Selective photoacoustic sampling for blood pressure prediction

Abstract

Some disclosed methods involve: monitoring a heart rate waveform associated with a subject to detect a cardiac cycle marker; determining a cardiac phase change window based on the cardiac cycle marker; and starting a photoacoustic sampling system at the beginning of the heart phase change window, wherein the photoacoustic sampling system comprises a piezoelectric receiver and a light source system. Such methods may involve, during the cardiac phase change window: controlling the light source system to emit a plurality of light pulses into biological tissue of the subject; receiving, from the piezoelectric receiver, signals corresponding to the acoustic waves emitted from the portions of the biological tissue; and obtaining plethysmographic data based on the signal. Such methods may involve deactivating the photoacoustic sampling system at the end of the cardiac phase change window.

Description

[0001] CLAIM OF PRIORITY

[0002] This application claims priority to U.S. Patent Application No. 18 / 461,026, filed September 5, 2023, entitled “SELECTIVE PHOTOACOUSTIC SAMPLING FOR BLOOD PRESSURE PREDICTION,” which is hereby incorporated by reference and for all purposes. TECHNICAL FIELD

[0003] The present disclosure relates generally to non-invasive blood pressure estimation and vascular monitoring.

[0004] TECHNICAL DESCRIPTION

[0005] Various different sensing technologies and algorithms are being investigated for use in various biomedical applications, including health and wellness monitoring. This push is due in part to limitations in the availability of traditional measurement devices for continuous, non-invasive, and dynamic monitoring. For example, a sphygmomanometer is an example of a traditional blood pressure monitoring device that utilizes an inflatable cuff to apply counter pressure to a region of interest (e.g., around a subject’s upper arm). The pressure applied by the inflatable cuff is designed to constrain arterial flow in order to measure systolic and diastolic pressures. Such traditional sphygmomanometers inherently affect the subject’s physiological state, which can introduce errors in blood pressure measurements. Such sphygmomanometers can also affect the subject’s psychological state, which can manifest as changes in the physiological state, thereby introducing errors in blood pressure measurements. For example, such devices are typically used primarily in isolated settings, such as when a subject visits a physician’s office or is admitted to a hospital. Of course, some subjects can experience anxiety in such scenarios, and this anxiety can affect (e.g., increase) the user’s blood pressure and heart rate.

[0006] For these and other reasons, such devices can not accurately estimate or “reflect” changes in blood pressure and the user’s overall health condition over time. While implantable or other invasive devices can more accurately estimate changes in blood pressure over time, such invasive devices are typically riskier than non-invasive devices and are typically not suitable for dynamic use. SUMMARY

[0007] The systems, methods, and devices of the present disclosure each have several aspects, no single one of which is solely responsible for its desirable attributes.

[0008] One innovative aspect of the subject matter described in this disclosure can be implemented in an apparatus or a system including the apparatus. The apparatus can include a heart rate waveform analyzer, a photoacoustic sampling system, and a control system. The photoacoustic sampling system can include an ultrasonic receiver (e.g., a piezoelectric receiver) and a light source system. The control system can include one or more general purpose single- or multi-chip processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gates or transistor logic, discrete hardware components, or combinations thereof.

[0009] The heart rate waveform analyzer can be configured to monitor a heart rate waveform associated with a subject to detect a cardiac cycle marker, and determine a cardiac phase transition window based on the cardiac cycle marker. The control system can be configured to initiate the photoacoustic sampling system at a start of the cardiac phase transition window, and during the cardiac phase transition window: control the light source system to emit a plurality of light pulses into a biological tissue of the subject, receive, from the piezoelectric receiver, signals corresponding to acoustic waves emitted from portions of the biological tissue in response to the plurality of light pulses, and obtain plethysmography data based on the signals. The biological tissue may, for example, include blood and blood vessels located deep within the biological tissue. The acoustic waves may, for example, correspond to photoacoustic emissions from the blood and the blood vessels caused by the plurality of light pulses. The control system can be configured to deactivate the photoacoustic sampling system at an end of the cardiac phase transition window.

[0010] According to some implementations, the control system can be further configured to deactivate the photoacoustic sampling system prior to the end of the cardiac phase transition window in response to determining that the plethysmography data includes at least a threshold number of samples prior to the end of the cardiac phase transition window. According to some implementations, the cardiac phase transition window can correspond to a systole-to-diastole transition. According to some other implementations, the cardiac phase transition window can correspond to a diastole-to-systole transition.

[0011] According to some implementations, the heart rate waveform analyzer can be further configured to obtain the heart rate waveform based on a data stream received from a heart activity sensor. According to some implementations, the control system can be further configured to determine a blood pressure based on the plethysmography data, and display the blood pressure on a display. According to some implementations, the control system can be further configured to determine the blood pressure based on systolic data included in the plethysmography data without reference to diastolic data included in the plethysmography data.

[0012] According to some embodiments, the volumetric data may be photoacoustic volumetric recording (PAPG) data. According to some embodiments, the control system may be further configured to generate a two-dimensional (2D) PAPG image based on the PAPG data. According to some embodiments, the 2D PAPG image may include a depth-time dimension and a pulse-time dimension.

[0013] Other innovative aspects of the subject matter described in this disclosure can be implemented in methods, such as biometric methods. The method may involve: monitoring a heart rate waveform associated with a subject to detect cardiac cycle markers, determining a cardiac phase transition window based on the cardiac cycle markers, and activating a photoacoustic sampling system at the beginning of the cardiac phase transition window. The photoacoustic sampling system may include an ultrasound receiver (e.g., a piezoelectric receiver) and a light source system. The method may involve: during the cardiac phase transition window: controlling the light source system to emit multiple light pulses into the subject's biological tissue, receiving signals from the piezoelectric receiver corresponding to sound waves emitted from various parts of the biological tissue, and obtaining plethysmography data based on the signals. The biological tissue may, for example, include blood and blood vessels located deep within the biological tissue. The sound waves may, for example, correspond to photoacoustic emissions from the blood and blood vessels caused by the multiple light pulses. The method may involve: deactivating the photoacoustic sampling system at the end of the cardiac phase transition window.

[0014] According to some specific embodiments, the method may also involve: in response to determining that the plethysmography data includes at least a threshold number of samples before the end of the cardiac phase transition window, deactivating the photoacoustic sampling system before the end of the cardiac phase transition window. According to some specific embodiments, the cardiac phase transition window may correspond to a systolic-diastolic transition. According to some other specific embodiments, the cardiac phase transition window may correspond to a diastolic-systolic transition.

[0015] According to some specific embodiments, the method may also involve obtaining the heart rate waveform based on a data stream received from a cardiac activity sensor. According to some specific embodiments, the method may also involve determining blood pressure based on the plethysmography data and displaying the blood pressure on a display. According to some specific embodiments, the method may also involve determining the blood pressure based on systolic data included in the plethysmography data, without referring to diastolic data included in the plethysmography data.

[0016] According to some specific embodiments, the volumetric data may be photoacoustic volumetric recording (PAPG) data. According to some specific embodiments, the method may also involve generating a two-dimensional (2D) PAPG image based on the PAPG data. According to some specific embodiments, the 2D PAPG image may include a depth-time dimension and a pulse-time dimension.

[0017] Some or all of the methods described herein can be executed by one or more devices according to instructions (e.g., software) stored on a non-transitory medium. Such non-transitory media may include memory devices such as those described herein, including but not limited to random access memory (RAM) devices, read-only memory (ROM) devices, etc. Therefore, some innovative aspects of the subject matter described herein can be implemented in one or more non-transitory media on which software is stored. The software may include instructions for controlling one or more devices to perform one or more of the disclosed methods.

[0018] One such method involves monitoring a heart rate waveform associated with a subject to detect cardiac cycle markers, determining a cardiac phase transition window based on the cardiac cycle markers, and activating a photoacoustic sampling system at the beginning of the cardiac phase transition window. The photoacoustic sampling system may include an ultrasound receiver (e.g., a piezoelectric receiver) and a light source system. The method may involve, during the cardiac phase transition window, controlling the light source system to emit multiple light pulses into the subject's biological tissue, receiving signals from the piezoelectric receiver corresponding to sound waves emitted from various parts of the biological tissue, and obtaining plethysmography data based on the signals. The biological tissue may, for example, include blood and blood vessels located deep within the biological tissue. The sound waves may, for example, correspond to photoacoustic emissions from the blood and blood vessels caused by the multiple light pulses. The method may involve deactivating the photoacoustic sampling system at the end of the cardiac phase transition window.

[0019] According to some specific embodiments, the method may also involve: in response to determining that the plethysmography data includes at least a threshold number of samples before the end of the cardiac phase transition window, deactivating the photoacoustic sampling system before the end of the cardiac phase transition window. According to some specific embodiments, the cardiac phase transition window may correspond to a systolic-diastolic transition. According to some other specific embodiments, the cardiac phase transition window may correspond to a diastolic-systolic transition.

[0020] According to some specific embodiments, the method may also involve obtaining the heart rate waveform based on a data stream received from a cardiac activity sensor. According to some specific embodiments, the method may also involve determining blood pressure based on the plethysmography data and displaying the blood pressure on a display. According to some specific embodiments, the method may also involve determining the blood pressure based on systolic data included in the plethysmography data, without referring to diastolic data included in the plethysmography data.

[0021] According to some specific embodiments, the volumetric data may be photoacoustic volumetric recording (PAPG) data. According to some specific embodiments, the method may also involve generating a two-dimensional (2D) PAPG image based on the PAPG data. According to some specific embodiments, the 2D PAPG image may include a depth-time dimension and a pulse-time dimension.

[0022] Details of one or more specific embodiments of the subject matter described in this disclosure are set forth in the accompanying drawings and the description below. Other features, aspects, and advantages will become apparent from the description, drawings, and claims. Note that the relative dimensions in the following drawings may not be drawn to scale. Attached Figure Description

[0023] FIG. 1A An example of a blood pressure monitoring device based on photoplethysmography (PPG) is shown.

[0024] FIG. 1B An example of two superimposed graphs showing blood pressure changes during the cardiac cycle is shown.

[0025] FIG. 1C An example of a blood pressure monitoring device based on photoacoustic volume plethysmography (PAPG) is shown.

[0026] FIG. 2 This is a block diagram showing example components of a device according to some examples.

[0027] FIG. 3A This is a block diagram illustrating a first example of a blood pressure estimation process based on some specific implementations.

[0028] FIG. 3B Example volumetric images according to various aspects of this disclosure are illustrated.

[0029] FIG. 4A This is a block diagram illustrating a second example of a blood pressure estimation process based on some specific implementations.

[0030] FIG. 4B An example cardiac phase transition window associated with a heart rate waveform is shown.

[0031] FIG. 5 Example biometric systems according to various aspects of this disclosure are illustrated.

[0032] FIG. 6 Example methods based on various aspects of this disclosure are illustrated.

