System to calibrate blood pressure values optically derived using an implantable medical device

Abstract

An example system includes a first blood pressure (BP) sensing device configured to sense a pulse pressure waveform of a patient; and one or more computing devices configured to: receive the pulse pressure waveform, wherein the pulse pressure waveform is configured to conform to BP parameters determined by a second BP sensing device, the second BP sensing device being different than the first BP sensing device; and apply the pulse pressure waveform to calibrate a model to determine BP values of the patient using one or more optical signals sensed by an optical sensor.

Description

SYSTEM TO CALIBRATE BLOOD PRESSURE VALUES OPTICALLY DERIVED USING AN IMPLANTABLE MEDICAL DEVICE

[0001] This application claims the benefit of U.S. Provisional Patent Application Serial No. 63 / 610,904, filed December 15, 2023, the entire content of which is incorporated herein by reference.TECHNICAL FIELD

[0002] This disclosure generally relates to determining and / or predicting blood pressure values.BACKGROUND

[0003] Hypertension represents a key factor into the development of cardiovascular disease. 1 out of 3 adults in the United States are diagnosed with hypertension every year. Uncontrolled hypertension dramatically increases risk for maladies, such as coronary artery disease, congestive heart failure, renal failure, eyesight damage and stroke. Consequently, blood pressure measurement and monitoring is a key indicator critical to treatment and management of a patient’s health.SUMMARY

[0004] In general, this disclosure is directed to techniques for determining measurements of blood pressure (BP) using an optically derived arterial pulse pressure waveform. The optically derived pulse pressure waveform may be a waveform where arterial blood flow is within the field of the optical sensor, which may be carried by an insertable cardiac monitor (ICM) or other implantable medical device (IMD). Processing circuitry of the IMD or another device of a medical system including the IMD may determine and / or predict systolic and diastolic BP values based on the optically derived waveform.

[0005] However, measurement or prediction of BP based on optically derived signals may have challenges with measurement / prediction accuracy. One challenge with calibration of the BP measurement / prediction is the conversion of units as optically derived signals are provided in units of millivolts whereas BP measurements are provided in units of millimeters of mercury (mmHg).

[0006] Addressing these challenges with optically derived BP values may include normalization and / or calibration such that the optically derived BP values correspond to values produced by an external BP detection systems, such as sphygmomanometer systems. However, using systolic and / or diastolic values from other BP sensing devices, such as a sphygmomanometer, to calibrate an algorithm or model for optically derived BP values only relies on the maximum (e.g., systolic) and minimum (e.g., diastolic) value of an arterial pulse pressure waveform to calibrate an algorithm that may provide unreliable and inaccurate optically derived BP values, which may make the optically derived BP values ineffective and not useful.

[0007] The present disclosure describes techniques to apply sensed pulse pressure waveforms to calibrate the algorithm or model that determines BP based on optically derived arterial pulse pressure waveforms, such as optically derived signals sensed by an optical sensor. A system may include a first BP sensing device, such as a tonometer, configured to sense a non-optical pulse pressure waveform. A system may further include one or more computing devices configured to receive the sensed pulse pressure waveform. The pulse pressure waveform is configured to conform to BP parameters, such as diastolic values and / or systolic values, sensed by a second BP sensing device, such as a sphygmomanometer that is separate from the first BP sensing device. The one or more computing devices may be configured to apply the sensed pulse pressure waveform to calibrate a model configured to determine and / or predict BP values of the patient using one or more optical signals sensed by an optical sensor, which provides a more reliable and accurate calibrated model that enables more reliable and accurate continuous BP sensing by an optical sensor positioned on an IMD. Unlike using two fiducial points of an arterial pulse pressure waveform (e.g., systolic and diastolic values) to calibrate an algorithm for optically derived BP values, the techniques described herein applies an entire tuned arterial pulse pressure waveform, that includes all the fiducial points on the waveform, to calibrate a model configured to determine and / or predict BP values of the patient using one or more optical signals sensed by an optical sensor, which provides a more reliable and accurate calibrated model that enables more reliable and accurate continuous BP sensing by an optical sensor positioned on an IMD. In this manner, the optically derived pulse pressure waveforms of the IMD may be useful which results in an improved and more useful medical system and an improved and more useful IMD.

[0008] To calibrate the model, the one or more computing devices may apply sensed arterial pulse pressure waveforms, e.g., continuous waveform segments, that are configured to conform to BP parameters sensed by the second BP sensing device. The calibration may enable to the system to optically derive BP values using the IMD continuously, e.g., autonomously and on a periodic and / or triggered basis without human intervention, while the IMD is subcutaneously implanted in a patient over months or years.

[0009] Processing circuitry of a system including the IMD may use the calibrated model and optical signal(s) sensed by the IMD and / or features derived from the optical signal(s) to determine / predict BP values and determine a health condition status of the patient based on the determined BP values, e.g., changes in the BP values over a period of time. Calibration of the model according to the techniques described herein may improve sensitivity and / or specificity of the optically derived BP measurements, including BP changes over time, and any health condition status determined therefrom. In some examples, improving the sensitivity and / or specificity of BP measurements, including BP changes over a period of time may facilitate more accurate determinations of hypertension, cardiac wellness, and risk of sudden cardiac death, and may lead to clinical interventions to suppress hypertension such as medications and ablations.

[0010] In one example, this disclosure describes a system comprising: a first blood pressure (BP) sensing device configured to sense a pulse pressure waveform of a patient; and one or more computing devices configured to: receive the pulse pressure waveform, wherein the pulse pressure waveform is configured to conform to BP parameters determined by a second BP sensing device, the second BP sensing device being different than the first BP sensing device; and apply the pulse pressure waveform to calibrate a model to determine BP values of the patient using one or more optical signals sensed by an optical sensor.

[0011] In another example, this disclosure describes an implantable medical device (IMD) comprising: a housing configured for subcutaneous implantation at a location within a patient; an optical sensor, the optical sensor being at least one of on or within the housing, the optical sensor configured to sense one or more optical signals indicative of blood movement in vessels of the patient proximate to the location over a period of time; and processing circuitry configured to: receive a pulse pressure waveform from a computing device, the pulse pressure waveform is sensed by a first blood pressure (BP)sensing device and configured to conform to BP parameters determined by a second BP sensing device, the second BP sensing device being different than the first BP sensing device; and apply the pulse pressure waveform to calibrate a model to determine BP values of the patient using the one or more optical signals sensed by the optical sensor.

[0012] In another example, this disclosure describes a method for operating a medical system comprising: sensing, by a first blood pressure (BP) sensing device, a pulse pressure waveform of a patient; receiving, by processing circuitry, the pulse pressure waveform; and applying, by the processing circuitry, the pulse pressure waveform to calibrate a model to determine BP values of the patient using one or more optical signals sensed by an optical sensor.

[0013] Further details of one or more examples of this disclosure are set forth in the accompanying drawings and in the description below. Other features, objects, and advantages will be apparent from the description and drawings, and from the claims.

