMD 10 can include radial asymmetry (e.g., a rectangular shape) along the longitudinal axis of IMD 10, which can help maintain the device in a desired orientation after implantation.

[0068] In some examples, the spacing between proximal electrode 16A and distal electrode 16B can be in the range of approximately 30-55 millimeters (mm), approximately 35-55 mm, or approximately 40-55 mm, or more generally, approximately 25-60 mm. In general, the length L of IMD 10 can be approximately 20-30 mm, approximately 40-60 mm, or approximately 45-60 mm. In some examples, the width W of major surface 18 can be in the range of approximately 3-10 mm, and can be any single width or range of widths between approximately 3-10 mm. In some examples, the depth D of IMD 10 can be in the range of approximately 2-9 mm. In other examples, the depth D of IMD 10 can be in the range of approximately 2-5 mm, and can be any single depth or range of depths between approximately 2-9 mm. In any such examples, IMD 10 is compact enough to be implanted in the subcutaneous space in the pectoral region of patient 4. In some examples, the housing of IMD 10 is configured for ECG measurements. Additionally, in some examples, the housing of IMD 10 is configured for optical sensing. The housing configured for optical sensing can be significantly smaller than the housing configured for ECG sensing, and the housing configured for optical sensing can be implanted in a different area of ​​the body of patient 4 than the housing configured for ECG sensing.

[0069] According to examples of the present disclosure, the IMD 10 can have a geometry and size designed for ease of implantation and patient comfort. The example of the IMD 10 described in the present disclosure can have a volume of 3 cubic centimeters (cm 3 ) or smaller, 1.5cm 3 or smaller or any volume therebetween. Figure 2 In the example shown, proximal end 22 and distal end 24 are rounded to reduce discomfort and irritation to surrounding tissue after implantation under the skin of patient 4. In some examples, IMD 10 may be powered via inductive coupling.

[0070] In some examples, when IMD 10 is inserted into patient 4, first major surface 18 of IMD 10 faces outwardly toward the skin, while second major surface 20 faces inwardly toward the muscle tissue of patient 4. Thus, first major surface 18 and second major surface 20 can face in a direction along the sagittal axis of patient 4 (see FIG. Figure 1 ), and due to the size of IMD 10, this orientation can be maintained after implantation. In some examples, first major surface 18 faces inwardly toward the muscle tissue of patient 4, and second major surface 20 faces outwardly toward the skin of patient 4.

[0071] When IMD 10 is subcutaneously implanted in patient 4, proximal electrode 16A and distal electrode 16B can be used to sense cardiac EGM signals (e.g., ECG signals). Processing circuitry 14 can determine a pulse transit time value based in part on the cardiac ECG signals, as further described below. In some instances, the processing circuitry of IMD 10 can also determine whether the cardiac ECG signal of patient 4 indicates an arrhythmia or other abnormality that the processing circuitry of IMD 10 can evaluate when determining whether the condition of patient 4 (e.g., heart failure) has changed. The cardiac ECG signal can be stored in a memory of IMD 10, and data derived from the cardiac ECG signal can be transmitted to another medical device, such as external device 12, via integrated antenna 26. In some examples, one or both of electrodes 16A and 16B may also be used to detect subcutaneous impedance values ​​to assess the hyperemic state of patient 4, monitor one or more respiratory parameters (e.g., respiratory rate, respiratory rate variability, respiratory effort, and relative tidal volume), and / or may be used by communication circuitry of IMD 10 for tissue conductance communication (TCC) with external device 12. In some examples, the ECG and / or impedance signals obtained by electrodes 16A and 16B may be used to determine one or more respiratory parameters (e.g., respiratory rate, respiratory rate variability, respiratory effort, or relative tidal volume).

[0072] exist Figure 2 In the example shown, proximal electrode 16A is in close proximity to proximal end 22, and distal electrode 16B is in close proximity to distal end 24 of IMD 10. In this example, distal electrode 16B is not limited to a flat, outward-facing surface, but rather may extend from first major surface 18 around circular edge 28 or end surface 30 and into second major surface 20 in a three-dimensional curved configuration. As shown, proximal electrode 16A is positioned on first major surface 18 and is substantially flat and outward-facing. However, in other examples not shown herein, both proximal electrode 16A and distal electrode 16B may be substantially flat, as shown in FIG. Figure 2 The proximal electrode 16A shown in FIG. 1 may be configured as shown in FIG. Figure 2 16B is configured as shown in FIG. 16C and 16D. In some examples, additional electrodes 16C and 16D can be positioned on one or both of first major surface 18 and second major surface 20, for a total of four electrodes on IMD 10. Any of electrodes 16A-16D can be formed from a biocompatible conductive material. For example, any of electrodes 16A-16D can be formed from any of stainless steel, titanium, platinum, iridium, or alloys thereof. Additionally, the electrodes of IMD 10 can be coated with materials such as titanium nitride or fractal titanium nitride, although other suitable materials and coatings for such electrodes may be used.

[0073] exist Figure 2In the example shown, the proximal end 22 of the IMD 10 includes a head mount assembly 32 having one or more of a proximal electrode 16A, an integrated antenna 26, an anti-migration protrusion 34, and a suture hole 36. The integrated antenna 26 is positioned on the same major surface (e.g., the first major surface 18) as the proximal electrode 16A and can be an integral part of the head mount assembly 32. In other examples, the integrated antenna 26 can be formed on a major surface opposite the proximal electrode 16A, or in still other examples, can be incorporated into the housing 15 of the IMD 10. The antenna 26 can be configured to transmit or receive electromagnetic signals for communication. For example, the antenna 26 can be configured to communicate via inductive coupling, electromagnetic coupling, tissue conductance, NFC, radio frequency identification (RFID), Antenna 26 may be coupled to communication circuitry of IMD 10 that may drive antenna 26 to transmit signals to external device 12, and may transmit signals received from external device 12 to processing circuitry of IMD 10 via the communication circuitry.

[0074] IMD 10 may include several features for maintaining IMD 10 in place once it is subcutaneously implanted in patient 4. For example, Figure 2 As shown, housing 15 can include anti-migration protrusions 34 positioned adjacent integrated antenna 26. Anti-migration protrusions 34 can include a plurality of bumps or projections extending away from first major surface 18 and can help prevent movement of IMD 10 after implantation in patient 4. In other examples, anti-migration protrusions 34 can be positioned on a major surface opposite proximal electrode 16A and / or integrated antenna 26. Additionally, in Figure 2 In the example shown, headmount assembly 32 includes suture holes 36, which provide another means of securing IMD 10 to the patient to prevent migration after insertion. In the example shown, suture holes 36 are positioned near proximal electrode 16A. In some examples, headmount assembly 32 may include a molded headmount assembly made of a polymeric or plastic material, which may be integral with or separable from the main portion of IMD 10.

[0075] In some examples, processing circuitry of IMD 10 may determine a subcutaneous tissue impedance value of patient 4 based on signals received from at least two of electrodes 16A-16D. For example, processing circuitry of IMD 10 may generate one of a current signal or a voltage signal, deliver the signal through two or more selected electrodes of electrodes 16A-16D, and measure the other of the resulting current or voltage. Processing circuitry of IMD 10 may determine the impedance signal based on the delivered current or voltage and the measured voltage or current.

[0076] exist Figure 2 In the illustrated example, IMD 10 includes a light emitter 38 and a proximal light detector 40A and a distal light detector 40B (collectively, "light detectors 40") positioned on housing 15 of IMD 10. Light detector 40A can be positioned at a distance S from light emitter 38, while distal light detector 40B can be positioned at a distance S+N from light emitter 38. In other examples, IMD 10 can include only one of light detectors 40A, 40B, or can include additional light emitters and / or additional light detectors. In summary, light emitter 38 and light detectors 40A, 40B can comprise optical sensors that can be used in the techniques described herein to determine StO2 or SpO2 values ​​for patient 4. Although light emitter 38 and light detectors 40A, 40B are described herein as being positioned on housing 15 of IMD 10, in other examples, one or more of light emitter 38 and light detectors 40A, 40B may be positioned within patient 4, such as on the housing of another type of IMD, such as a transvenous, subcutaneous, or extravascular pacemaker or ICD, or connected to such a device via leads. Light emitter 38 comprises a light source, such as an LED, that can emit light at one or more wavelengths within the visible (VIS) and / or near-infrared (NIR) spectrum. For example, light emitter 38 can emit light at one or more of approximately 660 nanometers (nm), 720 nm, 760 nm, 800 nm, or any other suitable wavelength.