[0033] FIG. 7A An example of a range gating window (RGW) selected to receive sound waves emitted from different depth ranges is shown.

[0034] FIG. 7B Examples of multiple acquisition time delays selected to receive sound waves emitted from different depths are shown.

[0035] FIG. 8A and FIG. 8B An example of a device configured to receive sound waves emitted from different depths is shown.

[0036] FIG. 9 It shows that it can execute FIG. 6 An example of a cross-sectional view of the apparatus for the method.

[0037] FIG. 10 This is a block diagram illustrating an example heart rate wave generation process based on some specific implementations.

[0038] FIG. 11A An example dynamic monitoring device 1100 designed to be worn on the wrist is shown according to some specific implementations.

[0039] FIG. 11B An example dynamic monitoring device 1110 designed to be worn on a finger is shown according to some specific implementations.

[0040] FIG. 11C An example dynamic monitoring device 1120, designed to be located on an earpiece according to some specific implementations, is shown.

[0041] The same reference numerals and names in the various figures indicate the same elements. Detailed Implementation

[0042] The following description is directed to certain implementations and is intended to describe various aspects of this disclosure. However, those skilled in the art will readily recognize that the teachings herein can be applied in a variety of different ways. Some of the concepts and examples provided in this disclosure are particularly applicable to blood pressure monitoring applications. However, some specific implementations may also be applicable to other types of biosensing applications and other fluid flow systems. The described specific implementations can be implemented in any device, apparatus, or system that includes the means disclosed herein. Furthermore, it is contemplated that the described specific implementations may be included in or associated with a variety of electronic devices, such as, but not limited to: mobile phones, cellular phones enabling multi-media networks, mobile TV receivers, wireless devices, smartphones, smart cards, wearable devices (such as wristbands, armbands, wrist straps, rings, hairbands, patches, etc.), Bluetooth. ®Devices, personal data assistants (PDAs), wireless email receivers, handheld or portable computers, notebook computers, laptops, smart e-readers, tablet computers, printers, copiers, scanners, fax machines, GPS receivers / navigators, cameras, digital media players, game consoles, wristwatches, clocks, calculators, television monitors, flat panel displays, electronic reading devices (e.g., e-readers), mobile health devices, computer monitors, automotive displays (including odometer and speedometer displays, etc.), cockpit controls and / or displays, camera view displays (such as displays of rearview cameras in vehicles), building structures, microwave ovens, refrigerators, stereo systems, tape recorders or players, DVD players, CD players, VCRs, radios, portable memory chips, washing machines, dryers, washer / dryer units, parking meters, car doors, autonomous or semi-autonomous vehicles, drones, Internet of Things (IoT) devices, etc. Therefore, this teaching is not intended to be limited to the specific specific implementations depicted and described with reference to the accompanying drawings; rather, its broad applicability will be apparent to those skilled in the art.

[0043] Additionally, please note that unless otherwise indicated, the conjunction “or” as used herein is intended to have an inclusive meaning where appropriate; that is, the phrase “A, B, or C” is intended to include the following possibilities: A alone; B alone; C alone; A and B without C; B and C without A; A and C without B; and A, B, and C. Similarly, the phrase “at least one of” in a list of items refers to any combination of those items, including a single item. For example, the phrase “at least one of A, B, or C” is intended to cover the following possibilities: at least one A; at least one B; at least one C; at least one A and at least one B; at least one B and at least one C; at least one A and at least one C; and at least one A, at least one B, and at least one C.

[0044] Various aspects generally relate to blood pressure monitoring, and more specifically to non-invasive blood pressure monitoring using photoplethysmography. Some aspects more specifically relate to blood pressure prediction using two-dimensional (2D) photoacoustic photoplethysmography (PAPG). In various specific implementations, a subject's blood pressure can be predicted based on 2D PAPG image fragments. 2D PAPG image fragments can be obtained using a fragment generation process. This fragment generation process includes performing photoacoustic sampling to obtain raw 2D PAPG data, constructing a 2D PAPG image based on the raw 2D PAPG data, and segmenting the 2D PAPG image on a heart rate cycle basis. According to various aspects of this disclosure, photoacoustic sampling and 2D PAPG image construction can be selectively performed to obtain 2D PAPG images corresponding to portions of the subject's heart rate cycle that are important for 2D PAPG-based blood pressure prediction, while avoiding the capture and processing of raw 2D PAPG data for insignificant portions of the heart rate cycle. According to various aspects of this disclosure, significant portions of the heart rate cycle may correspond to a cardiac phase transition window, which represents the time interval during which cardiac phase transitions (such as systolic-diastolic transition, diastolic-systolic transition, or both) occur. Depending on the specific implementation, blood pressure can be predicted using a predictive model based on 2D PAPG image fragments, trained using a deep learning network (DLN) (such as a Long Short-Term Memory (LSTM) neural network or a Convolutional Neural Network (CNN)).

[0045] According to various aspects of this disclosure, such cardiac phase transition windows can be identified via a parallel-operating, non-PAPG-based process, rather than via 2D PAPG-based analysis. For example, according to various specific embodiments, a PPG-based phase transition detection process can be implemented, according to which a photoplethysmography (PPG) device can be used to obtain a heart rate waveform associated with the subject, and this heart rate waveform can be analyzed to determine the cardiac phase transition window associated with the subject.

[0046] Specific embodiments of the subject matter described in this disclosure can be implemented to achieve one or more of the following potential advantages. According to some embodiments, using a deep learning network to train a model to estimate the blood pressure difference based on volumetric images obtained from raw 2D PAPG data can generate more accurate blood pressure difference estimates. Selectively performing photoacoustic sampling and 2DPAPG image construction, thereby avoiding the capture and processing of raw 2D PAPG data for unimportant parts of the heart rate cycle, enables the advantages of 2D PAPG-based blood pressure prediction while reducing costs in terms of power consumption, processing resource utilization, and memory resource utilization.

[0047] Some specific implementations of the portable monitoring devices described herein are also designed to consume relatively little power, enabling continuous wear and monitoring of biosignals of interest (such as blood pressure) for extended periods (e.g., hours, days, weeks, or even a month or longer) without external calibration, charging, or other interruptions. Continuous monitoring provides greater prognostic and diagnostic value compared to isolated measurements, such as those performed in a hospital or physician's office setting. Some specific implementations of the portable or "dynamic" monitoring devices described herein are also designed with a small form factor and a housing that can be coupled to a subject (also referred to herein as a "patient," "person," or "user"), enabling wearable, non-invasive, and unrestricted dynamic use. In other words, some specific implementations of the dynamic monitoring devices described herein do not restrict the free and unrestricted movement of the subject's arms or legs, and can continuously or periodically monitor cardiovascular characteristics, such as blood pressure, even while the subject is active or performing other physical activities. Such devices not only do not interfere with the subject's daily or other desired activities, but this non-interference may also encourage continuous wear. In some implementations, it is further expected that the subject may not even be aware of when the sensing devices of the dynamic monitoring device are actually performing a measurement.

[0048] Furthermore, some of the disclosed implementations offer advantages over previously deployed non-invasive blood pressure monitoring devices, such as those based on photoplethysmography (PPG). PPG-based blood pressure monitoring devices are not optimal because they overlay data corresponding to the blood volume of all irradiated vessels (arteries, veins, etc.), each exhibiting unique blood volume changes over time, resulting in a mixed signal that is not closely correlated with blood pressure and is susceptible to drift. In contrast, some disclosed devices employ depth-discriminate photoplethysmography (PAPG), which distinguishes between arterial, venous, and other heart rate waveforms. Blood pressure estimation using depth-discriminate PAPG is significantly more accurate than that using PPG-based methods.

[0049] Continuous blood pressure monitoring can be an essential component of patient care for a wide range of medical conditions. Depending on the approach, continuous blood pressure monitoring can be established using implantable or other invasive devices, such as catheters. However, invasive blood pressure monitoring devices can negatively impact patient comfort, pose risks of infection, and may not be suitable for dynamic use. In many cases, continuous, non-invasive, and dynamic monitoring of a patient's blood pressure may be desirable.

[0050] Some non-invasive blood pressure monitoring devices use plethysmography to monitor blood pressure. Generally speaking, plethysmography involves measuring changes in the volume of an organ, a part of the body, or the whole body. Monitoring blood pressure using plethysmography typically involves estimating blood pressure based on measurements of changes in blood volume within a part of the body.

[0051] Photoplethysmography (PPG) is a plethysmography method that can be used for blood pressure monitoring. PPG involves transmitting light through a region of human tissue (such as finger tissue), measuring the light reflected from the tissue, and analyzing the reflected light measurements to detect changes in blood volume in the irradiated area.

[0052] FIG. 1A An example of a PPG-based blood pressure monitoring device is shown. FIG. 1A Examples of arteries, veins, arterioles, venules, and capillaries of the circulatory system are shown, including those within the finger 115. FIG. 1A In the example shown, the electrocardiogram sensor has detected a proximal artery pulse near heart 116.

[0053] according to FIG. 1A The example shown includes a light source of one or more light-emitting diodes (LEDs) emitting light (in some examples, green, red, and / or near-infrared (NIR) light) that penetrates the tissue of the finger 115 in the irradiated area. The reflection of this tissue by the photodetector can be used to detect volume changes in the blood in the irradiated area of ​​the finger 115 that correspond to a heart rate waveform.

[0054] like FIG. 1A As shown in heart rate waveform 118, capillary heart rate waveform 119 has a different shape and phase shift compared to arterial heart rate waveform 117. In this simplified example, the detected heart rate waveform 121 is a combination of capillary heart rate waveform 119 and arterial heart rate waveform 117. In some instances, the response of one or more other vessels may also be part of the heart rate waveform 121 detected by a PPG-based blood pressure monitoring device.

[0055] FIG. 1B An example of two superimposed graphs showing blood pressure changes during the cardiac cycle is shown. Graph 123 corresponds to blood pressure measured by a catheter, a sufficiently reliable method to be considered a "benchmark truth" for comparing blood pressure estimation methods. In this example, graph 125 corresponds to blood pressure estimated by a PPG-based method. FIG. 1B In the example shown, the area between graphs 123 and 125 represents the error in blood pressure estimation according to the PPG-based method.

[0056] By comparison FIG. 1A Heart rate waveform diagram 118 and FIG. 1BThe blood pressure graph shows that PPG-based blood pressure monitoring devices are not optimal because PPG data is superimposed with the blood volume data corresponding to all irradiated vessels, and each vessel exhibits different time-shifted blood volume changes.

[0057] Another plethysmography method that can be used for more precise monitoring of blood pressure is photoacoustic plethysmography (PAPG). Similar to PPG, PAPG involves transmitting light through a region of human tissue, such as finger tissue. However, PAPG involves measuring the sound waves (rather than light) reflected from the tissue and analyzing the reflected sound wave measurements to detect changes in blood volume in the irradiated area.