[0014] The above summary is not intended to describe each illustrated example or every implementation of the present disclosure.BRIEF DESCRIPTION OF DRAWINGS

[0015] FIG. 1A is a conceptual diagram illustrating an example system for calibrating a model to determine and / or predict BP values, in accordance with some examples of the current disclosure.

[0016] FIG. IB is a block diagram illustrating an example system that includes an access point, a network, external computing devices, such as a server, and one or more other computing devices, which may be coupled to the IMD and / or computing device of FIGS. 1A, in accordance with some examples of the current disclosure.

[0017] FIG. 2A is a block diagram illustrating an example configuration of the IMD of FIGS. 1A and IB, in accordance with some examples of the current disclosure.

[0018] FIG. 2B is a block diagram illustrating an example configuration of a computing device, in accordance with some examples of the current disclosure.

[0019] FIGS. 3A-3B are conceptual diagrams of sensing and conforming pulse pressure waveforms in accordance with some examples of the current disclosure.

[0020] FIG. 4A is a conceptual perspective diagram illustrating an example configuration of the IMD of FIGS. 1A-2A.

[0021] FIG. 4B is a schematic diagram illustrating an example configuration of the IMD of FIGS. 1A-2A.

[0022] FIG. 4C is a conceptual perspective diagram illustrating an example configuration of the IMD of FIGS. 1A-2A.

[0023] FIG. 5 is a flow diagram illustrating an example technique for calibrating a model to determine and / or predict BP values, in accordance with some examples of the current disclosure.DETAILED DESCRIPTION

[0024] A variety of types of medical devices sense blood pressure (BP) of patient. An implantable medical device (IMD) may include an optical sensor configured to sense optical signals from which processing circuitry of a system including the IMD may determine / predict BP values. The optical sensor may be integrated with a housing of the IMD and / or coupled to the IMD via an elongated lead. Example IMDs that may be configured to sense optical signals that may be used to monitor BP include pacemakers and implantable cardioverter-defibrillators, which may be coupled to intravascular or extravascular leads, as well as pacemakers with housings configured for implantation within the heart, which may be leadless. An example of pacemaker configured for intracardiac implantation is the Micra™ Transcatheter Pacing System, available from Medtronic, Inc. Some IMDs that do not provide therapy, e.g., implantable patient monitors, may be configured to sense optical signals that may be used to monitor BP. One example of such an IMD is the Reveal LINQ™ and LINQ II™ Insertable Cardiac Monitors (ICMs), available from Medtronic, Inc., which may be inserted subcutaneously. Such IMDs may facilitate relatively longer-term monitoring of patients during normal daily activities, and may periodically transmit collected data to a network service, such as the Medtronic Carelink™ Network.

[0025] FIG. 1A is a conceptual diagram illustrating an example system 100 for calibrating a model that is configured be applied by processing circuitry to determine and / or predict BP values of patient 18 using one or more optical signals sensed by an optical sensor positioned in IMD 10. As shown in FIG. 1, system 100 may include one or more computing device(s) 12, a first BP sensing device 15, a second BP sensing device 17, and IMD 10. Computing device 12 may be a computing device used in a home,ambulatory, clinic, or hospital setting. Computing device 12 may include, for example, a clinician programmer, a desktop computer, a laptop computer, a workstation, a server, a mainframe, a cloud computing system, a smartphone (e.g., of patient 18 or a clinician caregiver), combinations thereof, or the like. Computing device 12 may be configured to receive, via a user interface device 14 (“UI 14”), input from a user, such as a clinician, output information to a user, or both. In some examples, UI 14 may include a display (e.g., a liquid crystal display (LCD) or light emitting diode (LED) display), such as a touch- sensitive display; one or more buttons; one or more keys (e.g., a keyboard); a mouse; one or more dials; one or more switches; a speaker; one or more lights; combinations thereof; or the like.

[0026] Computing device 12 may be communicatively coupled to one or more of IMD 10, first BP sensing device 15 and / or second BP sensing device 17.

[0027] With every contraction of the left ventricle of the heart, the left ventricle ejects blood to generate a pressure pulse that travels throughout the arteries of the patient. This pulse is detectable at various locations of a patient, including at various subcutaneous implantable positions. In some examples, IMD 10 may be configured to be implanted subcutaneously in patient 18 and may include an optical sensor(s) 62 (as shown in FIG. 2A and FIGS. 4A-4C) configured to sense optical signal(s) indicative of BP values of patient 18. In some examples, IMD 10 may include electrodes and other sensors 61 (as shown in FIG. 2A), in addition to optical sensor(s) 62 to sense physiological signals of patient 4, and may collect and store physiological data and detect episodes based on such signals. Some examples of physiological signals that may be sensed by such devices may include BP, electrocardiogram (ECG) signals, heart rate, cardiac output, heart sounds, impedance, cardiac motion, respiration signals, perfusion signals, activity and / or posture signals, pressure signals, blood oxygen saturation signals, body composition, fluid impedance signals, and blood glucose or other blood constituent signals. In some examples, the optical sensor(s) 62 of IMD 10 includes a photo detector and a photo emitter. In some examples, IMD 10 takes the form of the Reveal LINQ™ or LINQ II ICM™, or another ICM similar to, e.g., a version or modification of, the LINQ™ ICMs.

[0028] Computing device 12 may be communicatively coupled to first BP sensing device 15 configured to sense a non-optical pulse pressure waveform of a patient 18, such as an arterial pulse pressure waveform. In some examples, first BP sensing device 15 maybe a tonometer, such as an applanation tonometer. In some examples, computing device 12 may include first BP sensing device 15. For example, computing device 12 may be a smartphone and may include the first BP sensing device 15 located at a position on the smartphone to sense physiological signals of patient 18. Some examples of physiological signals that may be sensed by such devices may include BP, pulse pressure waveforms, arterial pulse pressure waveform, BP parameters, and / or pressure signals. In some examples, first BP sensing device 15 may include sensors configured to contact the skin of the patient to sense physiological signals of patient 18. In some examples, second BP sensing device 17 may be configured to determine BP parameters, such as diastolic and / or systolic values, of patient 18. For example, second BP sensing device 17 may be a sphygmomanometer. In some examples, a user, such as a patient 18 or clinician, may enter values of BP parameters determined by second BP sensing device 17 into computing device 12.

[0029] FIG. IB is a block diagram illustrating an example system 110 that includes an access point 20, a network 22, external computing devices, such as a server 24, and one or more other computing devices 3OA-3ON (collectively, “computing devices 30”), which may be coupled to IMD 10 and external device 23 via network 22, in accordance with one or more techniques described herein. In this example, IMD 10 may use communication circuitry 54 (FIG. 2B) to communicate with external device 23 via a first wireless connection, and to communicate with an access point 20 via a second wireless connection. In the example of FIG. IB, access point 20, external device 23, server 24, and computing devices 30 are interconnected and may communicate with each other through network 22. In some examples, external device 23 in FIG. IB may be computing device 12 as shown in FIG. 1A.