[0077] In some examples, techniques for determining StO2 can include using light emitter 38 to emit light at one or more VIS wavelengths (e.g., approximately 660 nm) and one or more NIR wavelengths (e.g., approximately 850-890 nm). The combination of VIS and NIR wavelengths can help enable the processing circuitry of IMD 10 to distinguish between oxyhemoglobin and deoxyhemoglobin in the tissue of patient 4 because, as the hemoglobin becomes less oxygenated, the attenuation of VIS light increases and the attenuation of NIR light decreases. By comparing the amount of VIS light detected by light detectors 40A, 40B with the amount of NIR light detected by light detectors 40A, 40B, the processing circuitry of IMD 10 can determine the relative amounts of oxyhemoglobin and deoxyhemoglobin in the tissue of patient 4. For example, if the amount of oxyhemoglobin in the tissue of patient 4 decreases, the amount of VIS light detected by light detectors 40A, 40B increases, and the amount of NIR light detected by light detectors 40A, 40B decreases. Similarly, if the amount of oxygenated hemoglobin in the tissue of the patient 4 increases, the amount of VIS light detected by the photodetectors 40A, 40B decreases, and the amount of NIR light detected by the photodetectors 40A, 40B increases.

[0078] like Figure 2 , light emitter 38 can be positioned on headmount assembly 32, but in other examples, one or both of light detectors 40A, 40B can additionally or alternatively be positioned on headmount assembly 32. In some examples, light emitter 38 can be positioned on a mid-section of IMD 10, such as a portion between proximal end 22 and distal end 24. Although light emitter 38 and light detectors 40A, 40B are shown as being positioned on first major surface 18, light emitter 38 and light detectors 40A, 40B can alternatively be positioned on second major surface 20. In some examples, the IMD can be implanted such that when IMD 10 is implanted, light emitter 38 and light detectors 40A, 40B face inwardly toward the muscles of patient 4, which can help minimize interference from background light outside the body of patient 4. Light detectors 40A, 40B can include glass or sapphire windows, as described below with respect to Figure 4B As described, it may alternatively be positioned beneath a portion of IMD 10 housing 15 that is made of glass or sapphire or is otherwise transparent or translucent.

[0079] During the technique for determining the StO2 value of patient 4, light emitter 38 may emit light to a target site in patient 4. When IMD 10 is implanted in patient 4, the target site may generally include the interstitial space surrounding IMD 10. Light emitter 38 may emit light directionally in that light emitter 38 may direct the signal to a side of IMD 10, such as when light emitter 38 is positioned on a side of IMD 10 that includes first major surface 18. The target site may include subcutaneous tissue adjacent to IMD 10 in patient 4.

[0080] The technique for determining the StO2 value can be based on the optical properties of blood-perfused tissue, which vary according to the relative amounts of oxyhemoglobin and deoxyhemoglobin in the tissue microcirculation. These optical properties are at least partially due to the different optical absorption spectra of oxyhemoglobin and deoxyhemoglobin. Therefore, the oxygen saturation level of the patient's tissue can affect the amount of light absorbed by the blood in the tissue adjacent to the IMD 10 and the amount of light reflected by the tissue. Each of the photodetectors 40A, 40B can receive light reflected by the tissue from the light emitter 38 and generate an electrical signal indicating the intensity of the light detected by the photodetectors 40A, 40B. The processing circuit system of the IMD 10 can then evaluate the electrical signals from the photodetectors 40A, 40B to determine the StO2 value of the patient 4.

[0081] In some examples, the difference between the electrical signals generated by photodetectors 40A, 40B can enhance the accuracy of the StO2 value determined by IMD 10. For example, because tissue absorbs some of the light emitted by light emitter 38, the intensity of light reflected by the tissue decreases as the distance (and tissue volume) between light emitter 38 and photodetectors 40A, 40B increases. Therefore, because photodetector 40B is farther from light emitter 38 (distance S+N) than photodetector 40A (distance S), the intensity of light detected by photodetector 40B should be less than the intensity of light detected by photodetector 40A. Because detectors 40A, 40B are in close proximity to each other, the difference between the intensity of light detected by photodetector 40A and the intensity of light detected by photodetector 40B should be attributed solely to the difference in distance from light emitter 38. In some examples, the processing circuitry of IMD 10 can use the difference between the electrical signals generated by photodetectors 40A, 40B, in addition to the electrical signals themselves, to determine the StO2 value of patient 4.

[0082] In some instances, the IMD 10 may include one or more additional sensors, such as one or more accelerometers (not shown). Such accelerometers may be 3D accelerometers that are configured to generate an indication of one or more types of movement of the patient, such as the patient's entire body movement (e.g., activity), patient posture, motion associated with heartbeat, coughing, rales, or other respiratory abnormalities. Additionally or alternatively, one or more of the parameters monitored by the IMD 10 may fluctuate in response to changes in one or more such motions. For example, a change in a parameter value may sometimes be attributed to an increase in patient activity (e.g., exercise or other physical activity relative to inactivity) or a change in the patient's posture, and not necessarily to a change in the heart failure state caused by the progression of the heart failure condition. Therefore, in some methods of identifying or monitoring the condition of the patient 4, it may be advantageous to consider such fluctuations when determining whether a change in a patient parameter indicates a change in the condition of the patient 4.

[0083] In some examples, IMD 10 can perform SpO2 measurements using light emitter 38 and light detector 40. For example, IMD 10 can perform SpO2 measurements by emitting light at one or more VIS wavelengths, one or more NIR wavelengths, or a combination of one or more VIS wavelengths and one or more NIR wavelengths using light emitter 38. By comparing the amount of VIS light detected by light detectors 40A, 40B with the amount of NIR light detected by light detectors 40A, 40B, processing circuitry of IMD 10 can determine the relative amounts of oxyhemoglobin and deoxyhemoglobin in tissue of patient 4. For example, if the amount of oxyhemoglobin in tissue of patient 4 decreases, the amount of VIS light detected by light detectors 40A, 40B increases, and the amount of NIR light detected by light detectors 40A, 40B decreases. Similarly, if the amount of oxygenated hemoglobin in the tissue of the patient 4 increases, the amount of VIS light detected by the photodetectors 40A, 40B decreases, and the amount of NIR light detected by the photodetectors 40A, 40B increases.

[0084] Although both SpO2 and StO2 measurements can employ the optical sensors of IMD 10 (e.g., light emitter 38 and light detector 40) to emit and sense light, SpO2 measurements can consume significantly more energy than StO2 measurements. In some instances, SpO2 measurements can consume up to three orders of magnitude (1,000 times) more power than StO2 measurements. Reasons for the inconsistent energy consumption include that SpO2 measurements may require light emitter 38 to be activated for up to 30 seconds, whereas StO2 measurements may require light emitter 38 to be activated for up to 5 seconds. Additionally, SpO2 measurements may require a sampling rate of up to 70 Hz, whereas StO2 measurements may require a sampling rate of up to 4 Hz.

[0085] Figure 3 is a demonstration of one or more techniques described herein Figure 1 and 2 10. FIGURE 10 is a functional block diagram of an example configuration of an IMD 10. In the example shown, IMD 10 includes electrodes 16, antenna 26, light emitter 38, processing circuitry 50, sensing circuitry 52, communication circuitry 54, memory 56, switching circuitry 58, sensor 62 including light detector 40, and power supply 68. In some examples, memory 56 includes computer-readable instructions that, when executed by processing circuitry 50, cause IMD 10 and processing circuitry 50 to perform the various functions attributed herein to IMD 10 and processing circuitry 50. Memory 56 may include any volatile, nonvolatile, magnetic, optical, or electrical medium, such as random access memory (RAM), read-only memory (ROM), nonvolatile RAM (NVRAM), electrically erasable programmable ROM (EEPROM), flash memory, or any other digital medium.

[0086] Processing circuitry 50 may include fixed-function circuitry and / or programmable processing circuitry. Processing circuitry 50 may include any one or more of the following: a microprocessor, a controller, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or equivalent discrete or analog logic circuitry. In some examples, processing circuitry 50 may include multiple components (e.g., any combination of one or more microprocessors, one or more controllers, one or more DSPs, one or more ASICs, or one or more FPGAs) as well as other discrete or integrated logic circuitry. The functionality attributed herein to processing circuitry 50 may be embodied in software, firmware, hardware, or any combination thereof.

[0087] Sensing circuitry 52 and communication circuitry 54 may be selectively coupled to electrodes 16A-16D via switching circuitry 58, as controlled by processing circuitry 50. Sensing circuitry 52 may monitor signals from electrodes 16A-16D to monitor electrical activity of the heart (e.g., to generate an ECG) and / or subcutaneous tissue impedance. Sensing circuitry 52 may also monitor signals from sensor 62, which may include photodetectors 40A, 40B and any additional photodetectors that may be positioned on IMD 10. In some examples, sensing circuitry 52 may include one or more filters and amplifiers for filtering and amplifying signals received from one or more of electrodes 16A-16D and / or photodetectors 40A, 40B.