[0058] FIG. 1C An example of a PAPG-based blood pressure monitoring device is shown. FIG. 1C It shows FIG. 1B The same example of arteries, veins, arterioles, venules, and capillaries within the finger 115 shown. In some examples, FIG. 1C The light source shown may be or may include one or more LEDs or laser diodes. In this example, as... FIG. 1A As shown, the light source emits light (in some examples, green, red, and / or near-infrared (NIR) light) that penetrates the tissue of the finger 115 in the irradiated area.

[0059] exist FIG. 1C In the example shown, the blood vessels (and components of the blood itself) are heated by incident light from a light source and emit sound waves. In this example, the emitted sound waves include ultrasound. According to this specific embodiment, the sound wave emission is detected by an ultrasound receiver (in this example, a piezoelectric receiver). The photoacoustic emission of the irradiated tissue detected by the piezoelectric receiver can be used to detect changes in blood volume in the irradiated area of ​​the finger 115, which correspond to a heart rate waveform. In some examples, the ultrasound receiver may correspond to the one described in the reference below. FIG. 2 The ultrasonic receiver 202 described.

[0060] FIG. 1A PPG-based systems and FIG. 1C One important difference between PAPG-based methods is that FIG. 1C The speed of sound wave propagation shown is much lower than FIG. 1A The propagation speed of the reflected light wave is shown. Therefore, it can be based on... FIG. 1C The arrival time of the sound waves is used to differentiate depths, while based on... FIG. 1A The arrival time of the light waves shown may not be distinguishable by depth. This depth distinction allows for the isolation of sound waves received from different blood vessels in some of the disclosed specific implementations.

[0061] Based on some such examples, this depth discrimination allows arterial heart rate waveforms to be distinguished from venous heart rate waveforms and other heart rate waveforms. Therefore, blood pressure estimation based on depth discrimination PAPG methods can be much more accurate than blood pressure estimation based on PPG methods.

[0062] FIG. 2 This is a block diagram illustrating example components of a device according to some disclosed specific embodiments. In this example, device 200 includes a biometric system. Here, the biometric system includes an ultrasonic receiver 202, a light source system 204, and a control system 206. Although FIG. 2 Not shown, but device 200 may include a substrate. In some examples, device 200 may include a pressure plate. Some examples are described below. Some specific implementations of device 200 may include interface system 208 and / or display system 210.

[0063] This document discloses various examples of ultrasonic receiver 202, some of which may include or be configured (or configurable) as ultrasonic transmitters, while others may not. In some embodiments, ultrasonic receiver 202 and ultrasonic transmitter may be combined in an ultrasonic transceiver. In some examples, ultrasonic receiver 202 may include a piezoelectric receiver layer, such as a PVDF polymer layer or a PVDF-TrFE copolymer layer. In some embodiments, a single piezoelectric layer may act as an ultrasonic receiver. In some embodiments, other piezoelectric materials, such as aluminum nitride (AlN) or lead zirconate titanate (PZT), may be used in the piezoelectric layer. In some examples, ultrasonic receiver 202 may include an array of ultrasonic transducer elements, such as a piezoelectric micromechanical ultrasonic transducer (PMUT) array, a capacitive micromechanical ultrasonic transducer (CMUT) array, etc. In some such examples, a piezoelectric receiver layer, PMUT elements in a monolayer array of PMUTs, or CMUT elements in a monolayer array of CMUTs may act as both an ultrasonic transmitter and an ultrasonic receiver. According to some examples, ultrasonic receiver 202 may be or may include an array of ultrasonic receivers. In some examples, device 200 may include one or more independent ultrasonic transmitter elements. In some such examples, the ultrasonic transmitter may include an ultrasonic plane wave generator.

[0064] In some examples, the light source system 204 may include an array of light-emitting diodes (LEDs). In some embodiments, the light source system 204 may include one or more laser diodes. According to some embodiments, the light source system may include at least one infrared, red, green, blue, white, or ultraviolet LED. In some embodiments, the light source system 204 may include one or more laser diodes. For example, the light source system 204 may include at least one infrared, red, green, blue, white, or ultraviolet laser diode. In some embodiments, the light source system 204 may include one or more organic LEDs (OLEDs).

[0065] In some embodiments, the light source system 204 can be configured to emit light of various wavelengths, which can be selective to achieve greater penetration into biological tissues and / or trigger photoacoustic emission primarily from specific types of materials. For example, because near-infrared (near-IR) light is not absorbed as readily by some types of biological tissues (e.g., melanin and vascular tissue) as relatively short wavelength light, in some embodiments, the light source system 204 can be configured to emit light in one or more near-IR ranges to obtain photoacoustic emission from relatively deep biological tissues. In some such embodiments, the control system 206 can control the wavelength of the light emitted by the light source system 204 within the range of 750 nm to 850 nm, for example, 808 nm. However, hemoglobin absorbs near-IR light as much as it absorbs shorter wavelength light (e.g., ultraviolet, violet, blue, or green light). Near-IR light can produce suitable photoacoustic emission from some blood vessels (e.g., 1 mm or larger in diameter), but not necessarily from very small blood vessels. To achieve stronger photoacoustic emission from blood overall, and especially from smaller blood vessels, in some implementations, the control system 206 may control the wavelength of the light emitted by the light source system 204 within the range of 495 nm to 570 nm (e.g., 520 nm to 532 nm). Light within this range is more readily absorbed by biological tissue and therefore may not penetrate as deeply as near-IR light, but it can produce relatively stronger photoacoustic emission in blood compared to near-infrared light. In some examples, the control system 206 may control the wavelength of the light emitted by the light source system 204 to preferentially induce sound waves in blood vessels, other soft tissues, and / or bone. For example, an infrared (IR) light-emitting diode (LED) may be selected, and short pulses of IR light are emitted to irradiate a portion of the target object and generate sound wave emission, which is then detected by the ultrasound receiver system 202. In another example, an IR LED and red or other colored LEDs (such as green, blue, white, or ultraviolet (UV)) may be selected, and short pulses of light are emitted sequentially from each light source, wherein an ultrasound image is obtained after each light source emits light. In other specific implementations, one or more light sources of different wavelengths can be illuminated sequentially or simultaneously to generate acoustic emissions that can be detected by an ultrasonic receiver. Image data from the ultrasonic receiver obtained from different wavelengths of light at different depths of the target object (e.g., discussed in detail below) can be combined to determine the location and type of material within the target object. Since materials in the human body typically absorb light of different wavelengths differently, image contrast may occur. When materials in the human body absorb light of a specific wavelength, they may differentially heat up and generate acoustic emissions with sufficiently strong and short light pulses. Depth contrast can be obtained using light of different wavelengths and / or intensities at each selected wavelength.In other words, continuous images can be obtained by using varying light intensity and wavelength at a fixed RGD (which corresponds to a fixed depth of the target object) to detect substances within the target object and their locations. For example, photoacoustic methods can be used to detect hemoglobin, blood glucose, and / or blood oxygen in the blood vessels of a target object (such as a finger).

[0066] According to some embodiments, the light source system 204 can be configured to emit light pulses with a pulse width of less than about 100 nanoseconds. In some embodiments, the pulse width of the light pulses can be between about 10 nanoseconds and about 500 nanoseconds or longer. According to some examples, the light source system can be configured to emit multiple light pulses at a pulse repetition frequency between 10 Hz and 100 kHz. Alternatively or additionally, in some embodiments, the light source system 204 can be configured to emit multiple light pulses at a pulse repetition frequency between about 1 MHz and about 100 MHz. Alternatively or additionally, in some embodiments, the light source system 204 can be configured to emit multiple light pulses at a pulse repetition frequency between about 10 Hz and about 1 MHz. In some examples, the pulse repetition frequency of the light pulses can correspond to the acoustic resonant frequency of the ultrasonic receiver and the substrate. For example, the light source system 204 can emit a set of four or more light pulses at a frequency corresponding to the resonant frequency of the resonant acoustic cavity in the sensor stack, thereby allowing the accumulation of received ultrasonic waves and obtaining a higher signal strength. In some embodiments, filtered light or a light source with a specific wavelength for detecting the selected substance may be included in the light source system 204. In some embodiments, the light source system may include a light source (such as red, green, and blue LEDs of a display) that can be enhanced with light sources of other wavelengths (such as IR and / or UV) and light sources with higher optical power. For example, a high-power laser diode or electronic flash unit (e.g., an LED or xenon flash unit) with or without a filter may be used for short-term irradiation of the target object.

[0067] Control system 206 may include one or more general-purpose single-chip or multi-chip processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic components, discrete hardware components, or combinations thereof. Control system 206 may also include (and / or be configured to communicate with) one or more memory devices, such as one or more random access memory (RAM) devices, read-only memory (ROM) devices, etc. Therefore, device 200 may have a memory system including one or more memory devices, but... FIG. 2The memory system is not shown. Control system 206 can be configured to receive and process data from ultrasonic receiver 202, for example, as described below. If device 200 includes an ultrasonic transmitter, control system 206 can be configured to control the ultrasonic transmitter. In some embodiments, the functionality of control system 206 can be divided among one or more controllers or processors, such as between a dedicated sensor controller and an application processor in a mobile device.

[0068] According to various aspects of this disclosure, control system 206 may be configured to control light source system 204 and ultrasound receiver 202 to implement photoacoustic volumetric plethysmography (PAPG) for blood pressure prediction. According to various embodiments, control system 206 may control light source system 204 to emit light (such as light pulses) with appropriate intensity, wavelength, and pulse repetition frequency for PAPG-based blood pressure prediction. According to various embodiments, control system 206 may control ultrasound receiver 202 to monitor sound waves emitted from human tissue due to light emission from light source system 204, and detect such sound wave emission when it occurs. According to various embodiments, control system 206 may be configured to process signals received from ultrasound receiver 202 to obtain PAPG data, based on which control system can perform PAPG-based blood pressure prediction.

[0069] Some specific implementations of device 200 may include interface system 208. In some examples, interface system 208 may include a wireless interface system. In some specific implementations, interface system 208 may include a user interface system, one or more network interfaces, one or more interfaces between control system 206 and memory system, and / or one or more interfaces between control system 206 and one or more external device interfaces (e.g., ports or application processors).

[0070] According to some examples, device 200 may include display system 210, which includes one or more displays. For example, display system 210 may include one or more LED displays, such as one or more organic LED (OLED) displays.

[0071] Device 200 can be used in a variety of different contexts, many of which are disclosed herein. For example, in some embodiments, a mobile device may include device 200. In some embodiments, a wearable device may include device 200. For example, a wearable device may be a bracelet, armband, wristband, ring, hairband, earplug, or patch.