[0030] Access point 20 may include a device that connects to network 22 via any of a variety of connections, such as telephone dial-up, digital subscriber line (DSL), or cable modem connections. In other examples, access point 20 may be coupled to network 22 through different forms of connections, including wired or wireless connections. In some examples, access point 20 may be a user device, such as a tablet or smartphone, that may be co-located with the patient. IMD 10 may be configured to transmit data, such as optical signal(s), to access point 20. Access point 20 may then communicate the retrieved data to server 24 via network 22.

[0031] In some cases, server 24 may be configured to provide a secure storage site for data that has been collected from IMD 10 and / or external device 23. In some cases, server 24 may assemble data in web pages or other documents for viewing by trained professionals, such as clinicians, via computing devices 30. One or more aspects of the illustrated system of FIG. IB may be implemented with general network technology and functionality, which may be similar to that provided by the Medtronic CareLink® Network. In some examples, server 24 may communicate with computing device 30 via network 22. For example, server 24 may communicate an analysis of data and / or results of an application of data, such as application of the sensed pulse pressure waveform to calibrate a model, to computing device 30, external device 23, or any other computing device via network 22. For example, server 24 may communicate a calibrated model that is calibrated based on the sensed pulse pressure waveform(s) to computing device 30, external device 23, or any other computing device via network 22.

[0032] In some examples, one or more of computing devices 30 may be a tablet or other smart device located with a clinician, by which the clinician may program, receive alerts from, and / or interrogate IMD 10. For example, the clinician may access data collected by IMD 10 through a computing device 30, such as when patient 4 is in in between clinician visits, to check on a status of a medical condition. In some examples, the clinician may enter instructions for a medical intervention for patient 4 into an application executed by computing device 30, such as based on a status of a patient condition determined by IMD 10, external device 23, server 24, or any combination thereof, or based on other patient data known to the clinician. Device 30 then may transmit the instructions for medical intervention to another of computing devices 30 located with patient 4 or a caregiver of patient 4. For example, such instructions for medical intervention may include an instruction to change a drug dosage, timing, or selection, to schedule a visit with the clinician, or to seek medical attention. In further examples, a computing device 30 may generate an alert to patient 4 based on a status of a medical condition of patient 4, which may enable patient 4 proactively to seek medical attention prior to receiving instructions for a medical intervention. In this manner, patient 4 may be empowered to take action, as needed, to address his or her medical status, which may help improve clinical outcomes for patient 4.

[0033] In the example illustrated by FIG. IB, server 24 includes a storage device 26, e.g., to store data retrieved from IMD 10, and processing circuitry 28. Although not illustrated in FIG. IB computing devices 30 may similarly include a storage device and processing circuitry. Processing circuitry 28 may include one or more processors that are configured to implement functionality and / or process instructions for execution within server 24. For example, processing circuitry 28 may be capable of processing instructions stored in memory 26. Processing circuitry 28 may include or be coupled to communication circuitry that may include any suitable hardware, firmware, software or any combination thereof for communicating with another device. In some examples, a description of processing circuitry 28 outputting a signal, such as a classification, may include processing circuitry 28 causing communication circuitry of server 4 to output the signal. Processing circuitry 28 may include, for example, microprocessors, DSPs, ASICs, FPGAs, or equivalent discrete or integrated logic circuitry, or a combination of any of the foregoing devices or circuitry. Accordingly, processing circuitry 28 may include any suitable structure, whether in hardware, software, firmware, or any combination thereof, to perform the functions ascribed herein to processing circuitry 28.

[0034] Processing circuitry of computing device 12, processing circuitry 28 of server 24 and / or the processing circuity of computing devices 30 may also implement any of the techniques described herein to calibrate a model based on a conformed non-optical pulse pressure waveform. Processing circuitry of computing device 12, processing circuitry 28 of server 24 and / or the processing circuity of computing devices 30 may also implement any of the techniques described herein to apply optical signal(s) received from IMD 10 to a calibrated model, e.g., to determine a health condition status of patient 4. For example, processing circuitry 28 may determine a health condition status of patient 4 based on BP measurements, such as changes in BP over time, where changes in BP may include changes in various features from the optical signal(s) from IMD 10.

[0035] Storage device 26 may include a computer-readable storage medium or computer-readable storage device. In some examples, memory 26 includes one or more of a short-term memory or a long-term memory. Storage device 26 may include, for example, RAM, DRAM, SRAM, magnetic discs, optical discs, flash memories, or forms of EPROM or EEPROM. In some examples, storage device 26 is used to store data indicative of instructions for execution by processing circuitry 28.

[0036] FIG. 2A is a block diagram illustrating an example configuration of IMD 10 of FIGS. 1A and IB. As shown in FIG. 2A, IMD 10 may include processing circuitry 50, memory 56, one or more sensor(s) 61, which may include one or more optical sensor(s) 62, sensing circuitry 52 coupled to one or more sensors 61 and electrodes 16A and 16B (collectively “electrodes 16”), and communication circuitry 54. As used herein, “sensors” may refer to any sensors described herein, including electrodes 16 and optical sensors 62.

[0037] One or more sensor(s) 61 of IMD 10 may sense physiological parameters or signals of patient 4. Sensor(s) 61 may include one or more accelerometers (e.g., 3-axis accelerometers), temperature sensors, pressure sensors, heart sound sensors (e.g., microphones or accelerometers), or other sensors. Electrodes 16 may be configured to sense cardiac electrograms or other electrogram signals of patient 4, and / or impedance of tissue fluid proximate the electrodes. One or more optical sensor(s) 62 may include one or more light detector(s) 64 configured to receive and / or detect light signals, such as reflected light signals originating from light emitter(s) 63. Light signals received and / or detected by optical sensor(s) 62 may be referred to as optical signals. In some examples, one or more of optical sensor(s) 62 may be configured to receive light reflected by blood in one or more blood vessels. In some examples, an optical sensor 62 may be included in a same sensor package and / or may be implemented using the same transducer(s). IMD 10 may, in some cases, include one or more optical sensors 62 including two or more light emitters 63 and one or more light detectors 64. In some examples, one or more optical sensor(s) 62 may a photoplethysmography (PPG) sensor.

[0038] FIG. 2B is a block diagram illustrating an example configuration of computing device 12 of FIG. 1 including a first BP sensing device 15 of FIG. 1. In some examples, first BP sensing device 15 may be separate from computing device 12. In some examples, as shown in FIG. 2B, computing device 12 may include first BP sensing device 15, processing circuitry 31, memory 32, and communication circuitry 38. In some examples, the first BP sensing device 15 may include one or more sensor(s) 34. In some examples, computing device 12 may further include a user interface 44.

[0039] In some examples, sensor(s) 34 may include pressure sensors. One or more sensor(s) 34 of first BP sensing device 15 may be configured to detect a non-optical pressure waveform of a patient, such as an arterial pulse pressure waveform. The sensor(s) 34 may include any suitable type of sensor, such as a pressure sensor, that are configuredto generate signals representative of an arterial pulse pressure waveform that may include one or more BP parameters, such as systolic, diastolic, and / or other BP values. In some examples, the sensor(s) 34 may include one or more of a piezoresistive pressure sensor or a strain gauge pressure sensor.