[0088] Communication circuitry 54 may include any suitable hardware, firmware, software, or any combination thereof, for communicating with another device, such as external device 12, or another IMD or sensor, such as a pressure sensing device. Under the control of processing circuitry 50, communication circuitry 54 may receive downlink telemetry from external device 12 or another device, and send uplink telemetry to the device, via an internal or external antenna, such as antenna 26. In some examples, communication circuitry 54 may communicate with external device 12. Additionally, processing circuitry 50 may communicate with an external device (e.g., external device 12) and a Medtronic® device, such as a Medtronic® device developed by Medtronic plc of Dublin, Ireland. Computer networks such as the Internet communicate with networked computing devices.

[0089] A clinician or other user may retrieve data from IMD 10 using external device 12 or by using another local or networked computing device configured to communicate with processing circuitry 50 via communications circuitry 54. A clinician may also program parameters of IMD 10 using external device 12 or another local or networked computing device.

[0090] Power supply 68 is configured to deliver operating power to the components of IMD 10. Power supply 68 may include a battery and power generation circuitry for generating the operating power. In some examples, the battery is rechargeable to allow for extended operation. In some examples, recharging is achieved through proximal inductive interaction between an external charger and an inductive charging coil within external device 12. Power supply 68 may include any one or more of a number of different battery types, such as nickel-cadmium and lithium-ion batteries. Non-rechargeable batteries may be selected to last for several years, while rechargeable batteries may be inductively charged from an external device, for example, daily or weekly.

[0091] Figure 4A and Figure 4B is to demonstrate that one or more techniques described herein can be substantially similar to Figure 1-3 10 but may include one or more additional features. Figure 4A and 4B Components may not necessarily be drawn to scale but may be exaggerated to show details. Figure 4A is a block diagram of a top view of an example configuration of IMD 10A. Figure 4B is a block diagram of a side view of an example IMD 10B that may include insulating layers as described below.

[0092] Figure 4A is to show that it can be basically similar to Figure 1 A conceptual diagram of another example of an IMD 10A is shown. Figure 1-3 In addition to the components shown in Figure 4A The example of the IMD 10 shown in FIG. 1 may also include a body portion 72 and an attachment plate 74. The attachment plate 74 may be configured to mechanically couple the header assembly 32 to the body portion 72 of the IMD 10A. The body portion 72 of the IMD 10A may be configured to accommodate Figure 3 , such as one or more of the internal components of IMD 10 shown in FIG, such as processing circuitry 50, sensing circuitry 52, communication circuitry 54, memory 56, switching circuitry 58, and sensor 62. In some examples, body portion 72 may be formed of one or more of titanium, ceramic, or any other suitable biocompatible material.

[0093] Figure 4B is to show that it can contain basically similar Figure 1 A conceptual diagram of an example of components of IMD 10 is shown in FIG. 1B. Figure 1-3 In addition to the components shown in Figure 4B The example IMD 10B shown in FIG. 1 can also include a wafer-level insulating cover 76 that can help insulate electrical signals transmitted between electrodes 16A-16D and / or photodetectors 40A, 40B on housing 15B and processing circuitry 50. In some examples, insulating cover 76 can be positioned over open housing 15 to form a housing for the components of IMD 10B. One or more components of IMD 10B (e.g., antenna 26, light emitter 38, photodetectors 40A, 40B, processing circuitry 50, sensing circuitry 52, communication circuitry 54, switching circuitry 58, or any combination thereof) can be formed on the bottom side of insulating cover 76, such as using flip-chip technology. Insulating cover 76 can be flipped over onto housing 15B. When flipped over and placed onto housing 15B, the components of IMD 10B formed on the bottom side of insulating cover 76 can be positioned within gap 78 defined by housing 15B.

[0094] Insulating cover 76 can be configured so as not to interfere with the operation of IMD 10B. For example, one or more of electrodes 16A-16D can be formed or placed above or on top of insulating cover 76 and electrically connected to switching circuitry 58 via one or more through-holes (not shown) formed through insulating cover 76. Additionally, to enable the IMD to determine patient parameter values ​​(e.g., StO2 and SpO2), at least a portion of insulating cover 76 can be transparent to NIR or visible wavelengths emitted by light emitter 38 and detected by light detectors 40A, 40B, which in some examples can be positioned on the bottom side of insulating cover 76 as described above.

[0095] In some examples, light emitter 38 may include a filter between light emitter 38 and insulating cover 76 that can restrict the spectrum of emitted light to a narrow band. Similarly, light detectors 40A, 40B may include a filter between light detectors 40A, 40B and insulating cover 76 so that light detectors 40A, 40B detect light from a narrow spectrum, typically at wavelengths longer than the emission spectrum. Other optical elements that may be included in IMD 10B may include index matching layers, antireflective coatings, or optical barriers that can be configured to block light emitted laterally by light emitter 38 from reaching light detector 40.

[0096] Figure 5 is a block diagram illustrating an example configuration of components of external device 12 according to one or more techniques of this disclosure. Figure 5 In the example of , external device 12 includes processing circuitry 80 , communication circuitry 82 , storage 84 , user interface 86 , and power supply 88 .

[0097] In one example, processing circuitry 80 may include one or more processors configured to implement functions and / or process instructions for execution within external device 12. For example, processing circuitry 80 may be capable of processing instructions stored in storage device 84. Processing circuitry 80 may include, for example, a microprocessor, a DSP, an ASIC, an FPGA, or equivalent discrete or integrated logic circuitry, or a combination of any of the foregoing devices or circuitry. Thus, processing circuitry 80 may include any suitable structure for performing the functions attributed herein to processing circuitry 80, whether in hardware, software, firmware, or any combination thereof.

[0098] Communications circuitry 82 may include any suitable hardware, firmware, software, or any combination thereof, for communicating with another device, such as IMD 10. Under the control of processing circuitry 80, communications circuitry 82 may receive downlink telemetry from, and send uplink telemetry to, IMD 10 or another device.

[0099] Storage device 84 can be configured to store information within external device 12 during operation. Storage device 84 can include computer-readable storage media or a computer-readable storage device. In some examples, storage device 84 includes one or more of short-term memory and long-term memory. Storage device 84 can include, for example, RAM, DRAM, SRAM, a magnetic disk, an optical disk, flash memory, or various forms of EPROM or EEPROM. In some examples, storage device 84 is used to store data indicative of instructions to be executed by processing circuitry 80. Storage device 84 can be used by software or applications running on external device 12 to temporarily store information during program execution.

[0100] The data exchanged between external device 12 and IMD 10 may include operating parameters. External device 12 may transmit data including computer-readable instructions that, when implemented by IMD 10, may control IMD 10 to change one or more operating parameters and / or export collected data. For example, processing circuitry 80 may send an instruction to IMD 10 requesting IMD 10 to export collected data (e.g., data corresponding to StO2 measurements, data corresponding to SpO2 measurements, or data corresponding to other parameter measurements) to external device 12. In turn, external device 12 may receive the collected data from IMD 10 and store the collected data in storage device 84. Additionally or alternatively, processing circuitry 80 may export an instruction to IMD 10 requesting IMD 10 to update an electrode combination for stimulation or sensing.

[0101] A user, such as a clinician or patient 4, can interact with external device 12 via user interface 86. User interface 86 includes a display (not shown), such as an LCD or LED display or other type of screen, which processing circuitry 80 can utilize to present information related to IMD 10 (e.g., EGM signals obtained from at least one electrode or at least one electrode). In addition, user interface 86 can include an input mechanism for receiving input from the user. The input mechanism can include, for example, buttons, a keypad (e.g., an alphanumeric keypad), a peripheral pointing device, or a touch screen, or another input mechanism that allows a user to navigate a user interface presented by processing circuitry 80 of external device 12 and provide input. In other examples, user interface 86 also includes audio circuitry for providing auditory notifications, instructions, or other sounds to patient 4, receiving voice commands from patient 4, or both. Storage device 84 can include instructions for operating user interface 86 and for managing power supply 88.

[0102] The power supply 88 is configured to deliver operating power to the components of the external device 12. The power supply 88 may include a battery and a power generation circuit for generating the operating power. In some examples, the battery is rechargeable to allow for extended operation. Recharging can be accomplished by electrically coupling the power supply 88 to a cradle or plug connected to an alternating current (AC) outlet. Alternatively, recharging can be accomplished through proximal inductive interaction between an external charger and an inductive charging coil within the external device 12. In other examples, conventional batteries (e.g., nickel-cadmium or lithium-ion batteries) may be used. Alternatively, the external device 12 may be coupled directly to an AC outlet for operation.