[0072] FIG. 3AThis is a block diagram illustrating an example blood pressure estimation process 300 according to some specific implementations. The blood pressure estimation process 300 is a 2D PAPG-based blood pressure estimation process and includes a 2D PAPG image fragment generation process 301 implemented to generate 2D PAPG image fragments 313. Based on the 2D PAPG image fragment generation process 301, photoacoustic sampling is performed at 302 to obtain the original 2D PAPG dataset 303. Depending on various specific implementations, it can be used... FIG. 2 The device 200 uses a light source system 204 and an ultrasonic receiver 202 to perform photoacoustic sampling at location 302. In some specific implementations, FIG. 5 The photoacoustic sampling system 504 (see below) of the biometric system 500 can perform photoacoustic sampling at 302. Each raw 2D PAPG dataset 303 may include multiple raw 2D PAPG data samples. According to aspects of this disclosure, any given raw 2D PAPG dataset 303 can be generated by sampling measurements of reflected acoustic waves over a time period corresponding to the duration of the data collection interval (e.g., 10 seconds). The raw 2D PAPG dataset 303 can be averaged and normalized at 304. According to aspects of this disclosure, averaging at 304 may involve overlapping sliding window averaging of the data in the raw 2D PAPG dataset 303 to reduce the effective underlying light source pulse repetition frequency (PRF) of the 2D PAPG dataset 303. For example, in some examples, the data in the raw 2D PAPG dataset 303 may reflect a 25 kHz PRF applied to the photoacoustic sampling light source, and overlapping sliding window averaging may be applied at 304 to reduce the effective underlying light source PRF by a factor of 50, to 500 Hz.

[0073] Based on the averaged and normalized 2D PAPG data obtained at 304, PAPG image construction can be performed at 310 to generate a 2D PAPG image 311. The 2D PAPG image 311 depicts the relative amounts of reflected acoustic energy at various depths within human tissue over a time period corresponding to the duration of the data collection interval associated with the original 2D PAPG dataset 303 (e.g., approximately 10 seconds). Any given 2D PAPG image 311 can depict reflected acoustic energy over a time period covering multiple heart rate cycles. At 312, a 2D PAPG segmentation and transformation process can be applied to generate 2D PAPG image segments 313 by segmenting and transforming the 2D PAPG image 311. Each 2D PAPG image segment 313 depicts the reflected acoustic energy of a corresponding heart rate cycle. In some examples, the 2D PAPG segmentation and transformation process may include transforming segments of the 2D PAPG image 311 via Fast Fourier Transform (FFT), wavelet transform, or another suitable type of transform.

[0074] A 2D PAPG image fragment 313 may be provided as input to a blood pressure (BP) prediction model 314 trained by a deep learning network (DLN). In some examples, the DLN-trained blood pressure prediction model 314 may be implemented as a long short-term memory (LSTM) neural network or a convolutional neural network (CNN). Based on the 2D PAPG image fragment 313, the DLN-trained blood pressure prediction model 314 may generate a blood pressure estimate 315. According to various aspects of this disclosure, the blood pressure estimate 315 may include any or all of a systolic blood pressure (SBP) estimate, a diastolic blood pressure (DBP) estimate, and a pulse pressure (PP) estimate. In some examples, the DLN-trained blood pressure prediction model 314 may determine one or more predictors based on the 2D PAPG image fragment 313, and may determine the blood pressure estimate 315 at least in part based on these predictors. According to various specific embodiments, such predictors may include direct or indirect indicators of properties such as systolic artery diameter, diastolic artery diameter, arterial dilation, arterial strain, arterial wave velocity (AWV), and pulse wave velocity (PWV).

[0075] The averaged and normalized 2D PAPG data obtained at 304 can also be passed to a heart rate waveform (HRW) generation process at 306, which can generate a heart rate waveform 307 based on the averaged and normalized 2D PAPG data. According to various aspects of this disclosure, the heart rate waveform generation process at 306 may include extracting HRW data from the averaged and normalized 2D PAPG data obtained at 304 and bandpass filtering the HRW data. Heart rate waveform analysis can be performed on the heart rate waveform 307 at 308 to identify periodic markers 309, which indicate the boundaries between portions of the heart rate waveform 307 corresponding to different heart rate cycles. According to various aspects of this disclosure, the periodic markers 309 can serve as the basis for segmenting the 2D PAPG image 311 at 312 by incorporating 2D PAPG segmentation and variation processes. In some specific embodiments, FIG. 2 The control system 206 of the device 200 can perform operations at points 304, 306, 308, 310, 312, and 314 in the blood pressure estimation process 300. In some specific implementations, FIG. 5 These operations can be performed by the control system 502 (see below) of the biometric system 500.

[0076] FIG. 3B Example volumetric image 350 is depicted according to various aspects of this disclosure. Volumetric image 350 may represent, for example, combinations of some examples. FIG. 3AA 2D PAPG image 311 is constructed for a specific implementation of the blood pressure estimation scheme 300. The horizontal axis provides the scale of the pulse time dimension of the volumetric image 350 (in seconds in the depicted example). The vertical axis provides the scale of the depth time dimension of the volumetric image 350 (in microseconds (μs) in the depicted example). The depth time dimension can represent arterial diameter, dilation, and strain, while the pulse time dimension can represent arterial wave velocity (AWV) and pulse wave velocity (PWV). The intensity at a given point in the volumetric image 350 corresponds to the acoustic energy proportional to the amount of light absorbed by arterial hemoglobin.

[0077] FIG. 4A This is a block diagram illustrating an example blood pressure estimation process 400 based on some specific implementations. FIG. 3A Similar to the blood pressure estimation process 300, the blood pressure estimation process 400 is a 2D PAPG-based blood pressure estimation process. However, according to the blood pressure estimation process 400, photoacoustic sampling can be selectively performed to obtain 2D PAPG images corresponding to the portions of the subject's heart rate cycle that are important for 2D PAPG-based blood pressure prediction, while avoiding the capture and processing of raw 2D PAPG data for unimportant portions of the heart rate cycle. According to various aspects of this disclosure, important portions of the heart rate cycle may correspond to cardiac phase transition windows, which represent the time interval in which cardiac phase transitions (such as systolic-diastolic transition, diastolic-systolic transition, or both) occur.

[0078] According to the blood pressure estimation process 400, a phase transition detection process 421 is used to identify the cardiac phase transition window 429, and at 302, photoacoustic sampling is initiated at the beginning of the cardiac phase transition window 429 and deactivated at the end of the cardiac phase transition window 429. In some embodiments, the phase transition detection process 421 may be a non-PAPG-based process operating in parallel with the 2D PAPG image fragment generation process 301. In some embodiments, for example, the phase transition detection process 421 may be a photoplethysmography (PPG) based process.

[0079] Based on the phase transition detection process 421, sensing can be performed at 422 to obtain sensor data 423 suitable as the basis for heart rate waveform generation. In some specific implementations, FIG. 5The biometric sensor 522 (see below) of the biometric system 500 can perform sensing at 422 to obtain sensor data 423. In some specific implementations, sensing at 422 can be performed using a PPG sensor, and sensor data 423 can be PPG data. A heart rate waveform 425 can be generated based on the sensor data 423 via a heart rate waveform generation process at 424. Heart rate waveform analysis can be performed on the heart rate waveform 425 at 426 to identify period markers 427, which can indicate the boundaries between portions of the heart rate waveform 425 corresponding to different heart rate cycles. A window prediction process at 428 can determine or predict a cardiac phase transition window 429 based on the identified period markers 427.

[0080] In some specific implementations, FIG. 2 The control system 206 of device 200 can perform operations at 424, 426, and 428 in the blood pressure estimation process 400. In some other embodiments, the control system 206 can perform some of the operations at 424, 426, and 428, and a second control system, possibly operating on a device separate from device 200, can perform other operations at 424, 426, and 428, or such a second control system can perform all the operations at 424, 426, and 428. In some embodiments, FIG. 5 The heart rate waveform generator 524 (see below) of the biometric system 500 can perform the operation at 424, and the heart rate waveform analyzer 426 can perform the operations at 426 and 428.

[0081] FIG. 4B An example cardiac phase transition window associated with heart rate waveform 450 is shown. FIG. 4B The image shows two heart rate cycles of heart rate waveform 450. The horizontal dimension represents time, and the vertical dimension represents relative pressure. Four cardiac phase transition windows 452A, 452B, 452C, and 452D are shown, each representing the time interval shortly before and after the relative pressure reaches a peak or trough. Cardiac phase transition windows 452A and 452C, with time spans of t2-t3 and t6-t7 respectively, correspond to the systolic-diastolic transition and include the relative pressure peak. Cardiac phase transition windows 452B and 452D, with time spans of t4-t5 and t8-t9 respectively, correspond to the diastolic-systolic transition and include the relative pressure trough.

[0082] Relative to according to FIG. 4A The blood pressure estimation process 400 is based on 2D PAPG. Data with significant predictive value largely lie within the cardiac phase transition windows 452A, 452B, 452C, and 452D, which constitute... FIG. 4AAn example of cardiac phase transition window 429. Data in regions 454A, 454B, 454C, 454D, and 454E (grey shading), located outside cardiac phase transition windows 452A, 452B, 452C, and 452D, may be of little importance, allowing data in 454A, 454B, 454C, 454D, and 454E to be ignored in consideration without significantly affecting the accuracy of 2D PAPG-based blood pressure estimation. Combined with FIG. 4A The blood pressure estimation process 400 can start photoacoustic sampling at the beginning of the corresponding cardiac phase transition windows 452A, 452B, 452C and 452D, and stop photoacoustic sampling at the end of the corresponding cardiac phase transition window 452A, 452B, 452C at 452D.

[0083] FIG. 5 An example biometric system 500 according to various aspects of this disclosure is illustrated. The biometric system 500 may represent an implementable FIG. 4A The system 400 includes a blood pressure estimation process. The biometric system 500 may include a control system 502, a heart rate waveform analyzer 526, and a photoacoustic sampling system 504. The photoacoustic sampling system 504 may include a piezoelectric receiver 506 and a light source system 508. The heart rate waveform analyzer 526 may be configured to monitor a heart rate waveform 525 associated with a subject to detect cardiac cycle markers 527 and determine a cardiac phase transition window 529 based on the cardiac cycle markers. According to various aspects of this disclosure, the heart rate waveform analyzer 526 may perform... FIG. 4A The heart rate waveform analysis at position 426 and the window prediction at position 428 correspond to the operations, and the cycle marker 527 and the cardiac phase transition window 529 can correspond to the cycle marker 427 and the cardiac phase transition window 429, respectively.

[0084] According to various aspects of this disclosure, cardiac cycle marker 527 can indicate the timing of observed cardiac phase transitions, and a heart rate waveform analyzer can apply a predictive model to determine cardiac phase transition window 529 based on the timing of observed cardiac phase transitions. In some examples, cardiac phase transition window 529 can correspond to the systolic-diastolic transition. In other examples, cardiac phase transition window 529 can correspond to the diastolic-systolic transition.