[0040] In some examples, e.g., in which first BP sensing device 15 is integrated with computing device 12 as shown in FIG. 2B, sensor(s) 34 may provide the generated pulse pressure waveform to processing circuitry 31 for conditioning and / or analysis of the pulse waveform. In some examples, first BP sensing device 15 may transmit the pulse pressure waveform to computing device 12, such as via communication circuitry 38 of computing device 12.

[0041] A pressure pulse that travels throughout the arteries of the patient is detectable at various locations of a patient, including the wrist and / or arm of the patient. Sensor(s) 34 may be located in a first BP sensing device 15. In some examples, a first BP sensing device 15 may be configured to be placed near a wrist and / or forearm of the patient and the pulse sensor(s) 34 in the first BP sensing device 15 may generate the pulse pressure waveform representative of the BP.

[0042] First BP sensing device 15 may be configured to sense non-optical pulse pressure waveform(s), such as an arterial pulse pressure waveform, of patient 18. Computing device 12 may receive the sensed pulse pressure waveform(s) from first BP sensing device 15. In some examples, the sensed pulse pressure waveform(s) may be segments that range between 5 second and 10 seconds in duration, but are not limited to durations between 5 and 10 seconds. In some examples, first BP sensing device 15 may be a tonometer, such as an applanation tonometer.

[0043] In some examples, second BP sensing device 17 may be configured to sense BP parameters, such as systolic values and / or diastolic values of patient 18. For example, second BP sensing device 17 may be a sphygmomanometer device. In some examples, the sensed pulse pressure waveform(s) sensed by the first BP sensing device 15 may be configured to conform to the BP parameters sensed by the second BP sensing device 17. For example, when second BP sensing device 17 senses systolic values and / or diastolic values, the sensed BP waveform(s) sensed by first BP sensing device 15 may be conformed to the systolic values and / or diastolic values sensed by second BP sensing device 17. Computing device 12 may collect and store pulse pressure waveform(s) andapply the sensed pulse pressure waveform to calibrate a model to determine and / or predict BP values of patient 18 using one or more optical signals sensed by an optical sensor in implantable device 10. In some examples, computing device 12 being configured to determine BP values of patient 18 may include computing device 12 being configured to determine, using the calibrated model, a BP value at a first time based on an optical signal at the first time and / or predict a BP value at a second time based on the optical signal at the first time, the second time being later than the first time.

[0044] As also shown in FIG. 2B, computing device 12 may include processing circuitry 31, communication circuitry 38, memory 32, and UI 14. Memory 32 may include any volatile or non-volatile media, such as a random access memory (RAM), read only memory (ROM), non-volatile RAM (NVRAM), electrically erasable programmable ROM (EEPROM), flash memory, or the like. Memory 32 may store computer-readable instructions that, when executed by processing circuitry 31, cause computing device 12 to perform various functions described herein. Processing circuitry 31 may include any combination of one or more processors including one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Accordingly, processing circuitry 31 may include any suitable structure, whether in hardware, software, firmware, or any combination thereof, to perform the functions ascribed herein to processing circuitry 31 and first BP sensing device 15. In some examples, when a computing device 12 is separate from the first BP sensing device 15, computing device 12 may be configured to receive data (e.g., via communication circuitry 38) from first BP sensing device 15.

[0045] The sensor(s) 34 may detect a pulse pressure waveform, such as an arterial pulse pressure waveform, of a patient and may include any suitable type of sensor, such as a pressure sensor, that are configured to generate signals representative of the pulse pressure waveform. For example, the pressure sensor may be piezoresistive pressure sensor or a strain gauge pressure sensor. In some examples, sensor(s) 34 may transmit the generated pulse pressure waveform information to processing circuitry 31 for conditioning and / or analysis of the pulse pressure waveform information, or first BP sensing device 15 may transmit the pulse pressure waveform information, such as via communication circuitry 38, directly to computing device 12.

[0046] In some examples, computing device 12 may receive the pulse pressure waveform sensed by the sensor(s) 34 in the first BP sensing device 15. The pulse pressure waveform may be configured to conform to BP parameters sensed by second BP sensing device 17. The received pulse pressure waveform may be the pulse pressure waveform itself and / or parameters indicative of the pulse pressure waveform.

[0047] The computing device 12 may apply the sensed pulse pressure waveform to calibrate a model that is configured to determine and / or predict BP values of the patient 18 using one or more optical signals sensed by optical sensor 62. Computing device 12 using a pulse pressure waveform to calibrate a model configured to determine and / or predict BP values based on optically derived pulse pressure waveforms provides improved accuracy of BP measurements and / or predictions of BP values based on optical signal(s) sensed by IMD 10. Computing device 12 using a pulse pressure waveform to calibrate a model configured to determine and / or predict BP values based on optically derived pulse pressure waveforms provides an improvement to a system 100 and / or IMD 10 to be able to provide clinically relevant and accurate BP results of patients, which makes the system 100 and / or IMD 10 more useful and which may lead to better care monitoring of patients.

[0048] In some of the following examples, techniques described in U.S. Application No. 63 / 498,903 by Ramos et al., entitled “A MEDICAL SYSTEM CONFIGURED TO DETERMINE HEALTH CONDITION STATUS BASED ON BLOOD PRESSURE CHANGES DETECTED BY IMPLANTABLE OPTICAL SENSOR,” filed on April 28, 2023, are incorporated herein by reference in their entirety, such as techniques for using a model configured to determine and / or predict BP based on optical signal(s) and / or techniques to determine health condition status based on BP values. In some examples, the model may be an artificial intelligence model, such as a machine learning model or other suitable model, to determine BP values of the patient using one or more optical signal by an optical sensor.

[0049] In some examples, the computing device 12 may be a smartphone that includes the first BP sensing device 15. In some examples, computing device 12 may be a wearable device, such as a smartwatch. In some examples, computing device 12 may be separate from the first BP sensing device 15. In some examples, the computing device 12 may receive the sensed pulse pressure waveform from the first BP sensing device 15 and then apply the sensed pulse pressure waveform to calibrate a model to determine and / or predictBP values of the patient using one or more optical signals sensed by an optical sensor. In some examples, the optical sensor may a PPG sensor. In some examples, the one or more optical signals may be derived from a PPG sensor.

[0050] Computing device 12 applying pulse pressure waveforms sensed by a first, non-optical, BP sensing device 15 to calibrate a model to determine and / or predict BP values of the patient using one or more optical signals sensed by an optical sensor, e.g., of an IMD, is an unconventional use of BP detection sensors. Conforming the pulse pressure waveforms sensed by the first, non-optical, BP sensing device 15 to BP parameters sensed by a second BP sensing device 17 is also an unconventional use of BP detection sensors.