[0103] Figure 6 is a block diagram illustrating an example system including access point 90, network 92, an external computing device such as server 94, and one or more other computing devices 100A-100N that may be coupled to IMD 10, external device 12, and processing circuitry 14 via network 92, in accordance with one or more techniques described herein. In this example, IMD 10 may communicate with external device 12 via a first wireless connection and with access point 90 via a second wireless connection using communication circuitry 54. Figure 6 In the example of , access point 90 , external device 12 , server 94 , and computing devices 100A- 100N are interconnected and can communicate with each other via network 92 .

[0104] The access point 90 may comprise a device connected to the network 92 via any of a variety of connections, such as a telephone dial-up, a digital subscriber line (DSL), or a cable modem connection. In other instances, the access point 90 may be coupled to the network 92 via different forms of connections, including wired connections or wireless connections. In some instances, the access point 90 may be a user device, such as a tablet or smartphone, that may be co-located with the patient. As discussed above, the IMD 10 may be configured to transmit data, such as current values ​​and heart failure status, to the external device 12. In addition, the access point 90 may query the IMD 10, such as periodically or in response to a command from the patient or the network 92, to retrieve a current value of the heart failure status as determined by the processing circuit system 50 of the IMD 10 or other operational data or patient data from the IMD 10. The access point 90 may then transmit the retrieved data to the server 94 via the network 92.

[0105] In some cases, server 94 may be configured to provide a secure storage site for data that has been collected from IMD 10 and / or external device 12. In some cases, server 94 may compile the data in a web page or other document for viewing by a trained professional, such as a clinician, via computing devices 100A-100N. Figure 6 One or more aspects of the system shown may be similar to that developed by Medtronic plc of Dublin, Ireland. It is implemented using the general network technologies and functions provided by the network.

[0106] In some examples, one or more of computing devices 100A-100N (e.g., device 100A) may be a tablet computer or other smart device located with a clinician, which the clinician can program to receive alerts and / or query IMD 10. For example, when patient 4 is between clinician visits, the clinician can access parameter values ​​associated with patient 4 (e.g., StO2 and SpO2 values) via device 100A to check patient 4's heart failure status as needed. In some examples, a user may enter instructions for a medical intervention for patient 4 into an application within device 100A, such as based on patient 4's heart failure status as determined by IMD 10 or based on other patient data known to the clinician. Device 100A may then transmit the instructions for performing the medical intervention to another computing device among computing devices 100A-100N located with patient 4 or a caregiver of patient 4 (e.g., device 100B). For example, such instructions for medical intervention may include instructions for changing medication dosage, timing, or selection, for scheduling a visit with a clinician, or for seeking medical attention. In another example, device 100B may issue an alert to patient 4 based on the patient's 4 heart failure status determined by processing circuitry 14, which may enable patient 4 to proactively seek medical attention before receiving instructions for medical intervention. In this way, patient 4 may be empowered to take actions as needed to address his or her heart failure status, which may help improve clinical outcomes for patient 4.

[0107] Figure 7 is a flowchart illustrating example operations for performing parameter measurements according to one or more techniques of the present disclosure. Figure 1 -4 IMD 10, external device 12 and processing circuit system 14 Figure 7 However, Figure 7 The techniques may be performed by different components of IMD 10 or by additional or alternative medical devices.

[0108] In some instances, IMD 10 may be an ICM that measures patient parameters for analysis to identify or monitor one or more patient conditions, such as heart failure, sleep apnea, or COPD. In other words, IMD 10 may be implanted in patient 4 to collect data that can be processed to identify the condition causing the symptoms patient 4 is experiencing, and IMD 10 may be implanted in patient 4 to monitor the identified patient condition and output an alert if the patient condition worsens. IMD 10 may be configured to measure a set of parameters including StO2, SpO2, patient motion (e.g., via a motion sensor signal), the amount of ambient light present in tissue, temperature, patient posture, respiratory rate, respiratory volume, heart rate, heart rate variability, tissue impedance associated with electrodes 16, or any combination thereof. Data corresponding to at least some of the set of parameters may be analyzed to identify or monitor the patient condition. However, parameter measurements consume energy, and IMD 10 may be powered by power supply 68 having a limited amount of charge. Thus, it may be beneficial to limit the amount of energy used to perform parameter measurements, particularly those that consume a relatively high amount of power. In some examples, processing circuitry 14 may include processing circuitry 50 of IMD 10, processing circuitry of external device 12, processing circuitry of another device, or any combination thereof.

[0109] like Figure 7 As shown, processing circuitry 14 determines whether it is time to begin evaluating a group of evaluations. The group of evaluations may be performed at an evaluation rate such that a uniform amount of time separates each successive evaluation in the group of evaluations. In this manner, processing circuitry 14 is configured to initiate an evaluation when it is "scheduled." For example, if it is time to perform an hourly, daily, weekly, or monthly evaluation, processing circuitry 14 may begin the evaluation.

[0110] At block 702, processing circuitry 14 determines whether it is time to perform an assessment. If it is not time to perform an assessment (the "no" branch of block 702), processing circuitry 14 again determines whether it is time to begin an assessment. If it is time to perform an assessment (the "yes" branch of block 702), processing circuitry 14 outputs instructions to perform a motion level measurement and an ambient light measurement (704). In some instances, processing circuitry 14 outputs instructions to perform a motion level measurement and an ambient light measurement to IMD 10. Subsequently, processing circuitry 14 receives data corresponding to the motion level measurement and data corresponding to the ambient light measurement (706). In some instances, processing circuitry 14 determines a motion level associated with patient 4 based on the data corresponding to the motion level measurement. Additionally, in some instances, processing circuitry 14 determines an amount of ambient light present in at least a portion of patient 4's tissue based on the data corresponding to the ambient light measurement. In some instances, the data corresponding to the motion level measurement is generated by a motion sensor of IMD 10, and the data corresponding to the ambient light measurement is generated by light detector 40 of IMD 10.

[0111] At block 708, processing circuitry 14 determines whether the motion level derived from the motion level measurement is below a threshold motion level. If the motion level is not below the threshold motion level (the "no" branch of block 708), the example operation returns to block 702 and the evaluation is complete. In other words, if the motion level is not below the threshold motion level, processing circuitry 14 may terminate the evaluation and initiate another evaluation some time later when it is time to perform another evaluation. If the motion level is indeed below the threshold motion level (the "yes" branch of block 708), processing circuitry 14 proceeds to determine whether the amount of ambient light derived from the ambient light measurement is below a threshold amount of ambient light (710).

[0112] If the amount of ambient light is not below the threshold amount of ambient light (the "no" branch of block 710), the example operation returns to block 702 and the evaluation is complete. In other words, if the amount of ambient light is not below the threshold amount of ambient light, then when it is time to perform another evaluation, processing circuitry 14 may terminate the evaluation and initiate another evaluation some time later. If the amount of ambient light is indeed below the threshold amount of ambient light (the "yes" branch of block 710), processing circuitry 14 outputs an instruction to perform an optical test measurement (712). In some examples, processing circuitry 14 outputs the instruction to perform an optical test measurement to IMD 10, causing IMD 10 to perform the optical test measurement to obtain an optical test signal. IMD 10 may then output the optical test signal to processing circuitry 14 for analysis.

[0113] In some examples, the threshold amount of ambient light represents a first threshold amount of ambient light. If the amount of ambient light is less than the first threshold amount of ambient light (“yes” branch of block 710), then in some cases, processing circuitry 14 may determine whether the amount of ambient light is less than a second threshold amount of ambient light ( Figure 7 (not shown). If the amount of ambient light is less than the second threshold amount of ambient light, example operations may proceed to block 712 and processing circuitry 14 outputs instructions to perform an optical test measurement to IMD 10. If the amount of ambient light is not less than the second threshold amount of ambient light, processing circuitry 14 outputs instructions to perform an optical test measurement and instructions to subtract the ambient light noise component from the data corresponding to the corresponding StO2 measurement to IMD 10. In this manner, if the amount of ambient light is less than the first threshold amount of ambient light and greater than or equal to the second threshold amount of ambient light, it may still be possible to perform an adequate StO2 measurement while subtracting or otherwise eliminating the ambient light noise component from the data corresponding to the StO2 measurement.