[0085] In some implementations, the biometric system 500 may include: a biometric sensor 522 configured to generate sensor data 523 suitable as the basis for generating a heart rate waveform; and may include a heart rate waveform generator 524 configured to generate a heart rate waveform 525 based on the sensor data 523. In some examples, the biometric sensor 522 may be a cardiac activity sensor, such as a PPG sensor, an electrocardiogram (ECG) sensor, a contact microphone for sensing cardiac activity, or another type of device capable of sensing cardiac activity (e.g., heartbeat). In some examples, for instance, the biometric sensor 522 may be a PPG sensor, and the sensor data 523 may be PPG data, such as that included in a PPG data stream.

[0086] In some embodiments, the heart rate waveform generator 524 and the heart rate waveform analyzer 526 may both reside on the same device as the control system 502 and the photoacoustic sampling system 504. In some embodiments, the biometric sensor 522 may be external to this device, while in other embodiments, the biometric sensor 522 may also be located on this device. In some embodiments, one or both of the heart rate waveform generator 524 and the heart rate waveform analyzer 526 may be a subsystem of the control system 502. In some embodiments, one or both of the heart rate waveform generator 524 and the heart rate waveform analyzer 526 may correspond to functionality external to the control system 502. In some such embodiments, such functionality may reside on a device separate from the host control system 502. In an example, the biometric sensor 522, the heart rate waveform generator 524, and the heart rate waveform analyzer 526 may reside on a PPG blood pressure estimation device communicatively coupled to the device carrying the control system 502 and the photoacoustic sampling system 504.

[0087] According to various aspects of this disclosure, the control system 502 can generally be configured to control the photoacoustic sampling system 504 to perform photoacoustic sampling within the cardiac phase transition window and avoid performing photoacoustic sampling outside the cardiac phase transition window. In this case, the control system 502 may activate the photoacoustic sampling system 504 at the beginning of the cardiac phase transition window 529.

[0088] During the cardiac phase transition window 529, the control system 502 can control the light source system 508 to emit multiple light pulses into the subject's biological tissue. The biological tissue may include blood and blood vessels located deep within the biological tissue. The control system 502 can receive signals 510 from a piezoelectric receiver 506 corresponding to sound waves emitted from various parts of the subject's biological tissue. These sound waves may correspond to photoacoustic emissions from the blood and blood vessels caused by the multiple light pulses.

[0089] In some embodiments, the control system 502 may obtain plethysmography data 512 based on received signal 510, and may determine blood pressure 516 based on plethysmography data 512. Blood pressure 516 may include any or all of systolic blood pressure, diastolic blood pressure, and pulse pressure. In some embodiments, the control system 502 may determine blood pressure 516 based on systolic data included in plethysmography data 512 without referring to diastolic data included in plethysmography data 512. In some embodiments, the control system 502 may be configured to display blood pressure 516 on a display.

[0090] According to some specific implementations, the volumetric data 512 may be PAPG data, and the control system 502 may generate a 2D PAPG image 514 based on the volumetric data 512 and determine blood pressure 516 based on the 2D PAPG image 514. In some examples, the 2D PAPG image 514 may include a depth time dimension and a pulse time dimension. In some examples, the control system 502 may use a blood pressure prediction model to determine blood pressure 516 based on the 2D PAPG image 514, which is trained using a deep learning network (DLN) (such as a long short-term memory (LSTM) neural network or a convolutional neural network).

[0091] According to various aspects of this disclosure, the control system 502 may deactivate the photoacoustic sampling system 504 at the end of the cardiac phase transition window 529. In some examples, the control system 504 deactivates the photoacoustic sampling system 504 before the end of the cardiac phase transition window 529 in response to determining that the volumetric data 512 includes at least a threshold number of samples. In some other examples, the control system 502 deactivates the photoacoustic sampling system 504 at the end of the cardiac phase transition window 529 in response to determining that the cardiac phase transition window 529 has ended.

[0092] FIG. 6 Example method 600 according to various aspects of this disclosure is illustrated. Method 600 may represent an operation according to some examples, which may be performed, for example, by... FIG. 5 Biometric system 500 combined FIG. 4A The blood pressure estimation scheme 400 is implemented in a specific manner. In various implementations, method 600 may include more or fewer boxes than indicated. Furthermore, the boxes of method 600 are not necessarily executed in the indicated order. In some instances, FIG. 6 One or more boxes in the box shown can be executed simultaneously.

[0093] According to method 600, heart rate waveforms associated with the subject can be monitored at 605 to detect cardiac cycle markers. For example, FIG. 5The biometric system 500's heart rate waveform analyzer 526 can monitor heart rate waveforms 525 associated with the subject to detect cardiac cycle markers 527. In some examples, the heart rate waveform can be obtained based on a data stream received from a cardiac activity sensor. For example, FIG. 5 The heart rate waveform analyzer 526 of the biometric system 500 can receive a heart rate waveform 525 from a heart rate waveform generator 524, which can generate the heart rate waveform 525 based on sensor data 523 received from a biometric sensor 522. The sensor data 523 can be a data stream output by the biometric sensor 522, and the biometric sensor 522 can be a PPG sensor, an ECG sensor, a contact microphone for sensing cardiac activity, or another type of device capable of sensing cardiac activity (such as heartbeat).

[0094] At position 610, the cardiac phase transition window can be determined based on cardiac cycle markers. For example, FIG. 5 The heart rate waveform analyzer 526 of the biometric system 500 can determine a cardiac phase transition window 529 based on cardiac cycle markers 527. According to various aspects of this disclosure, cardiac cycle markers can indicate the timing of observed cardiac phase transitions, and predictive models can be used to determine the cardiac phase transition window based on the timing of observed cardiac phase transitions. In some examples, the cardiac phase transition window may correspond to the systolic-diastolic transition. In other examples, the cardiac phase transition window may correspond to the diastolic-systolic transition. At 615, a photoacoustic sampling system can be initiated at the beginning of the cardiac phase transition window. The photoacoustic sampling system may include a piezoelectric receiver and a light source system. For example, FIG. 5 The control system 502 of the biometric system 500 can activate the photoacoustic sampling system 504 at the start of the cardiac phase transition window 529, and the photoacoustic sampling system 505 may include a piezoelectric receiver 506 and a light source system 508.

[0095] During the cardiac phase transition window determined at position 610, operations can be performed at positions 620, 625, and 630. At position 620, the light source system can be controlled to emit multiple light pulses onto the subject's biological tissues. For example, FIG. 5 The control system 502 of the biometric system 500 can control the light source system 508 to emit multiple light pulses into the biological tissue of the subject. According to various aspects of this disclosure, the biological tissue may include blood and blood vessels located deep within the biological tissue. At 625, signals corresponding to sound waves emitted from various parts of the biological tissue can be received from a piezoelectric receiver. For example, FIG. 5 The control system 502 of the biometric system 500 can receive a signal 510 from a piezoelectric receiver 506, which corresponds to sound waves emitted from various parts of biological tissue.

[0096] At 630, volumetric data can be obtained based on the signal. For example, FIG. 5 The control system 502 of the biometric system 500 can obtain plethysmography data 512 based on a signal 510 received from a piezoelectric receiver 506 of the photoacoustic sampling system 504. In some examples, blood pressure can be determined based on the plethysmography data. For example, FIG. 5 The control system 502 of the biometric system 500 can determine blood pressure 516 based on plethysmography data 512. According to various aspects of this disclosure, the determined blood pressure may include any or all of systolic pressure, diastolic pressure, and pulse pressure. In some examples, the blood pressure may be displayed on a monitor. For example, FIG. 5 The control system 502 of the biometric system 500 can display blood pressure 516 on a display. In some examples, blood pressure can be determined based on systolic data included in the plethysmography data, without referring to diastolic data included in the plethysmography data. For example, FIG. 5 The control system 502 of the biometric system 500 can determine blood pressure 516 based on systolic data included in plethysmography data 512 without referring to diastolic data included in plethysmography data 512.

[0097] In some examples, the volumetric data obtained at 630 may be photoacoustic volumetric imaging (PAPG) data. In some examples, two-dimensional (2D) PAPG images may be generated based on PAPG data. In some examples, 2D PAPG images may include depth-time dimensions and pulse-time dimensions. In some examples, blood pressure may be determined based on 2D PAPG images. For example, FIG. 5 The control system 502 of the biometric system 500 can generate a 2D PAPG image 514 based on volumetric data 512 including PAPG data, and can determine blood pressure 516 based on the 2D PAPG image 514. In some examples, a blood pressure prediction model can be used to determine blood pressure based on the 2D PAPG image, which is trained using a deep learning network (DLN) (such as a long short-term memory (LSTM) neural network or a convolutional neural network). For example, FIG. 5 The control system 502 of the biometric system 500 can use a blood pressure prediction model to determine blood pressure 516 based on a 2D PAPG image 514, which is generated based on volumetric data 512 including PAPG data. The blood pressure prediction model is trained using a deep learning network (DLN) (such as an LSTM neural network or a convolutional neural network). In some examples, the 2D PAPG image may include a depth time dimension and a pulse time dimension.

[0098] At position 635, the photoacoustic sampling system can be deactivated at the end of the cardiac phase transition window. For example, FIG. 5The control system 502 of the biometric system 500 may deactivate the photoacoustic sampling system 504 at the end of the cardiac phase transition window 529. In some examples, the photoacoustic sampling system may be deactivated before the end of the cardiac phase transition window in response to determining that the volumetric data includes at least a threshold number of samples. In some other examples, the photoacoustic sampling system may be deactivated at the end of the cardiac phase transition window in response to determining that the cardiac phase transition window has ended.

[0099] According to various aspects of this disclosure, such as FIG. 7A The biometric system 500 can be configured to distinguish venous heart rate waveforms and arterial heart rate waveforms by acquiring depth-distinguishing signals. FIG. 7B An example of a range gating window (RGW) selected to receive sound waves emitted from different depth ranges is shown. The time delay or range gating delay is obtained (in...). FIG. 8A The marker "RGD" is measured from the start time t1 of the photoexcitation signal 705 shown in Figure 700. For example, RGD can be selected to correspond to the time required for the photoacoustic emission to reach the receiver from the shallowest target of interest, for example, as referenced below. FIG. 8B and FIG. 7B As described. Therefore, RGD can depend on the specific arrangement of the apparatus used to receive the photoacoustic emission, including the thickness of the layer between the target and the receiver, and the sound velocity of the layer between the target and the receiver. Figure 701 depicts the time following RGD, during which the emitted sound waves can be received and sampled by the ultrasonic receiver during the acquisition time window of the RGW (also known as the range gating window or range gating width). In some embodiments, the RGW can be 10 microseconds. Other embodiments may have larger or smaller RGWs.