[0051] The examples herein are directed to human patients. However, the techniques and systems described herein may also be used to screen non-human mammals to calibrate a model to determine and / or predict BP values using one or more optical signals sensed by an optical sensor.

[0052] FIGS. 3A-3B are conceptual diagrams of sensing and conforming pulse pressure waveforms in accordance with some examples of the current disclosure. As shown as an example in FIG. 3A, first BP sensing device 15 may sense a pulse pressure waveform 300 of a patient 18. In FIG. 3 A, the x-axis is time in seconds, and the y-axis is mmHG.

[0053] As shown as an example in FIG. 3B, first BP sensing device 15 may sense a pulse pressure waveform 300 of a patient 18 that is configured to conform to BP parameters, such as systolic value 310A and / or diastolic value 310B, sensed by second BP sensing device 17. In FIG. 3B, the x-axis is time, and the y-axis is mmHG. As shown as an example in FIG. 3B, as the pulse pressure waveform 300 extends along the x-axis, the pulse pressure waveform 300 conforms to the BP parameters 310A, 310B. For example, the BP parameters may include a systolic value 310A and / or a diastolic value 310B sensed by second BP sensing device 17, such as a sphygmomanometer. In some examples, by conforming the pulse pressure waveform 300 to BP parameters sensed by second BP sensing device 317, the parameters of the pulse pressure waveform 300, such as amplitude, may be more accurate, which may provide improved calibration of the model applied to optical derived pulse pressure waveforms for improved accuracy of the BP values produced by the model. In some examples, the pulse pressure waveform 300 may be conformed by a user adjusting the first BP sensing device 15, e.g., a position orpressure of the device on the patient, so the sensed pulse pressure waveform 300 conforms to the BP parameters sensed by the second BP sensing device 17.

[0054] One or more computing devices, such as one or more of computing device 12, IMD 10, server 24, and / or computing device 30 may receive the sensed pulsed pressure waveform 300 that is configured to conform to BP parameters, such as a systolic value 310A and / or a diastolic value 310B, sensed by second BP sensing device 17. In some examples, one or more computing devices, such as one or more of computing device 12, IMD 10, server 24, and / or computing device 30 may apply the sensed pulse pressure waveforms 300 to calibrate a model to determine and / or predict BP values of the patient using one or more optical signals sensed by an optical sensor, such as optical sensor 62, which provide improved calibration of the model configured to determine and / or predict BP values, such as an optically derived pulse pressure waveform, of the patient using one or more optical signals sensed by an optical sensor, such as optical sensor(s) 62.

[0055] FIG. 4A is a conceptual drawing illustrating an IMD 10A, which may be an example configuration of IMD 10 of FIGS. 1A-2A as an implantable cardiac monitor (ICM). In the example shown in FIG. 4A, IMD 10A may be embodied as a monitoring device having housing 412, proximal electrode 16A, distal electrode 16B, and optical sensor(s) 62. The optical sensor(s) 62 may be positioned at various locations on IMD 10A. Housing 412 may further comprise first major surface 414, second major surface 418, proximal end 420, and distal end 422. Housing 412 encloses electronic circuitry located inside the IMD 10A and protects the circuitry contained therein from body fluids. Electrical feedthroughs provide electrical connection of electrodes 16A and 16B.

[0056] In the example shown in FIG. 4 A, IMD 10A is defined by a length L, a width W and thickness or depth D and is in the form of an elongated rectangular prism wherein the length L is much larger than the width W, which in turn is larger than the depth D. In one example, the geometry of the IMD 10A - in particular a width W greater than the depth D - is selected to allow IMD 10A to be inserted under the skin of the patient using a minimally invasive procedure and to remain in the desired orientation during insertion. For example, the device shown in FIG. 4A includes radial asymmetries (notably, the rectangular shape) along the longitudinal axis that maintains the device in the proper orientation following insertion. For example, the spacing between proximal electrode 16A and distal electrode 16B may range from 30 millimeters (mm) to 55mm, 35mm to 55mm,and from 40mm to 55mm and may be any range or individual spacing from 25mm to 60mm. In addition, IMD 10A may have a length L that ranges from 30mm to about 70mm. In other examples, the length L may range from 5mm to 60mm, 15mm to 50mm, 40mm to 60mm, 45mm to 60mm and may be any length or range of lengths between about 5mm and about 80mm. In addition, the width W of major surface 414 may range from 5mm to 15mm, 3mm to 10mm, and may be any single or range of widths between 3mm and 15mm. The thickness of depth D of IMD 10A may range from 2mm to 9mm. In other examples, the depth D of IMD 10A may range from 2mm to 5mm, may range from 5mm to 15mm, and may be any single or range of depths from 2mm to 15mm. In addition, IMD 10A according to an example of the present disclosure is has a geometry and size designed for ease of implant and patient comfort. Examples of IMD 10A described in this disclosure may have a volume of three cubic centimeters (cm) or less, 1.5 cubic cm or less or any volume between three and 1.5 cubic centimeters.

[0057] In the example shown in FIG. 4A, once inserted within the patient, the first major surface 414 faces outward, toward the skin of the patient while the second major surface 418 is located opposite the first major surface 414. In addition, in the example shown in FIG. 4A, proximal end 420 and distal end 422 are rounded to reduce discomfort and irritation to surrounding tissue once inserted under the skin of the patient. IMD 10A, including instrument and method for inserting IMDs 10 is described, for example, in U.S. Patent Publication No. 2014 / 0276928, incorporated herein by reference in its entirety.

[0058] Proximal electrode 16A and distal electrode 16B are used to sense cardiac signals, e.g. EGM signals, intra-thoracically or extra-thoracically, which may be sub- muscularly or subcutaneously. EGM signals may be stored in a memory of IMD 10A, and data may be transmitted via integrated antenna 426A to another medical device, which may be another implantable device or an external device, such as computing device 12. In some example, electrodes 16A and 16B may additionally or alternatively be used for sensing any bio-potential signal of interest, which may be, for example, an EGM, electroencephalogram (EEG), electromyogram (EMG), or a nerve signal, from any implanted location.

[0059] In the example shown in FIG. 4A, proximal electrode 16A is in close proximity to the proximal end 420 and distal electrode 16B is in close proximity to distal end 422. In this example, distal electrode 16B is not limited to a flattened, outward facing surface, butmay extend from first major surface 414 around rounded edges 424 and / or end surface 425 and onto the second major surface 418 so that the electrode 16B has a three-dimensional curved configuration. In some examples, electrode 16B is an uninsulated portion of a metallic, e.g., titanium, part of housing 412.

[0060] In the example shown in FIG. 4 A, proximal electrode 16A is located on first major surface 414 and is substantially flat, and outward facing. However, in other examples proximal electrode 16A may utilize the three dimensional curved configuration of distal electrode 16B, providing a three dimensional proximal electrode (not shown in this example). Similarly, in other examples distal electrode 16B may utilize a substantially flat, outward facing electrode located on first major surface 414 similar to that shown with respect to proximal electrode 16 A.