[0114] In some examples, the optical test measurement includes activating the optical sensors (e.g., light emitter 38 and light detector 40) of IMD 10. In some examples, the optical test signal generated by the optical test measurement may include a sequence of data points having a duration between one second and ten seconds. Additionally, the sequence may include a set of frequency components ranging from 4 Hertz (Hz) to 55 Hz. At block 714, processing circuitry 14 determines whether the optical test signal quality is sufficient. For example, processing circuitry 14 may analyze the set of frequency components of the optical test signal to determine whether the optical sensors of IMD 10 are currently capable of generating high-quality optical data. If processing circuitry 14 determines that the optical test signal quality is insufficient (the "no" branch of block 714), the example operation returns to block 702 and the evaluation is complete. In other words, if the optical test signal quality is insufficient, processing circuitry 14 may terminate the evaluation and initiate another evaluation at a later time when it is time to perform another evaluation. If processing circuitry 14 determines that the optical test signal quality is sufficient ("yes" branch of block 714), processing circuitry 14 is configured to output instructions to perform a StO2 measurement (716).

[0115] In some cases, processing circuitry 14 may output an instruction to IMD 10 to perform an StO2 measurement. The StO2 measurement may consume significantly more power from power supply 68 of IMD 10 than the ambient light measurement, motion level measurement, posture measurement, and optical test measurement. In fact, a single StO2 measurement may consume more energy than the combination of the motion level measurement, ambient light measurement, posture measurement, and optical test measurement used by processing circuitry 14 to determine whether to output an instruction to perform an StO2 measurement. Thus, although the motion level measurement, ambient light measurement, posture measurement, and optical test measurement consume energy, it may be beneficial to perform such measurements to avoid performing an StO2 measurement that potentially produces a low-quality StO2 value. In some instances, IMD 10 may continue to monitor motion, posture, and ambient light during the StO2 measurement to verify that these parameters remain relatively constant during the StO2 measurement. If any one or more of motion, posture, and ambient light deviate from acceptable values ​​relative to one or more thresholds during the StO2 measurement, processing circuitry 14 may output an instruction to abort the StO2 measurement.

[0116] The processing circuitry 14 may receive a StO2 value corresponding to a StO2 measurement (718). The processing circuitry 14 may then add the StO2 value to a set of StO2 values ​​(720), wherein each StO2 value corresponds to a respective StO2 measurement. Based on the set of StO2 values, the processing circuitry 14 may be configured to identify a trend in the StO2 values ​​(722). In some examples, to determine the trend in the StO2 values, the processing circuitry 14 may be configured to plot each StO2 value in the set of StO2 values ​​over time and determine whether the set of StO2 values ​​increases, decreases, or remains generally constant over a period of time. Additionally, in some examples, the processing circuitry 14 may be configured to identify a rate at which the StO2 values ​​are changing and also determine whether the StO2 values ​​exceed or fall below a threshold value for the StO2 value.

[0117] At block 724, the processing circuitry 14 is configured to determine whether the trend of the StO2 values ​​is stable. In some examples, if the set of StO2 values ​​decreases over a period of time, the processing circuitry 14 determines that the trend of the StO2 values ​​is unstable. This decrease in StO2 values ​​may indicate a worsening patient condition, such as heart failure. Alternatively, in some examples, if the set of StO2 values ​​remains relatively constant over a period of time, the processing circuitry 14 determines that the trend of the StO2 values ​​is stable. If the processing circuitry 14 determines that the trend of the StO2 values ​​is stable (the "yes" branch of block 724), the example operation returns to block 702. Subsequently, when it is time to perform another assessment, the processing circuitry 14 may initiate another assessment after a period of time. If the processing circuitry 14 determines that the trend of the StO2 values ​​is unstable (the "no" branch of block 724), the processing circuitry 14 may output an instruction to perform a pulse oximetry (SpO2) measurement (726). In some examples, processing circuitry 14 outputs an instruction to IMD 10 to perform an SpO2 measurement. In other examples, processing circuitry 14 outputs an instruction to perform an SpO2 measurement to another device configured to measure SpO2. In some examples, processing circuitry 14 outputs a prompt to an external device, and the external device displays a prompt instructing the user to perform an external SpO2 measurement. In examples where processing circuitry 14 outputs an instruction to IMD 10 to perform an SpO2 measurement, the SpO2 measurement may consume more energy from power supply 68 than the StO2 measurement. Thus, it may be beneficial to avoid performing an SpO2 measurement unless processing circuitry 14 determines that the trend of the StO2 value is unstable.

[0118] In some cases, StO2 may represent a weighted average of SaO2 and SvO2, with SvO2 being weighted higher than SaO2. SpO2 may be an approximation of SaO2 alone. In this manner, the SpO2 measurement may confirm whether the trend of the StO2 value is unstable due to SaO2 instability, or whether the trend of the StO2 value is unstable due to SvO2 instability. The processing circuit system 14 receives the SpO2 value corresponding to the SpO2 measurement (728). Subsequently, the processing circuit system 14 determines whether the SpO2 value confirms the trend of the StO2 value (730). In other words, if the processing circuit system 14 determines, based on the SpO2 value, that the trend of the StO2 value is unstable due to SaO2, then the processing circuit system 14 confirms the trend. Alternatively, in some instances, if the processing circuit system 14 determines, based on the SpO2 value, that the trend of the StO2 value is unstable due to a parameter other than SaO2, then the processing circuit system 14 does not confirm the trend. If the SpO2 value does not confirm the trend of the StO2 value (the "No" branch of block 730), the example operation returns to block 702. Subsequently, when it is time to perform another evaluation, the processing circuit system 14 may initiate another evaluation after a period of time. If the SpO2 value confirms the trend of the StO2 value (the "Yes" branch of block 730), the processing circuit system 14 outputs an alarm (732).

[0119] In some examples, processing circuit system 14 outputs an alert containing information that the patient's condition is worsening to any combination of external device 12, external server 98, or computing device 100. In other examples, processing circuit system 14 outputs the alert to Figure 1 -Another device not depicted in 4.

[0120] Figure 8 is a flowchart illustrating another example operation for performing parameter measurement according to one or more techniques of the present disclosure. Figure 1 -4 IMD 10, external device 12 and processing circuit system 14 Figure 8 However, Figure 8 The techniques may be performed by different components of IMD 10 or by additional or alternative medical devices.

[0121] In some instances, the IMD 10 can be an ICM that measures patient parameters for analysis to identify or monitor one or more patient conditions such as heart failure, sleep apnea, or COPD. In other words, the IMD 10 can be implanted in the patient 4 to collect data that can be processed to identify the condition causing the symptoms the patient 4 is experiencing, and the IMD 10 can be implanted in the patient 4 to monitor the identified patient condition and output an alarm if the patient condition worsens. The IMD 10 can be configured to measure a set of parameters including StO2, SpO2, patient motion (e.g., via a motion sensor signal), the amount of ambient light present in the tissue, temperature, patient posture, respiratory rate, respiratory volume, heart rate, heart rate variability, tissue impedance associated with the electrodes 16, or any combination thereof. Data corresponding to at least some of the parameters in the set can be analyzed to identify or monitor the patient condition. However, some parameter measurements may be noisy or of poor quality for another reason. Thus, in some examples, it may be beneficial to identify parameter measurements that may be of poor quality so that these low-quality parameter measurements can be excluded when analyzing the parameter measurements to identify or monitor a patient condition. In some examples, processing circuitry 14 may include processing circuitry 50 of IMD 10, processing circuitry of external device 12, processing circuitry of another device, or any combination thereof.

[0122] like Figure 8 As shown, processing circuitry 14 determines whether it is time to begin evaluating a group of evaluations. The group of evaluations may be performed at an evaluation rate such that a uniform amount of time separates each successive evaluation in the group of evaluations. In this manner, processing circuitry 14 is configured to initiate an evaluation when it is "scheduled." For example, if it is time to perform an hourly, daily, weekly, or monthly evaluation, processing circuitry 14 may begin the evaluation.

[0123] At block 802, processing circuitry 14 determines whether it is time to perform an assessment. If it is not time to perform an assessment (the "no" branch of block 802), processing circuitry 14 again determines whether it is time to begin an assessment. If it is time to perform an assessment (the "yes" branch of block 802), processing circuitry 14 outputs instructions to perform a motion level measurement and an ambient light measurement (804). In some instances, processing circuitry 14 outputs instructions to perform a motion level measurement and an ambient light measurement to IMD 10. Subsequently, processing circuitry 14 receives data corresponding to the motion level measurement and data corresponding to the ambient light measurement (806). In some instances, processing circuitry 14 determines a motion level associated with patient 4 based on the data corresponding to the motion level measurement. Additionally, in some instances, processing circuitry 14 determines an amount of ambient light present in at least a portion of patient 4's tissue based on the data corresponding to the ambient light measurement. In some instances, the data corresponding to the motion level measurement is generated by a motion sensor of IMD 10, and the data corresponding to the ambient light measurement is generated by light detector 40 of IMD 10.