[0100] In some examples, depth-distinguishing signals can be obtained by dividing the acoustic waves received during the RGW into multiple smaller time windows. Each time window can correspond to a depth range within the target object where the acoustic waves are received. In some examples, the depth range or thickness of each layer can be 0.5 mm. Assuming a sound velocity of 1.5 mm / µs, each 0.5 mm layer would correspond to a time slot of approximately 0.33 µs. However, the depth range can vary depending on the specific implementation.

[0101] According to some alternative examples, receiving a signal from a piezoelectric receiver involves applying the first to the second... N The depth differentiation signal is obtained by acquiring the time delay, and in the first to the second... N During the acquisition time window, receive the first to the second N Signals, from the first to the last N Each of the time acquisition windows in the first to the second time acquisition window NThe event occurs after a specific acquisition time delay, where... N It is an integer greater than one. The control system can be configured to determine a first subset and a second subset of the detected heart rate waveforms, at least in part, based on the depth-discriminating signal.

[0102] FIG. 7B Examples of multiple acquisition time delays selected for receiving sound waves emitted from different depths are shown. In these examples, (in FIG. 8A Each of the acquisition time delays (marked as distance gating delay or RGD) is from the start time t of the photoexcitation signal 705 shown in Figure 700. l Measurements are initiated. Figure 710 depicts the emitted acoustic wave (received wave (1) is an example), which can be received by an ultrasonic sensor array at the acquisition time delay RGD1 and sampled during the acquisition time window (also known as the distance gating window or distance gating width) of RGW1. Such acoustic waves are typically emitted from a relatively shallower portion of a target object located near the pressure plate of the biometric system or positioned on the pressure plate.

[0103] Figure 715 depicts the emitted sound wave (received wave (2) is an example), which is received by an ultrasonic sensor array at an acquisition time delay RGD2 (where RGD2 > RGD1) and sampled during the acquisition time window of RGW2. Such sound waves are typically emitted from a relatively deeper part of the target object.

[0104] Figure 720 depicts the emitted sound wave (the received wave (n) is an example), which has an acquisition time delay RGD. n (of which RGD) n Received at RGD2>RGD1) and in RGW n Sampling is performed during the acquisition time window. Such acoustic waves are typically emitted from a deeper portion of the target object. The range gating delay is typically an integer multiple of the clock cycle. For example, a clock frequency of 128 MHz has a clock cycle of 7.8125 nanoseconds, and the RGD range can be from less than 10 nanoseconds to over 2000 nanoseconds. Similarly, the range gating width can also be an integer multiple of the clock cycle, but is typically much shorter than the RGD (e.g., less than about 50 nanoseconds) to capture the return signal while maintaining good axial resolution. In some specific implementations, the acquisition time window (e.g., RGW) may range from 175 nanoseconds to 320 nanoseconds or even longer. In some examples, the RGW may be longer or shorter, for example, in the range of 25 nanoseconds to 1000 nanoseconds.

[0105] FIG. 8B and FIG. 8AAn example of a device configured to receive sound waves emitted from different depths is shown. FIG. 8B and FIG. 2 The device shown is FIG. 8A An example of the apparatus 200 is shown. As with other specific embodiments shown and described herein, FIG. 8B and FIG. 8A The component types, component arrangements, and component sizes shown are merely illustrative examples.

[0106] According to this example, device 200 includes an ultrasonic receiver 202, a light source system 204 (including an LED in this example), and a control system (not shown in the example). FIG. 8B and FIG. 8A (As shown in the figure). According to this embodiment, the device 200 has a beam splitter 801 on the side 802 where the LED is mounted. In this example, a finger 806 rests on the adjacent side 804 of the beam splitter 801.

[0107] FIG. 8A The image shows light emitted from the light source system 204, a portion of which is reflected by beam splitter 801 and enters finger 806. The distance gating delay used in this and other embodiments can, for example, be selected to correspond to the time required for the photoacoustic emission to reach the receiver from the shallowest target of interest. For example, in device 200, an ultrasonic receiver 202 is used with finger 806. FIG. 8B In a configuration where a 12.7mm beamsplitter is used between the RX and the signal, the arrival time of the signal on the finger surface is equal to the time it takes for the sound wave to travel through the entire beamsplitter. Using the speed of sound of borosilicate glass, 5500 m / s, as an approximation of the speed of sound for the beamsplitter, and with a beamsplitter size of 12.7mm, this time becomes 12.7mm / 5500m / s, or 2.3μs. Therefore, a distance gating delay of 2.3μs corresponds to the surface of finger 806. For example, using the current tissue speed of sound, 1.5mm / μs, to travel 1mm into finger 806, this time becomes 1mm / 1.5mm / μs, or approximately 0.67μs. Therefore, a distance gating delay of approximately 2.97μs (2.3μs + 0.67μs) will cause the ultrasonic receiver 202 to begin sampling the sound wave reflected from a depth of approximately 1mm below the outer surface of finger 806.

[0108] FIG. 8B The acoustic signals corresponding to the photoacoustic emission from tissues (e.g., blood and blood vessels) within the finger 806 caused by light entering the finger 806 are shown. FIG. 7BIn the example shown, the acoustic signals originate from different depths (depths 808a, 808b, and 808c) within the finger 806. Therefore, the propagation times t1, t2, and t3 from depths 808a, 808b, and 808c to the ultrasonic receiver 202 are also different: in this example, t3 > t2 > t1. Thus, multiple acquisition time delays can be selected to receive sound waves emitted from depths 808a, 808b, and 808c, for example, as... FIG. 9 As shown, and as described above.

[0109] FIG. 5 It shows that it can execute FIG. 9 An example of a cross-sectional view of the apparatus for the method. FIG. 2 The device 200 shown is the reference above. FIG. 9 Another example of the described apparatus 200. Similar to other specific embodiments shown and described herein, FIG. 9 The component types, component arrangements, and component sizes shown are merely illustrative examples.

[0110] FIG. 9 An example of a target object (finger 806 in this example) illuminated by incident light and subsequently emitting sound waves is shown. In this example, device 200 includes a light source system 204, which may include an array of light-emitting diodes and / or an array of laser diodes. In some embodiments, light source system 204 may be able to emit light of various wavelengths, which may be selectable to trigger sound wave emission primarily from a specific type of material. In some instances, the incident light wavelength, wavelength, and / or wavelength range may be selected to trigger sound wave emission primarily from a specific type of material (e.g., blood, blood vessels, other soft tissue, or bone). To achieve sufficient image contrast, the light source 904 of light source system 204 may need to have a higher intensity and optical power output than light sources typically used to illuminate displays. In some embodiments, a light source with a light output of 1 to 100 millijoules or more per pulse (e.g., 10 millijoules per pulse) and a pulse width in the range of 100 nanoseconds to 600 nanoseconds may be suitable. In some embodiments, the pulse width of the emitted light may be between 10 nanoseconds and 700 nanoseconds.

[0111] In this example, incident light 911 has been emitted from the light source 904 of the light system 204, passed through the sensor stack 905, and entered the finger 806 above. Various layers of the sensor stack 905 may include substrates of one or more glass or other materials (such as plastic or sapphire) that are substantially transparent to the light emitted by the light source system 204. In this example, the sensor stack 905 includes a substrate 910 to which the light source system 204 is coupled; according to some embodiments, the light source system may be a backlight for a display. In alternative embodiments, the light source system 204 may be coupled to a headlight. Thus, in some embodiments, the light source system 204 may be configured to illuminate a display and a target object.

[0112] In this embodiment, substrate 910 is coupled to thin-film transistor (TFT) substrate 915 of ultrasonic receiver 202, in this example, the ultrasonic receiver includes an array of sensor pixels 902. According to this example, piezoelectric receiver layer 920 covers the sensor pixels 902 of ultrasonic receiver 202, and pressure plate 925 covers piezoelectric receiver layer 920. Therefore, in this example, device 200 is able to allow incident light 911 to transmit through one or more substrates of sensor stack 905, which includes ultrasonic receiver 202 having substrate 915 and pressure plate 925, the pressure plate also being considered a substrate. In some embodiments, the sensor pixels 902 of ultrasonic receiver 202 may be transparent, partially transparent, or substantially transparent, such that device 200 is able to allow incident light 911 to transmit through the elements of ultrasonic receiver 202. In some embodiments, ultrasonic receiver 202 and associated circuitry may be formed on or within a glass, plastic, or silicon substrate.

[0113] Depending on some specific implementations, device 200 may include an ultrasonic transmitter 927, such as FIG. 9 The ultrasonic transmitter 927 is shown. Depending on the specific implementation, the ultrasonic transmitter may or may not be part of the ultrasonic receiver 202. In some examples, the ultrasonic receiver 202 may include PMUT or CMUT elements capable of transmitting and receiving ultrasonic waves, and the piezoelectric receiver layer 920 may be replaced by an acoustic coupling layer. In some examples, the ultrasonic receiver 202 may include an array of pixel input electrodes and sensor pixels partially formed by TFT circuitry, an overlying piezoelectric receiver layer 920 having a piezoelectric material (such as PVDF or PVDF-TrFE), and an upper electrode layer (sometimes referred to as a receiver bias electrode) located on the piezoelectric receiver layer. FIG. 9 In the example shown, at least a portion of the device 200 includes an ultrasonic transmitter 927 that can be used as a plane wave ultrasonic transmitter. The ultrasonic transmitter 927 may, for example, include a piezoelectric transmitter layer, wherein transmitter excitation electrodes are disposed on each side of the piezoelectric transmitter layer.

[0114] Here, incident light 911 induces photoexcitation within finger 806, thereby generating sound waves. In this example, the generated sound waves 913 comprise ultrasound. The acoustic emission generated by absorbing the incident light can be detected by ultrasound receiver 202. Because the resulting ultrasound is caused by light stimulation rather than by reflection of the transmitted ultrasound, a high signal-to-noise ratio is achieved.

[0115] In this example, device 200 includes a control system, although the control system is not in FIG. 10 As shown in the figure. According to some examples, the control system can be configured to distinguish venous heart rate waveforms and arterial heart rate waveforms by acquiring a depth-discriminating signal. According to some such examples, receiving a signal from a piezoelectric receiver involves acquiring a depth-discriminating signal by selecting an acquisition time window to receive sound waves emitted from different depth ranges within a target object (e.g., fingers, wrists, ears, etc.). In some examples, the depth-discriminating signal can be obtained by a process of dividing the sound waves received during the RGW into multiple smaller time windows, for example, as described above. Each time window may correspond to a depth range within the target object where the sound waves are received. According to some alternative examples, receiving a signal from a piezoelectric receiver involves applying a first to a second... N The depth differentiation signal is obtained by acquiring the time delay, and in the first to the second... N During the acquisition time window, receive the first to the second N Signals, from the first to the last N Each of the time acquisition windows in the first to the second time acquisition window N The event occurs after a specific acquisition time delay, where... N It is an integer greater than one. The control system can be configured to determine venous heart rate waveforms and arterial heart rate waveforms, at least in part, based on depth-distinguishing signals.