[0061] The various electrode configurations allow for configurations in which proximal electrode 16A and distal electrode 16B are located on both first major surface 414 and second major surface 418. In other configurations, such as that shown in FIG.4A, only one of proximal electrode 16A and distal electrode 16B is located on both major surfaces 414 and 418, and in still other configurations both proximal electrode 16A and distal electrode 16B are located on one of the first major surface 414 or the second major surface 418 (e.g., proximal electrode 16A located on first major surface 14 while distal electrode 16B is located on second major surface 418). In another example, IMD 10A may include electrodes on both major surface 414 and 418 at or near the proximal and distal ends of the device, such that a total of four electrodes are included on IMD 10A. Electrodes 16A and 16B may be formed of a plurality of different types of biocompatible conductive material, e.g., stainless steel, titanium, platinum, iridium, or alloys thereof, and may utilize one or more coatings such as titanium nitride or fractal titanium nitride.

[0062] In the example shown in FIG. 4A, proximal end 420 includes a header assembly 428 that includes one or more of proximal electrode 16A, integrated antenna 426A, anti-migration projections 432, and / or suture hole 434. Integrated antenna 426A is located on the same major surface (i.e., first major surface 414) as proximal electrode 16A and is also included as part of header assembly 428. Integrated antenna 426A allows IMD 10A to transmit and / or receive data. In other examples, integrated antenna 426A may be formed on the opposite major surface as proximal electrode 16A, or may be incorporated within the housing 412 of IMD 10A. In the example shown in FIG. 4A, anti-migrationprojections 432 are located adjacent to integrated antenna 426A and protrude away from first major surface 414 to prevent longitudinal movement of the device. In the example shown in FIG. 4A, anti-migration projections 432 include a plurality (e.g., nine) small bumps or protrusions extending away from first major surface 414. As discussed above, in other examples anti-migration projections 432 may be located on the opposite major surface as proximal electrode 16A and / or integrated antenna 426 A. In addition, in the example shown in FIG. 4A, header assembly 428 includes suture hole 434, which provides another means of securing IMD 10A to the patient to prevent movement following insertion. In the example shown, suture hole 434 is located adjacent to proximal electrode 16A. In one example, header assembly 428 is a molded header assembly made from a polymeric or plastic material, which may be integrated or separable from the main portion of IMD 10A.

[0063] FIG. 4B is a functional schematic diagram of IMD 10A as shown in FIG. 4A according to an embodiment of the present disclosure. IMD 10A may include proximal electrode 16B located at proximal end 422, distal electrode 16A located at distal end 420, optical sensor(s) 62, integrated antenna 426A, electrical circuitry 400 and power source 402. In particular, electrical circuitry 400 is coupled to proximal electrode 16B and distal electrode 16A to sense cardiac signals and monitor events. Electrical circuitry 400 may also connected to transmit and receive communications via integrated antenna 426A. Power source 402 provides power to electrical circuitry 400, as well as to any other components that require power. Power source 402 may include one or more energy storage devices, such as one or more rechargeable or non-rechargeable batteries. In some examples, electrical circuitry 400 includes processing circuitry 50 and storage device 56, such as a memory, as shown in FIG. 2, the memory 56 being operatively coupled to the processing circuitry 50 and configured to store a machine learning model.

[0064] In the example shown in FIG. 4B, electrical circuitry 400 may receive raw EGM signals monitored by proximal electrode 16B and distal electrode 16A and raw optical signals monitored by optical sensor(s) 62. Electrical circuitry 400 may include components / modules for converting the raw EGM signal to a processed EGM signal that can be analyzed to detect sense events and for converting the raw optical signals to calibrated processed optical signal(s) that can be analyzed to detect sense events. Although not shown, electrical circuitry 400 may include any discrete and / or integrated electroniccircuit components that implement analog and / or digital circuits capable of producing the functions described for analyzing optical signal(s) to determine a health condition status of a patient. For example, the electrical circuitry 400 may include analog circuits, e.g., preamplification circuits, filtering circuits, and / or other analog signal conditioning circuits. The modules may also include digital circuits, e.g., digital filters, combinational or sequential logic circuits, state machines, integrated circuits, a processor (shared, dedicated, or group) that executes one or more software or firmware programs, memory devices, or any other suitable components or combination thereof that provide the described functionality.

[0065] In one example, electrical circuitry 400 includes a sensing unit for monitoring the EGM signal detected by the respective proximal and distal electrodes 16A and 16B and light signals received by the optical sensor(s) 62, respectively. In one example, electrical circuitry 400 includes processing circuitry 50 that is utilized to receive information regarding sensed events and implements one or more algorithms for determining a health condition status of a patient. In addition, the analog voltage signals received from electrodes 16A and 16B may be passed to analog-to-digital (A / D) converters included in the electrical circuitry 400, and stored in a memory unit (not shown) included as part of electrical circuitry 400 for subsequent analysis with firmware executed by the processor included as part of electrical circuitry 400.

[0066] In some examples, housing 412 (FIG. 4A) may be a hermetically-sealed housing configured for subcutaneous implantation within the patient, wherein at least the power source 402, memory, and processing circuitry 50 are within the hermetically- sealed case.

[0067] FIG. 4C is a perspective drawing illustrating another IMD 10B, which may be another example configuration of IMD 10 from FIGS. 1A-2A. IMD 10B of FIG. 4C may be configured substantially similarly to IMD lOA of FIG. 4A, with differences between them discussed herein.

[0068] IMD 10B may include a leadless, subcutaneously-implantable monitoring device, e.g. an ICM. IMD 10B includes housing having a base 440 and an insulative cover 442. IMD 10B includes optical sensor(s) 62. Proximal electrode 16C and distal electrode 16D may be formed or placed on an outer surface of cover 442. Various circuitries and components of IMD 10B, e.g., described below with respect to FIG. 2A,may be formed or placed on an inner surface of cover 442, or within base 440. In some examples, a battery or other power source of IMD 10B may be included within base 440. In the illustrated example, antenna 426B is formed or placed on the outer surface of cover 442, but may be formed or placed on the inner surface in some examples. In some examples, insulative cover 442 may be positioned over an open base 440 such that base 440 and cover 442 enclose the circuitries and other components and protect them from fluids such as body fluids.

[0069] Circuitries and components may be formed on the inner side of insulative cover 442, such as by using flip-chip technology. Insulative cover 442 may be flipped onto a base 440. When flipped and placed onto base 440, the components of IMD 10B formed on the inner side of insulative cover 442 may be positioned in a gap 444 defined by base 440. Electrodes 16C and 16D and antenna 426B may be electrically connected to circuitry formed on the inner side of insulative cover 442 through one or more vias (not shown) formed through insulative cover 442. Insulative cover 442 may be formed of sapphire (i.e., corundum), glass, parylene, and / or any other suitable insulating material. Base 440 may be formed from titanium or any other suitable material (e.g., a biocompatible material). Electrodes 16C and 16D may be formed from any of stainless steel, titanium, platinum, iridium, or alloys thereof. In addition, electrodes 16C and 16D may be coated with a material such as titanium nitride or fractal titanium nitride, although other suitable materials and coatings for such electrodes may be used.