[0124] At block 808, processing circuitry 14 determines whether the motion level derived from the motion level measurement is below a threshold motion level. If the motion level is not below the threshold motion level (the "no" branch of block 808), processing circuitry 14 marks the assessment as low quality (816). In other words, high motion levels may interfere with potential StO2 measurements by introducing noise into the StO2 measurement, and processing circuitry 14 may identify data associated with StO2 measurements performed under such high motion conditions as potentially low quality. If the motion level is indeed below the threshold motion level (the "yes" branch of block 808), processing circuitry 14 proceeds to determine whether the amount of ambient light derived from the ambient light measurement is below a threshold amount of ambient light (810).

[0125] If the amount of ambient light is not below the threshold amount of ambient light (the "No" branch of block 810), processing circuitry 14 marks the evaluation as low quality (816). In other words, a large amount of ambient light may interfere with the potential StO2 measurement by introducing noise into the StO2 measurement, and processing circuitry 14 may identify the data associated with the StO2 measurement performed under such high ambient light conditions as potentially low quality. If the amount of ambient light is indeed below the threshold amount of ambient light (the "Yes" branch of block 810), processing circuitry 14 outputs an instruction to perform an optical test measurement (812). In some examples, processing circuitry 14 outputs the instruction to perform the optical test measurement to IMD 10, causing IMD 10 to perform the optical test measurement to obtain an optical test signal. IMD 10 may then output the optical test signal to processing circuitry 14 for analysis.

[0126] In some examples, the threshold amount of ambient light represents a first threshold amount of ambient light. If the amount of ambient light is less than the first threshold amount of ambient light (the "yes" branch of block 810), then in some cases, the processing circuitry may determine whether the amount of ambient light is less than a second threshold amount of ambient light ( Figure 8 (not shown). If the amount of ambient light is less than the second threshold amount of ambient light, example operations may proceed to block 812 and processing circuitry 14 outputs instructions to perform an optical test measurement to IMD 10. If the amount of ambient light is not less than the second threshold amount of ambient light, processing circuitry 14 outputs instructions to perform an optical test measurement and instructions to subtract the ambient light noise component from the data corresponding to the corresponding StO2 measurement to IMD 10. In this manner, if the amount of ambient light is less than the first threshold amount of ambient light and greater than or equal to the second threshold amount of ambient light, it may still be possible to perform a “high quality” StO2 measurement while subtracting or otherwise eliminating the ambient light noise component from the data corresponding to the StO2 measurement.

[0127] In some instances, the optical test measurement includes activating the optical sensors (e.g., light emitter 38 and light detector 40) of IMD 10. In some instances, the optical test signal generated by the optical test measurement may include a sequence of data points having a duration between one second and ten seconds. Additionally, the sequence may include a set of frequency components ranging between 4 Hertz (Hz) and 55 Hz. At block 814, processing circuitry 14 determines whether the optical test signal quality is sufficient. For example, processing circuitry 14 may analyze the set of frequency components of the optical test signal to determine whether the optical sensors of IMD 10 are currently capable of generating high-quality optical data. If processing circuitry 14 determines that the optical test signal quality is insufficient (the "No" branch of block 814), processing circuitry 14 marks the evaluation as low quality (816). In other words, if the optical test signal is insufficient, the potential StO2 measurement may produce a low-quality StO2 value. If processing circuitry 14 determines that the optical test signal quality is adequate (“yes” branch of block 814 ), processing circuitry 14 is configured to mark the assessment as high quality ( 818 ).

[0128] In both cases where the processing circuitry 14 marks the assessment as low quality and where the processing circuitry 14 marks the assessment as high quality, the processing circuitry 14 outputs an instruction to perform a StO2 measurement (820). In some instances, the processing circuitry 14 outputs an instruction to perform a StO2 measurement to the IMD 10. Subsequently, the processing circuitry 14 receives data indicating a StO2 value (822) and adds the StO2 value to a set of StO2 values ​​(824). The processing circuitry 14 is configured to identify a trend of high-quality StO2 values ​​(826). In this manner, in some cases, the processing circuitry 14 can identify high-quality StO2 values ​​in the set of StO2 values. The high-quality StO2 values ​​correspond to StO2 measurements performed after the assessment was marked as high quality by the processing circuitry 14. In other words, the processing circuitry 14 can exclude low-quality StO2 values ​​while identifying a trend in the StO2 values. In this manner, the trend identified by the processing circuitry 14 is not affected by insufficient data points due to noise in an uneven measurement environment.

[0129] At block 828, the processing circuitry 14 is configured to determine whether the trend of the high-quality StO2 values ​​is stable. In some examples, if the high-quality StO2 values ​​decrease over a period of time, the processing circuitry 14 determines that the trend of the high-quality StO2 values ​​is unstable. This decrease in StO2 values ​​may indicate that a patient condition, such as heart failure, is worsening. Alternatively, in some examples, if the high-quality StO2 values ​​remain relatively constant over a period of time, the processing circuitry 14 determines that the trend of the StO2 values ​​is stable. If the processing circuitry 14 determines that the trend of the high-quality StO2 values ​​is stable (the "yes" branch of block 828), the example operation returns to block 802. Subsequently, when it is time to perform another assessment, the processing circuitry 14 may initiate another assessment after a period of time. If the processing circuitry 14 determines that the trend of the StO2 values ​​is unstable (the "no" branch of block 828), the processing circuitry 14 may output an instruction to perform a pulse oximetry (SpO2) measurement (830). In some examples, processing circuitry 14 outputs instructions to IMD 10 to perform an SpO2 measurement. In other examples, processing circuitry 14 outputs instructions to perform an SpO2 measurement to another device configured to measure SpO2. In examples where processing circuitry 14 outputs instructions to IMD 10 to perform an SpO2 measurement, an SpO2 measurement may consume more energy from power supply 68 than an StO2 measurement. Thus, it may be beneficial to avoid performing an SpO2 measurement unless processing circuitry 14 determines that the trend of the StO2 value is unstable.

[0130] The processing circuitry 14 receives an SpO2 value corresponding to the SpO2 measurement (832). The processing circuitry 14 then determines whether the SpO2 value confirms the trend of the StO2 value (834). In other words, if the processing circuitry 14 determines, based on the SpO2 value, that the trend of the StO2 value is unstable due to SaO2, then the processing circuitry 14 confirms the trend. Alternatively, in some examples, if the processing circuitry 14 determines, based on the SpO2 value, that the trend of the StO2 value is unstable due to a parameter other than SaO2, then the processing circuitry 14 does not confirm the trend. If the SpO2 value does not confirm the trend of the StO2 value (the "No" branch of block 834), the example operation returns to block 802. Subsequently, when it is time to perform another evaluation, the processing circuitry 14 may initiate another evaluation after a period of time. If the SpO2 value confirms the trend of the StO2 value (the "Yes" branch of block 834), then the processing circuitry 14 outputs an alert (836).

[0131] In some examples, processing circuit system 14 outputs an alert containing information that the patient's condition is worsening to any combination of external device 12, external server 98, or computing device 100. In other examples, processing circuit system 14 outputs the alert to Figure 1 -Another device not depicted in 4.

[0132] Figure 9 is a flow chart illustrating example operations for performing tissue oxygen saturation measurements using IMD 10 in accordance with one or more techniques described herein. Figure 1 -4 IMD 10 pairs Figure 9 However, Figure 9 The techniques may be performed by different components of IMD 10 or by additional or alternative medical devices.

[0133] When the IMD 10 performs an StO2 measurement, it may be beneficial to collect enough StO2 samples to ensure that the StO2 value determined based on the StO2 samples is sufficient (e.g., a greater number of StO2 samples collected during an StO2 measurement may improve the quality / accuracy / noise level of the StO2 value). Additionally, in some instances, it may be beneficial to limit the number of StO2 samples collected during an StO2 measurement to maintain a charge level of the power supply 68 that provides power to components of the IMD 10 (e.g., a greater number of StO2 samples causes the optical sensor to consume a greater amount of current). The IMD 10 may be configured to balance the number of StO2 samples collected by the IMD 10 during an StO2 measurement by determining a minimum number of StO2 samples for producing a StO2 value of sufficient quality.