[0116] FIG. 2This is a block diagram illustrating an example heart rate waveform generation process 1000 according to some specific implementations. According to the heart rate waveform generation process 1000, at 1004, the raw 2D PAPG data 1003 can undergo a one-dimensional fast Fourier transform to obtain a spectral amplitude parameter 1005 associated with the raw 2D PAPG data 1003. At 1006, a horizontal projection can be performed based on the spectral amplitude parameter 1005 to obtain a 1D column 1007. At 1008, heart rate detection can be performed to identify a frequency 1009 based on the 1D column 1007. At 1010, the frequency 1009 can serve as the basis for region of interest (ROI) selection, thereby selecting a frequency band 1011. At 1012, a vertical projection can be performed based on the spectral amplitude parameter 1005 and the frequency band 1011 to obtain a 1D column 1013. At 1014, active pixel identification can be performed to determine a depth frequency band 1015 based on the 1D column 1013. At 1016, the depth band 1015 can serve as input for the arterial / venous (A / V) score, which generates an A / V score 1017. At 1018, active pixel grouping can determine the A / V band 1019 based on the A / V score 1017. At 1020, heart rate waveform generation can be performed based on the determination of the A / V band 1019 to generate a heart rate waveform 1021.

[0117] In some specific implementations, FIG. 2Some or all components of device 200 may be arranged, assembled, or otherwise included within a single housing of a single motion monitoring device. In some examples, the housing and other components of the motion monitoring device may be configured such that, when the motion monitoring device is secured or otherwise physically coupled to a subject, the light source system 204 will emit light pulses along a segment of an artery into the tissue, assuming that various arterial characteristics along that segment are relatively constant. In various embodiments, the housing of the motion monitoring device is a wearable housing or integrated into or integrated with a wearable housing. In some specific embodiments, the wearable housing includes (or is connected to) a physical coupling mechanism for detachable, non-invasive connection to a user. The housing may be formed using any of a variety of suitable manufacturing processes, including injection molding and vacuum forming. Furthermore, the housing may be made of any of a variety of suitable materials, including but not limited to plastics, metals, glass, rubber, and ceramics, or combinations of these or other materials. In various embodiments, the housing and coupling mechanism enable fully dynamic use. In other words, some specific implementations of the wearable monitoring devices described in this article are non-invasive, do not impose physical restrictions, and generally do not restrict the free and uninhibited movement of the subject's arms or legs, thus enabling continuous or periodic monitoring of cardiovascular characteristics, such as blood pressure, even while the subject is active or performing other physical activities. Therefore, dynamic monitoring devices can facilitate and enable long-term wear and monitoring (e.g., for days, weeks, or months or longer without interruption) of one or more biometrics of interest to gain a comprehensive understanding of changes in such characteristics over a longer period and a more holistic understanding of the user's overall health status.

[0118] In some specific implementations, FIG. 11A Some or all of the components of the device 200 may be arranged, assembled or otherwise included within the housing of the motion monitoring device, which, similar to a watch or fitness / activity tracker, can be positioned on the user's wrist via a wristband or watch strap. FIG. 2 An example motion monitoring device 1100, designed to be worn on the wrist according to some specific embodiments, is shown. In the illustrated example, the monitoring device 1100 includes a housing 1102 integrally formed, coupled, or otherwise integrated with a wristband or watch strap 1104. In this example, the motion monitoring device 1100 is coupled around the wrist such that a light source system within the housing 1102 emits light pulses along an artery 1105 into the tissue.

[0119] In some other specific implementations, FIG. 11B Some or all of the components of the device 200 may be arranged, assembled or otherwise included in the housing of a dynamic monitoring device, which may be similarly designed or adapted to be positioned on the forearm, upper arm, ankle, calf, thigh or finger using a wristband or watch strap. FIG. 2An example motion monitoring device 1110, designed to be worn on a finger according to some specific embodiments, is shown. In the illustrated example, the monitoring device 1110 includes a housing 1112 integrally formed, coupled, or otherwise integrated with a wristband or watchband 1114. In this example, the motion monitoring device 1110 is coupled around the finger such that a light source system within the housing 1112 emits light pulses into the tissue along an artery 1115.

[0120] In some other specific implementations, FIG. 2 Some or all of the components of the device 200 may be arranged, assembled, or otherwise included within the housing of a motion monitoring device that can be positioned in an area of ​​interest to the user without the need for a wristband or watch strap. For example, FIG. 11C Some or all of the components of the device 200 may be arranged, assembled or otherwise included in a housing that is secured to the skin of the user’s area of ​​interest using an adhesive or other suitable connection mechanism (example of a “patch” monitoring device).

[0121] ​ An example motion monitoring device 1120, designed to be located on an earbud according to some specific implementation, is shown. According to this example, the motion monitoring device 1120 is coupled to the housing of the earbud 1130. In this example, the motion monitoring device 1120 is positioned such that a light source system within the housing 1122 will emit light pulses along an artery 1125 into the tissue.

[0122] Specific implementation examples are described in the following numbered clauses: Clause 1. A biometric system comprising: a heart rate waveform analyzer configured to monitor a heart rate waveform associated with a subject to detect cardiac cycle markers, and to determine a cardiac phase transition window based on the cardiac cycle markers; a photoacoustic sampling system including a piezoelectric receiver and a light source system; and a control system configured to: activate the photoacoustic sampling system at the beginning of the cardiac phase transition window; during the cardiac phase transition window: control the light source system to emit a plurality of light pulses into the subject's biological tissue, the biological tissue including blood and blood vessels located deep within the biological tissue; receive from the piezoelectric receiver signals corresponding to sound waves emitted from various portions of the biological tissue, the sound waves corresponding to photoacoustic emissions from the blood and blood vessels caused by the plurality of light pulses; obtain plethysmography data based on the signals; and deactivate the photoacoustic sampling system at the end of the cardiac phase transition window.

[0123] Clause 2. The biometric system according to Clause 1, wherein the control system is further configured to: in response to determining that the plethysmography data comprises at least a threshold number of samples before the end of the cardiac phase transition window, deactivate the photoacoustic sampling system before the end of the cardiac phase transition window.

[0124] Clause 3. A biometric system according to any one of Clauses 1 to 2, wherein the cardiac phase transition window corresponds to the transition from systole to diastole.

[0125] Clause 4. A biometric system according to any one of Clauses 1 to 2, wherein the cardiac phase transition window corresponds to the transition from diastole to systole.

[0126] Clause 5. A biometric system according to any one of Clauses 1 to 4, wherein the heart rate waveform analyzer is further configured to obtain the heart rate waveform based on a data stream received from a cardiac activity sensor.

[0127] Clause 6. The biometric system according to any one of Clauses 1 to 5, wherein the control system is further configured to: determine blood pressure based on the plethysmography data, and display the blood pressure on a display.

[0128] Clause 7. The biometric system according to Clause 6, wherein the control system is further configured to determine the blood pressure based on systolic data included in the plethysmography data, without referring to diastolic data included in the plethysmography data.

[0129] Clause 8. A biometric system according to any one of Clauses 1 to 7, wherein the volumetric data is photoacoustic volumetric data (PAPG).

[0130] Clause 9. The biometric system according to Clause 8, wherein the control system is further configured to generate a two-dimensional (2D) PAPG image based on the PAPG data.

[0131] Clause 10. The biometric system according to Clause 9, wherein the 2D PAPG image includes a depth-time dimension and a pulse-time dimension.

[0132] Clause 11. A biometric method comprising: monitoring a heart rate waveform associated with a subject to detect cardiac cycle markers; determining a cardiac phase transition window based on the cardiac cycle markers; activating a photoacoustic sampling system at the beginning of the cardiac phase transition window, the photoacoustic sampling system including a piezoelectric receiver and a light source system; during the cardiac phase transition window: controlling the light source system to emit a plurality of light pulses into biological tissue of the subject, the biological tissue including blood and blood vessels located deep within the biological tissue; receiving from the piezoelectric receiver signals corresponding to sound waves emitted from various portions of the biological tissue, the sound waves corresponding to photoacoustic emissions from the blood and blood vessels caused by the plurality of light pulses; and obtaining plethysmography data based on the signals; and deactivating the photoacoustic sampling system at the end of the cardiac phase transition window.

[0133] Clause 12. The biometric method according to Clause 11, further comprising: in response to determining that the plethysmography data comprises at least a threshold number of samples before the end of the cardiac phase transition window, deactivating the photoacoustic sampling system before the end of the cardiac phase transition window.

[0134] Clause 13. The biometric method according to any one of Clauses 11 to 12, wherein the cardiac phase transition window corresponds to the transition from systole to diastole.

[0135] Clause 14. The biometric method according to any one of Clauses 11 to 12, wherein the cardiac phase transition window corresponds to the transition from diastole to systole.

[0136] Clause 15. The biometric method according to any one of Clauses 11 to 14, the biometric method further comprising: obtaining the heart rate waveform based on a data stream received from a cardiac activity sensor.

[0137] Clause 16. The biometric method according to any one of Clauses 11 to 15, the biometric method further comprising: determining blood pressure based on the plethysmography data, and displaying the blood pressure on a display.

[0138] Clause 17. The biometric method according to Clause 16 further includes: determining the blood pressure based on systolic data included in the plethysmography data, without referring to diastolic data included in the plethysmography data.

[0139] Clause 18. The biometric method according to any one of Clauses 11 to 17, wherein the volumetric data is photoacoustic volumetric data (PAPG).

[0140] Clause 19. The biometric method according to Clause 18, further comprising: generating a two-dimensional (2D) PAPG image based on the PAPG data.

[0141] Clause 20. The biometric method according to Clause 19, wherein the 2D PAPG image includes a depth-time dimension and a pulse-time dimension.

[0142] Clause 21. One or more non-transient media having software stored thereon, the software including instructions for controlling one or more devices to perform a biometric method comprising: monitoring a heart rate waveform associated with a subject to detect cardiac cycle markers; determining a cardiac phase transition window based on the cardiac cycle markers; activating a photoacoustic sampling system at the beginning of the cardiac phase transition window, the photoacoustic sampling system including a piezoelectric receiver and a light source system; during the cardiac phase transition window: controlling the light source system to emit a plurality of light pulses into the subject's biological tissue, the biological tissue including blood and blood vessels located deep within the biological tissue; receiving from the piezoelectric receiver signals corresponding to sound waves emitted from various portions of the biological tissue, the sound waves corresponding to photoacoustic emissions from the blood and blood vessels caused by the plurality of light pulses; and obtaining plethysmographic data based on the signals; and deactivating the photoacoustic sampling system at the end of the cardiac phase transition window.

[0143] Clause 22. One or more non-transient media as described in Clause 21, wherein the biometric method further comprises: in response to determining that the volumetric data includes at least a threshold number of samples before the end of the cardiac phase transition window, deactivating the photoacoustic sampling system before the end of the cardiac phase transition window.