[0070] In the example shown in FIG. 4C, the housing of IMD 10B defines a length L, a width W and thickness or depth D and is in the form of an elongated rectangular prism wherein the length L is much larger than the width W, which in turn is larger than the depth D, similar to IMD 10A of FIG. 4C. For example, the spacing between proximal electrode 16C and distal electrode 16D may range from 30 millimeters (mm) to 50mm, from 35mm to 45mm, or be approximately 40mm. In addition, IMD 10B may have a length E that ranges from 30mm to about 70mm. In other examples, the length L may range from 5mm to 60mm, 40mm to 60mm, 45mm to 55mm, or be approximately 45mm. In addition, the width W may range from 3mm to 15mm, such as approximately 8mm. The thickness of depth D of IMD 10B may range from 2mm to 15mm, from 3 to 5mm, or be approximately 4mm. IMD 10B may have a volume of three cubic centimeters (cm) or less, or 1.5 cubic cm or less, such as approximately 1.4 cubic cm.

[0071] In the example shown in FIG. 4C, once inserted subcutaneously within the patient, outer surface of cover 442 faces outward, toward the skin of the patient. In addition, as shown in FIG. 4C, proximal end 446 and distal end 448 are rounded to reduce discomfort and irritation to surrounding tissue once inserted.

[0072] FIG. 5 is a flow diagram illustrating an example technique for operating system 100. As indicated by FIG. 5, first BP sensing device 15 may sense a pulse pressure waveform 300 of patient 18 (500). Computing device 12 and / or a user may conform the pulse pressure waveform 300 to BP parameters, such as systolic values 310A and / or diastolic values 310B, sensed by the second BP sensing device 17 (502). Computing device 12 may apply the conformed pulse pressure waveform 300 to calibrate a model that is configured to determine and / or predict BP values based on an optically derived pulse pressure waveform, such as an optical signal sensed by an optical sensor 62 of IMD 10 (504). Computing device 12 using a non-optical pulse pressure waveform to calibrate a model that is configured to determine and / or predict BP values based on optically derived pulse pressure waveforms provides improved accuracy of calibration of determination of BP using an IMD 10 with an optical sensor 62 which leads to more accurate BP measurements and / or predictions of BP values.

[0073] 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 the described techniques may be implemented within one or more processors or processing circuitry, including one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or any other equivalent integrated or discrete logic circuitry, as well as any combinations of such components. The term “processor” or “processing circuitry” may generally refer to any of the foregoing logic circuitry, alone or in combination with other logic circuitry, or any other equivalent circuitry. A control unit including hardware may also perform one or more of the techniques of this disclosure.

[0074] Such hardware, software, and firmware may be implemented within the same device or within separate devices to support the various operations and functions described in this disclosure. In addition, any of the described units, circuits or components may be implemented together or separately as discrete but interoperable logic devices. Depiction of different features as circuits or units is intended to highlight different functional aspectsand does not necessarily imply that such circuits or units must be realized by separate hardware or software components. Rather, functionality associated with one or more circuits or units may be performed by separate hardware or software components or integrated within common or separate hardware or software components.

[0075] The techniques described in this disclosure may also be embodied or encoded in a computer-readable medium, such as a computer-readable storage medium, containing instructions that may be described as non-transitory media. Instructions embedded or encoded in a computer-readable storage medium may cause a programmable processor, or other processor, to perform the method, e.g., when the instructions are executed. Computer readable storage media may include random access memory (RAM), read only memory (ROM), programmable read only memory (PROM), erasable programmable read only memory (EPROM), electronically erasable programmable read only memory (EEPROM), flash memory, a hard disk, a CD-ROM, a floppy disk, a cassette, magnetic media, optical media, or other computer readable media.

[0076] Various aspects of the techniques may enable the following examples.

[0077] Example 1 : A system includes a first blood pressure (BP) sensing device configured to sense a pulse pressure waveform of a patient; and one or more computing devices configured to: receive the pulse pressure waveform, wherein the pulse pressure waveform is configured to conform to BP parameters determined by a second BP sensing device, the second BP sensing device being different than the first BP sensing device; and apply the pulse pressure waveform to calibrate a model to determine BP values of the patient using one or more optical signals sensed by an optical sensor.

[0078] Example 2: The system recited in example 1, wherein the BP parameters determined by the second BP sensing device include a systolic value.

[0079] Example 3: The system recited in example 2, wherein a systolic value of the pulse pressure waveform is configured to conform to the systolic value determined by the second BP sensing device.

[0080] Example 4: The system recited in any of examples 1-3, wherein the first BP sensing device comprises a tonometer.

[0081] Example 5: The system recited in any of examples 1-4, wherein the second BP sensing device comprises a sphygmomanometer.

[0082] Example 6: The system recited in any of examples 1-5, wherein the pulse pressure waveform is an arterial pulse pressure waveform.

[0083] Example 7: The system recited in any of examples 1-6, further comprising an implantable medical device (IMD) that comprises the optical sensor.

[0084] Example 8: The system recited in any of examples 1-6, wherein the system further comprises an implantable medical device (IMD) comprising: a housing configured for subcutaneous implantation at a location within a patient; and the optical sensor configured to sense the one or more optical signals indicative of blood movement in vessels of the patient proximate to the location over a period of time.

[0085] Example 9: The system recited of example 8, further comprising processing circuitry configured to: determine a plurality of calibrated BP values over the period of time based on the one or more optical signals and the calibrated model; determine a health condition status of the patient based on the calibrated BP values over the period of time; and output an indication of the determined health condition status.

[0086] Example 10: The system recited of example 9, wherein one of the processing circuitry is positioned in the IMD.

[0087] Example 11: The system recited of any of examples 9-10, wherein the computing devices comprises one or more of a server or a mobile computing device, and one of the processing circuitry is positioned in the server or one of the processing circuitry is positioned in the mobile computing device.

[0088] Example 12: The system recited in example 9, wherein the IMD is an insertable cardiac monitor, the insertable cardiac monitor comprising: the processing circuitry; a power source operatively coupled to the processing circuitry and the optical sensor; a memory operatively coupled to the processing circuitry and configured to store the model; a distal electrode operatively coupled to the processing circuitry; a proximal electrode operatively coupled to the processing circuitry; and wherein at least the power source, memory, and processing circuitry are within the housing, and wherein the housing has a length, a width, and a depth, wherein the length is greater than the width and the width is greater than the depth, wherein the length is within a range from 5 millimeters (mm) to 60 mm, wherein the width is within a range from 5 mm to 15 mm, and wherein the depth is within a range from 5 mm to 15 mm.

[0089] Example 13: The system recited of any of examples 1-12, wherein the model is a machine learning model.