[0134] like Figure 9As shown in FIG, the IMD 10 may receive an instruction to perform a StO2 measurement (902). The IMD 10 may receive an instruction from an external device 12, processing circuitry 14, or Figure 1 -4 receives the instruction. In some instances, IMD 10 receives the instruction from processing circuitry 50 of IMD 10 (which, in some cases, may be part of processing circuitry 14). In other instances, IMD 10 receives the instruction from another device via antenna 26 and communication circuitry 54. After receiving the instruction, IMD 10 collects a first sequence of StO2 samples, wherein the sequence includes M StO2 samples (904). In some instances, the sampling frequency of the first sequence of StO2 samples is between 2 Hz and 10 Hz. Additionally, in some instances, the duration of the sequence is between 5 seconds and 15 seconds. Each sample in the first sequence of StO2 samples may represent a sample StO2 value.

[0135] The processing circuitry 50 of the IMD 10 may calculate a standard deviation for the first sequence of StO2 samples (906). Based on the standard deviation, the processing circuitry 50 calculates a precision value associated with the first sequence of StO2 samples (908). A higher standard deviation may indicate a higher precision value, and a lower standard deviation may indicate a lower precision value. Based on the precision value, the processing circuitry 50 may determine a minimum number (N) of StO2 samples (910) required for an adequate StO2 measurement. The processing circuitry 50 may store the number of StO2 samples in a memory cell. Figure 9 The example operation is used as M for N in subsequent iterations of .

[0136] At block 912, the processing circuitry 50 determines whether the number of samples (M) included in the first sequence of StO2 samples is less than the minimum number of samples (N) required for an adequate StO2 measurement. If M is not less than N (the "No" branch of block 912), the IMD 10 may complete the StO2 measurement and output the first sequence of StO2 samples (914). If M is indeed less than N (the "Yes" branch of block 912), the IMD 10 may collect a second sequence of N StO2 samples (916). In some instances, the IMD 10 may subtract M from N to obtain a sample difference value and store the sample difference value in the memory 56. Subsequently, the IMD 10 may complete the StO2 measurement and output the second sequence of StO2 samples (918). In this manner, the IMD 10 may ensure that the StO2 measurement contains at least N samples, thereby improving the quality of the StO2 measurement by collecting a sufficient amount of data during each StO2 measurement.

[0137] Figure 10is a flow chart illustrating example operations for analyzing tissue oxygen saturation values ​​according to one or more techniques of the present disclosure. Figure 1 -4 IMD 10, external device 12 and processing circuit system 14 Figure 10 However, Figure 10 The techniques may be performed by different components of IMD 10 or by additional or alternative medical devices.

[0138] exist Figure 10 In the example operation of block 912, processing circuitry 14 determines whether to control IMD 10 to perform a StO2 measurement (1002). In some examples, processing circuitry 14 may determine whether to control IMD 10 to perform a StO2 measurement based on an evaluation performed by processing circuitry 14. In some cases, the evaluation may include an analysis of whether one or more parameters satisfy corresponding thresholds or corresponding threshold ranges. In some examples, processing circuitry 14 determines to control IMD 10 to perform a StO2 measurement at a measurement frequency (e.g., one measurement per hour, one measurement per day, or any other valid frequency). If processing circuitry determines not to control IMD 10 to perform a StO2 measurement (the "No" branch of block 912), the example operation returns to block 1002 and processing circuitry 14 reevaluates whether to control IMD 10 to perform a StO2 measurement.

[0139] If processing circuitry 14 determines to control IMD 10 to perform an StO2 measurement (the "yes" branch of block 912), processing circuitry 14 receives data corresponding to the StO2 measurement from IMD 10 (1004) and determines a tissue oxygen saturation value based on the data corresponding to the StO2 measurement (1006). In some instances, if processing circuitry 14 determines to control IMD 10 to perform an StO2 measurement, processing circuitry 14 may determine whether to classify the measurement as a high-quality measurement or a low-quality measurement based on the evaluation performed by processing circuitry 14. Processing circuitry 14 may choose to exclude low-quality measurements from the analysis. Processing circuitry 14 may obtain data indicating one or more values ​​of a set of parameters (1008). In some instances, the one or more values ​​are measured by IMD 10 within a time window corresponding to the time when the StO2 measurement is performed. In this manner, the one or more values ​​may reflect the current condition at the time the IMD 10 performs the StO2 measurement. In some examples, the set of parameters may include any combination of the following: the amount of ambient light present in the target tissue of patient 4, the optical sensor test signal, the temperature of the target tissue, the posture of patient 4 (e.g., sitting, standing, prone, or supine), respiratory rate, respiratory volume, heart rate, heart rate variability, and subcutaneous tissue impedance. By obtaining data indicative of one or more values ​​of the set of parameters, processing circuitry 14 may be configured to classify the tissue oxygen saturation value based on the set of parameters.

[0140] For example, processing circuitry 14 may associate one or more values ​​of the set of parameters with a tissue oxygen saturation value (1010) and add the tissue oxygen saturation value to a set of tissue oxygen saturation values ​​(1012). In some cases, each tissue oxygen saturation value in the set of tissue oxygen saturation values ​​is associated with a corresponding StO2 measurement that corresponds to the corresponding one or more values ​​of the set of parameters. In this manner, these values, which may indicate the condition at which IMD 10 performed the corresponding StO2 measurement, may enable processing circuitry 14 to perform one or more customized analyses of the set of tissue oxygen saturation values. For example, processing circuitry 14 analyzes the set of tissue oxygen saturation values ​​based on at least a subset of the set of parameters (1014).

[0141] In some cases, processing circuitry 14 may determine a first subset of tissue oxygen saturation values ​​within the set of tissue oxygen saturation values ​​that correspond to StO2 measurements performed while patient 4 was lying in a supine position. Additionally, in some cases, processing circuitry 14 may determine a second subset of tissue oxygen saturation values ​​within the set of tissue oxygen saturation values ​​that correspond to StO2 measurements performed while patient 4 was lying in a prone position. In this manner, processing circuitry may be configured to compare tissue oxygen data corresponding to patient 4 lying supine with tissue oxygen data corresponding to patient 4 lying prone. The analysis is not limited to a supine / prone comparison. Processing circuitry 14 may divide the set of tissue oxygen saturation values ​​into any number of subsets and perform analysis based on any of the set of parameters.

[0142] Figure 11 is a graph showing a hemoglobin oxygen saturation / oxygen partial pressure graph 1100 according to one or more techniques of the present disclosure. For example, Figure 11 A plot line 1110 is included that tracks the relationship between the percent hemoglobin oxygen saturation and the partial pressure of oxygen. In some examples, the partial pressure of oxygen represents the true potential oxygen delivery capacity of whole blood.

[0143] like Figure 11 As shown in , when the hemoglobin oxygen saturation is greater than 90% (e.g., between 92% and 97%), there is a relatively low oxygen saturation sensitivity to the oxygen partial pressure in the solution. In other words, a small change in SaO2 corresponds to a large change in oxygen partial pressure. In contrast, for venous blood, in some cases, where SvO2 may occupy a range between 60% and 80%, there is a relatively high oxygen saturation sensitivity to the oxygen partial pressure in the solution. In other words, a large change in SvO2 corresponds to a small change in oxygen partial pressure. The venous oxygen partial pressure is related to the arterial blood by the flow rate and metabolism of the local tissue within the range of the optical sensor of the IMD 10. For example, if the arterial oxygen saturation, flow, and local metabolism do not change, the venous oxygen saturation, flow, and local metabolism may also remain constant.

[0144] Thus, while StO2 may represent a weighted average of SaO2 and SvO2, if patient 4's SaO2 remains stable, then patient 4's StO2 is also likely to remain stable under conditions of substantially constant metabolism and substantially constant cardiac output. Furthermore, if patient 4's SaO2 changes, then patient 4's StO2 may also change. However, the reverse is not always true. For example, in some cases, if StO2 changes, such changes may be caused by changes in blood flow or changes in local tissue oxygen metabolism—rather than changes in SaO2. At least in part for this reason, performing an SpO2 measurement in response to determining that the trend of the StO2 value is unstable may be beneficial. Because the SpO2 value indicates SaO2, performing an SpO2 measurement using IMD 10 can confirm whether changes in StO2 are related to corresponding changes in SaO2 or whether changes in StO2 are related to other parameters, such as SvO2, blood flow, or local tissue oxygen metabolism. Measuring additional parameters, such as impedance measurements and Doppler blood flow measurements, can help further distinguish blood flow from local tissue metabolism. Although SpO2 is a good indicator of SaO2, StO2 can also be a good indicator of SaO2. In other words, under conditions of substantially constant metabolism and substantially constant cardiac output, tracking changes in StO2 values ​​can be useful for tracking changes in SaO2 over a period of time.

[0145] Local tissue oxygen metabolism may affect StO2. For example, in some cases, muscle tissue may lose its ability to metabolize oxygen. In some such cases, StO2 may increase for a period of time. In other such cases, StO2 may remain constant if local tissue metabolism and blood flow decrease, or if SaO2 decreases. For example, in the case of patient 4 suffering from heart failure, patient 4's cardiac output capacity may decrease, and patient 4's muscle tissue may lose its metabolic capacity. However, it may be uncommon or even rare for these competing effects to not cause changes in StO2.

[0146] The techniques described in this disclosure may be implemented, at least in part, in hardware, software, firmware, or any combination thereof. For example, various aspects of these techniques may be implemented in one or more processors, DSPs, ASICs, FPGAs, or any other equivalent integrated or discrete logic QRS circuit systems, as well as any combination of such components, which are embodied in external devices such as physician or patient programmers, simulators, or other devices. The terms "processor" and "processing circuit system" may generally refer to any of the aforementioned logic circuit systems, alone or in combination with other logic circuit systems, or any other equivalent circuit systems, alone or in combination with other digital or analog circuit systems.

[0147] For various aspects implemented in software, at least some of the functionality attributed to the systems and devices described in this disclosure may be embodied as instructions on a computer-readable storage medium, such as RAM, DRAM, SRAM, magnetic disk, optical disk, flash memory, or various forms of EPROM or EEPROM. The instructions may be executed to support one or more aspects of the functionality described in this disclosure.

[0148] In addition, in some aspects, the functionality described herein can be provided within dedicated hardware and / or software modules. Depicting different features as modules or units is intended to highlight different functional aspects and does not necessarily imply that such modules or units must be implemented by separate hardware or software components. Instead, the functionality associated with one or more modules or units can be performed by separate hardware or software components, or integrated into shared or separate hardware or software components. Moreover, the technology can be implemented entirely in one or more circuits or logic elements. The technology disclosed herein can be implemented in a variety of devices or equipment, including an IMD, an external programmer, a combination of an IMD and an external programmer, an integrated circuit (IC) or a group of ICs, and / or a discrete circuit system resident in the IMD and / or the external programmer.

Claims

1. A medical device system comprising: an optical sensor configured to measure ambient light and tissue oxygen saturation parameters; as well as processing circuitry configured to: determining that a current measurement of the tissue oxygen saturation parameter is prompted; controlling the optical sensor to perform an ambient light measurement associated with the current measurement of the tissue oxygen saturation parameter; and Determine at least one of the following based on the ambient light measurement: whether to control the optical sensor to perform the current measurement of the tissue oxygen saturation parameter, when controlling the optical sensor to perform the current measurement of the tissue oxygen saturation parameter, or whether to include the current measurement of the tissue oxygen saturation parameter in a trend of the tissue oxygen saturation parameter, Wherein, when the processing circuit system determines to control the optical sensor to perform the current measurement of the tissue oxygen saturation parameter, the processing circuit system is further configured to: receiving data corresponding to the current measurement of the tissue oxygen saturation parameter from the optical sensor; determining a tissue oxygen saturation value based on the data corresponding to the current measurement of the tissue oxygen saturation parameter; and adding the tissue oxygen saturation value to a set of tissue oxygen saturation values, wherein each tissue oxygen saturation value in the set of tissue oxygen saturation values ​​is associated with a corresponding measurement of the tissue oxygen saturation parameter, wherein the processing circuitry is further configured to: identifying the trend in the tissue oxygen saturation parameter based on the set of tissue oxygen saturation values; determining whether the trend of the tissue oxygen saturation parameter is stable; and In response to determining that the trend of the tissue oxygen saturation parameter is unstable, control performs a pulse oximetry measurement associated with the current measurement of the tissue oxygen saturation parameter.

2. The medical device system of claim 1 , further comprising a motion sensor configured to measure motion of the patient, wherein the processing circuitry is further configured to: controlling the motion sensor to perform an exercise level measurement associated with the current measurement of the tissue oxygen saturation parameter; and At least one of whether to control the optical sensor to perform the current measurement, when to control the optical sensor to perform the current measurement, or whether to include the current measurement in the trend is determined based on the ambient light measurement and the motion level measurement.

3. The medical device system of claim 2 , wherein to determine at least one of whether to control the optical sensor to perform the current measurement, when to control the optical sensor to perform the current measurement, or whether to include the current measurement in the trend, the processing circuitry is configured to: receiving data corresponding to the ambient light measurement from the optical sensor; receiving data corresponding to the motion level measurement from the motion sensor; determining an exercise level associated with the patient based on the data corresponding to the exercise level measurement; determining an amount of ambient light present in target tissue based on the data corresponding to the ambient light measurement; comparing the activity level to a threshold activity level; and The amount of ambient light is compared to a threshold amount of ambient light.

4. The medical device system of claim 3, wherein the optical sensor is further configured to measure an optical sensor test signal, and wherein the processing circuitry is further configured to: controlling the optical sensor to perform an optical sensor test measurement associated with the current measurement of the tissue oxygen saturation parameter; and At least one of whether to control the optical sensor to perform the current measurement, when to control the optical sensor to perform the current measurement, or whether to include the current measurement in the trend is determined based on the ambient light measurement, the motion level measurement, and the optical sensor test measurement.

5. The medical device system of claim 4 , wherein to determine at least one of whether to control the optical sensor to perform the current measurement, when to control the optical sensor to perform the current measurement, or whether to include the current measurement in the trend, the processing circuitry is further configured to: receiving an optical sensor test signal from the optical sensor corresponding to the optical sensor test measurement; and A determination is made based on the optical sensor test signal whether the optical sensor test signal quality is sufficient.

6. The medical device system of claim 5 , wherein the processing circuitry is configured to determine not to control the optical sensor to perform the current measurement of the tissue oxygen saturation parameter if: the activity level being greater than or equal to the threshold activity level; the amount of ambient light is greater than or equal to a threshold amount of ambient light; or The optical sensor test signal quality is insufficient, and wherein the processing circuit system is configured to determine to control the optical sensor to perform the current measurement of the tissue oxygen saturation parameter if: the activity level being less than the threshold activity level; The amount of ambient light is less than a threshold amount of ambient light; and The optical sensor test signal quality is sufficient.

7. The medical device system of claim 5 , wherein the processing circuitry is configured to determine not to include the current measurement of the tissue oxygen saturation parameter in the trend of the tissue oxygen saturation parameter if: the activity level being greater than or equal to the threshold activity level; the amount of ambient light is greater than or equal to a threshold amount of ambient light; or The optical sensor test signal quality is insufficient, and wherein the processing circuitry is configured to determine that the current measurement of the tissue oxygen saturation parameter is to be included in the trend of the tissue oxygen saturation parameter if: the activity level being less than the threshold activity level; The amount of ambient light is less than a threshold amount of ambient light; and The optical sensor test signal quality is sufficient.

8. The medical device system of claim 2, further comprising a medical device comprising a set of sensors including the optical sensor, the motion sensor, and one or more electrodes.

9. The medical device system of claim 8, wherein the medical device comprises an implantable medical device (IMD) implanted outside the patient's chest.

10. The medical device system of claim 8, wherein if the processing circuitry determines to control the optical sensor to perform the current measurement, the processing circuitry is configured to: receiving data corresponding to the current measurement of the tissue oxygen saturation parameter from the optical sensor; determining a tissue oxygen saturation value based on the data corresponding to the current measurement of the tissue oxygen saturation parameter; and The tissue oxygen saturation value is classified based on a set of parameters measured by the set of sensors.

11. The medical device system of claim 10, wherein to classify the current measurement, the processing circuitry is configured to: obtaining data indicative of one or more values ​​of the set of parameters, wherein the one or more values ​​are measured within a time window associated with a time at which the current measurement is performed; associating the one or more values ​​of the set of parameters with the tissue oxygen saturation value; adding the tissue oxygen saturation value to a set of tissue oxygen saturation values, wherein each tissue oxygen saturation value in the set of tissue oxygen saturation values ​​is associated with a respective measurement of the tissue oxygen saturation parameter, the respective measurement corresponding to the respective one or more values ​​of the set of parameters; and The set of tissue oxygen saturation values ​​is analyzed based on at least a subset of the set of parameters.

12. A medical device system according to claim 10, wherein the group parameters include any one or more of the following: the amount of ambient light present in the target tissue, an optical sensor test signal, the temperature of the target tissue, the patient's posture, respiratory rate, respiratory volume, heart rate, heart rate variability, tissue hemoglobin index (THI) value or subcutaneous tissue impedance.

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