[0090] Example 14: An implantable medical device (IMD) comprising: a housing configured for subcutaneous implantation at a location within a patient; an optical sensor, the optical sensor being at least one of on or within the housing, the optical sensor configured to sense one or more optical signals indicative of blood movement in vessels of the patient proximate to the location over a period of time; and processing circuitry configured to: receive a pulse pressure waveform from a computing device, the pulse pressure waveform is sensed by a first blood pressure (BP) sensing device and configured to conform to BP parameters determined by a second BP sensing device, the second BP sensing device being different than the first BP sensing device; and apply the pulse pressure waveform to calibrate a model to determine BP values of the patient using the one or more optical signals sensed by the optical sensor.

[0091] Example 15: The IMD recited in example 14, wherein the BP parameters determined by the second BP sensing device include a systolic value.

[0092] Example 16: The IMD recited in example 15, wherein a systolic value of the pulse pressure waveform is configured to conform to the systolic value determined by the second BP sensing device.

[0093] Example 17: The IMD recited in any of examples 14-16, wherein the first BP sensing device comprises a tonometer.

[0094] Example 18: The IMD recited in any of examples 14-17, wherein the second BP sensing device comprises a sphygmomanometer.

[0095] Example 19: The IMD recited in any of examples 14-18, wherein the pulse pressure waveform is an arterial pulse pressure waveform.

[0096] Example 20: The IMD recited in any of examples 14-19, wherein the processing circuitry is configured to: determine a plurality of calibrated BP values over the period of time based on the one or more optical signals and the calibrated model; determine a health condition status of the patient based on the calibrated BP values over the period of time; and output an indication of the determined health condition status.

[0097] Example 21: The IMD recited of any of examples 14-20, wherein the model is a machine learning model.

[0098] Example 22: A method for operating a medical system comprising: sensing, by a first blood pressure (BP) sensing device, a pulse pressure waveform of a patient; receiving, by processing circuitry, the pulse pressure waveform; and applying, by the processing circuitry, the pulse pressure waveform to calibrate a model to determine BP values of the patient using one or more optical signals sensed by an optical sensor.

[0099] Example 23: The method recited in example 22, the method further comprising: determining, by the processing circuitry, a plurality of calibrated BP values over the period of time based on the one or more optical signals and the calibrated model; determining, by the processing circuitry, a health condition status of the patient based on the calibrated BP values over the period of time; and outputting, by the processing circuitry, an indication of the determined health condition status.

[0100] Example 24: The method of any of examples 22-23, the method further comprising: conforming the pulse pressure waveform to BP parameters determined by a second BP sensing device, the second BP sensing device being different than the first BP sensing device.

[0101] Example 25: The method recited in example 24, wherein the BP parameters determined by the second BP sensing device include a systolic value.

[0102] Example 26: The method recited in example 25, wherein conforming the pulse pressure waveform to BP parameters sensed by the second BP sensing device comprises conforming a systolic value of the pulse pressure waveform to the systolic value determined by the second BP sensing device.

[0103] Example 27: The method recited in any of examples 22-26, wherein the first BP sensing device comprises a tonometer.

[0104] Example 28: The method recited in any of examples 24-27, wherein the second BP sensing device comprises a sphygmomanometer.

[0105] Example 29: The method recited in any of examples 22-28, wherein the pulse pressure waveform is an arterial pulse pressure waveform.

[0106] Example 30: The method recited in any of examples 22-29, wherein an implantable medical device (IMD) comprises the optical sensor.

[0107] Example 31: The method recited of example 30, wherein one of the processing circuitry is positioned in the IMD.

[0108] Example 32: The method recited of any of examples 22-31, wherein one of the processing circuitry is positioned in the server or one of the processing circuitry is positioned in the mobile computing device.

[0109] Example 33: The method recited of any of examples 22-32, wherein the model is a machine learning model.

[0110] Various examples have been described. These and other examples are within the scope of the following claims.

Claims

WHAT IS CLAIMED IS:

1. A system comprising: a first blood pressure (BP) sensing device configured to sense a pulse pressure waveform of a patient; and one or more computing devices configured to: receive the pulse pressure waveform, wherein the pulse pressure waveform is configured to conform to BP parameters determined by a second BP sensing device, the second BP sensing device being different than the first BP sensing device; and apply the pulse pressure waveform to calibrate a model to determine BP values of the patient using one or more optical signals sensed by an optical sensor.

2. The system recited in claim 1, wherein the BP parameters determined by the second BP sensing device include a systolic value.

3. The system recited in claim 2, wherein a systolic value of the pulse pressure waveform is configured to conform to the systolic value determined by the second BP sensing device.

4. The system recited in any of claims 1-3, wherein the first BP sensing device comprises a tonometer.

5. The system recited in any of claims 1-4, wherein the second BP sensing device comprises a sphygmomanometer.

6. The system recited in any of claims 1-5, wherein the system further comprises an implantable medical device (IMD) comprising: a housing configured for subcutaneous implantation at a location within a patient; and the optical sensor configured to sense the one or more optical signals indicative of blood movement in vessels of the patient proximate to the location over a period of time.

7. The system recited of claim 6, further comprising processing circuitry configured to: determine a plurality of calibrated BP values over the period of time based on the one or more optical signals and the calibrated model; determine a health condition status of the patient based on the calibrated BP values over the period of time; and output an indication of the determined health condition status.

8. The system recited of claim 7, wherein one of the processing circuitry is positioned in the IMD.

9. The system recited of any of claims 7-8, wherein the computing devices comprises one or more of a server or a mobile computing device, and one of the processing circuitry is positioned in the server or one of the processing circuitry is positioned in the mobile computing device.

10. The system recited of any of claims 1-9, wherein the model is a machine learning model.

11. An implantable medical device (IMD) comprising: a housing configured for subcutaneous implantation at a location within a patient; an optical sensor, the optical sensor being at least one of on or within the housing, the optical sensor configured to sense one or more optical signals indicative of blood movement in vessels of the patient proximate to the location over a period of time; and processing circuitry configured to: receive a pulse pressure waveform from a computing device, the pulse pressure waveform is sensed by a first blood pressure (BP) sensing device and configured to conform to BP parameters determined by a second BP sensing device, the second BP sensing device being different than the first BP sensing device; andapply the pulse pressure waveform to calibrate a model to determine BP values of the patient using the one or more optical signals sensed by the optical sensor.

12. The IMD recited in claim 11, wherein the BP parameters determined by the second BP sensing device include a systolic value, and a systolic value of the pulse pressure waveform is configured to conform to the systolic value determined by the second BP sensing device.

13. The IMD recited in any of claims 11-12, wherein the first BP sensing device comprises a tonometer and the second BP sensing device comprises a sphygmomanometer.

14. The IMD recited in any of claims 11-13, wherein the processing circuitry is configured to: determine a plurality of calibrated BP values over the period of time based on the one or more optical signals and the calibrated model; determine a health condition status of the patient based on the calibrated BP values over the period of time; and output an indication of the determined health condition status.

15. The IMD recited of any of claims 11-14, wherein the model is a machine learning model.

Images