[0144] Clause 23. One or more nontransient media according to any one of Clauses 21 to 22, wherein the cardiac phase transition window corresponds to the transition from systole to diastole.

[0145] Clause 24. One or more nontransient media according to any one of Clauses 21 to 22, wherein the cardiac phase transition window corresponds to the transition from diastole to systole.

[0146] Clause 25. One or more non-transient media according to any one of Clauses 21 to 24, wherein the biometric method further comprises: obtaining the heart rate waveform based on a data stream received from a cardiac activity sensor.

[0147] Clause 26. One or more non-transient media according to any one of Clauses 21 to 25, wherein the biometric method further comprises: determining blood pressure based on the plethysmography data, and displaying the blood pressure on a display.

[0148] Clause 27. One or more non-transient media as described in Clause 26, wherein the biometric method further comprises: determining the blood pressure based on systolic data included in the plethysmography data, without referring to diastolic data included in the plethysmography data.

[0149] Clause 28. One or more non-transient media according to any one of Clauses 21 to 27, wherein the volumetric data is photoacoustic volumetric data (PAPG).

[0150] Clause 29. One or more non-transient media as described in Clause 28, wherein the biometric method further comprises: generating a two-dimensional (2D) PAPG image based on the PAPG data.

[0151] Clause 30. One or more non-transient media as described in Clause 29, wherein the 2D PAPG image includes a depth time dimension and a pulse time dimension.

[0152] Clause 31. An apparatus comprising: a photoacoustic system including a piezoelectric receiver and a light source system; and a control system configured to: receive heart rate waveform data from a heart rate waveform analyzer; activate a photoacoustic sampling system at the beginning of a cardiac phase transition window, the cardiac phase transition window being indicated by the heart rate waveform data; during the cardiac phase transition window: control the light source system to emit a plurality of light pulses into a subject's biological tissue, the biological tissue including blood and blood vessels located deep within the biological tissue; receive signals from the piezoelectric receiver corresponding to sound waves emitted from various portions of the biological tissue, the sound waves corresponding to photoacoustic emissions from the blood and blood vessels caused by the plurality of light pulses; obtain plethysmography data based on the signals; and deactivate the photoacoustic sampling system at the end of the cardiac phase transition window.

[0153] Clause 32. The apparatus according to Clause 31, wherein the control system is further configured to: deactivate the photoacoustic sampling system before the end of the cardiac phase transition window in response to determining that the volumetric data comprises at least a threshold number of samples before the end of the cardiac phase transition window.

[0154] Clause 33. A biometric system according to any one of Clauses 31 to 32, wherein the cardiac phase transition window corresponds to the transition from systole to diastole.

[0155] Clause 34. A biometric system according to any one of Clauses 31 to 32, wherein the cardiac phase transition window corresponds to the transition from diastole to systole.

[0156] Clause 35. In any one of Clauses 31 to 34, the heart rate waveform analyzer is configured to obtain the heart rate waveform based on a data stream received from a cardiac activity sensor.

[0157] Clause 36. The biometric system according to any one of Clauses 31 to 35, wherein the control system is further configured to: determine blood pressure based on the plethysmography data, and display the blood pressure on a display.

[0158] Clause 37. The biometric system of Clause 36, wherein the control system is further configured to determine the blood pressure based on systolic data included in the plethysmography data, without referring to diastolic data included in the plethysmography data.

[0159] Clause 38. A biometric system according to any one of Clauses 31 to 37, wherein the volumetric data is photoacoustic volumetric data (PAPG).

[0160] Clause 39. The biometric system according to Clause 38, wherein the control system is further configured to generate a two-dimensional (2D) PAPG image based on the PAPG data.

[0161] Clause 40. The biometric system according to Clause 39, wherein the 2D PAPG image includes a depth-time dimension and a pulse-time dimension.

[0162] Unless otherwise indicated, the terms “estimating,” “measuring,” “calculating,” “inferring,” “deducing,” “evaluating,” “determining,” and “monitoring” may be used interchangeably in this document where appropriate. Similarly, derivatives of the roots of these terms may also be used interchangeably where appropriate; for example, the terms “estimate,” “measurement,” “calculation,” “inference,” and “determination” may also be used interchangeably in this document.

[0163] The various exemplary logics, logic blocks, modules, circuits, and algorithmic processes described in conjunction with the specific implementations disclosed herein can be implemented as electronic hardware, computer software, or a combination of both. The interchangeability of hardware and software has been broadly described in terms of functionality and illustrated in the aforementioned exemplary components, blocks, modules, circuits, and processes. Whether such functionality is implemented in hardware or software depends on the specific application and the design constraints imposed on the overall system.

[0164] Hardware and data processing means for implementing the various exemplary logic units, logic blocks, modules, and circuits described herein can be implemented or executed using general-purpose single-chip or multi-chip processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic units, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor can be a microprocessor, or any conventional processor, controller, microcontroller, or state machine. A processor can also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors combined with a DSP core, or any other such configuration. In some specific implementations, specific processes and methods can be performed by circuitry specific to a given function.

[0165] In one or more aspects, the described functionality may be implemented in hardware, digital electronic circuits, computer software, firmware, including the structures disclosed in this specification and their structural equivalents or any combination thereof. Specific implementations of the subject matter described in this specification may also be implemented as one or more computer programs, i.e., one or more modules of computer program instructions encoded on a computer storage medium for execution by a data processing apparatus or for controlling the operation of a data processing apparatus.

[0166] If implemented in software, the functions can be stored as one or more instructions or codes on or transmitted via a computer-readable medium such as a non-transitory medium. The processes of the methods or algorithms disclosed herein can be implemented in a processor-executable software module that can reside on a computer-readable medium. Computer-readable media include both computer storage media and communication media, including any medium capable of transferring a computer program from one location to another. Storage media can be any available medium accessible to a computer. By way of example and not limitation, non-transitory media can include RAM, ROM, EEPROM, CD-ROM or other optical disc storage devices, disk storage devices or other magnetic storage devices, or any other medium that can be used to store desired program code in the form of instructions or data structures and is accessible to a computer. Additionally, any connection can be appropriately referred to as a computer-readable medium. As used herein, disks and optical discs include compact optical discs (CDs), laser discs, optical discs, digital versatile optical discs (DVDs), floppy disks, and Blu-ray discs, wherein disks typically magnetically reproduce data, while optical discs optically reproduce data using lasers. Combinations of the above should also be included within the scope of computer-readable media. In addition, the operation of a method or algorithm may reside as a set of code and instructions or any combination of code and instructions on a machine-readable medium and a computer-readable medium that may be incorporated into a computer program product.

[0167] Various modifications to the specific embodiments described herein may be apparent to those skilled in the art, and the general principles defined herein may be applied to other specific embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not intended to be limited to the specific embodiments shown herein, but is to be accorded the widest scope consistent with the claims, principles, and novel features disclosed herein. The word “exemplary” (if any) is used herein specifically to mean “serving as an example, instance, or illustration.” Any specific embodiment described herein as “exemplary” is not necessarily to be construed as superior to or better than other specific embodiments.

[0168] Certain features described in this specification in the context of a single embodiment may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments. Furthermore, although features may be described above as operating in certain combinations and even originally claimed in this way, one or more features from the claimed combination may be removed from that combination in some cases, and the claimed combination may be for sub-combinations or variations thereof.

[0169] Similarly, although operations are depicted in a specific order in the accompanying drawings, this should not be construed as requiring such operations to be performed in the shown specific order or sequential order, or to perform all illustrated operations to achieve the desired result. In some environments, multitasking and parallel processing are advantageous. Furthermore, the separation of the various system components in the embodiments described above should not be construed as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products. Additionally, other embodiments are within the scope of the following claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve the desired result.

[0170] It should be understood that unless features in any particular embodiment of the description are explicitly identified as incompatible with each other, or the surrounding context suggests that they are mutually exclusive and not easily combined in a complementary and / or supporting sense, the general conception and ideas of this disclosure may be selectively combined with specific features of those complementary embodiments to provide one or more comprehensive but slightly different technical solutions. Therefore, it should also be understood that the above description is given by way of example only and may be modified in detail within the scope of this disclosure.

[0171] Various modifications to the specific embodiments described in this disclosure will be apparent to those skilled in the art, and the general principles defined herein may be applied to other specific embodiments without departing from the spirit or scope of this disclosure. Therefore, the following claims are not intended to limit the specific embodiments shown herein, but should be given the maximum scope consistent with this disclosure, the principles disclosed herein, and the novel features.

[0172] Furthermore, certain features described in the context of a single embodiment in this specification may also be implemented in combination within a single embodiment. Conversely, individual features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments. Moreover, while some features are described above as working in a particular combination and even initially claimed in this way, in some cases, one or more features from the claimed combination may be extracted from that combination, and the claimed combination may involve sub-combinations or variations thereof.

[0173] Similarly, although operations are depicted in a specific order in the accompanying drawings, this should not be construed as requiring such operations to be performed in the indicated specific order or sequential order, or to perform all illustrated operations to achieve the desired result. Furthermore, the drawings may schematically depict one or more example processes in the form of flowcharts. However, other operations not depicted may be incorporated into the schematically illustrated example processes. For example, one or more additional operations may be performed before, after, simultaneously with, or between any of the illustrated operations. Moreover, the various operations in the described and illustrated operations may themselves include and together be referred to as multiple sub-operations. For example, each of the above operations may itself involve the execution of a process or algorithm. Furthermore, in some embodiments, the various operations in the described and illustrated operations may be combined or performed in parallel. Similarly, the separation of various system components in the above embodiments should not be construed as requiring such separation in all embodiments. Therefore, other embodiments are also within the scope of the following claims. In some cases, the actions recited in the claims may be performed in a different order and still achieve the desired result.

Claims

1. A biometric identification system comprising: a heart rate waveform analyzer configured to: monitor a heart rate waveform associated with a subject to detect a cardiac cycle marker; and determine a cardiac phase transition window based on the cardiac cycle marker; a photoacoustic sampling system comprising: a piezoelectric receiver; and a light source system; and a control system configured to: initiate the photoacoustic sampling system at a start of the cardiac phase transition window; during the cardiac phase transition window: control the light source system to emit a plurality of light pulses into biological tissue of the subject, the biological tissue including blood and blood vessels located deep within the biological tissue; receive, from the piezoelectric receiver, signals corresponding to acoustic waves emitted from portions of the biological tissue, the acoustic waves corresponding to photoacoustic emissions from the blood and the blood vessels caused by the plurality of light pulses; and obtain plethysmography data based on the signals; and deactivate the photoacoustic sampling system at an end of the cardiac phase transition window.

2. The biometric identification system of claim 1, wherein the control system is further configured to deactivate the photoacoustic sampling system prior to the end of the cardiac phase transition window in response to determining that the plethysmography data includes at least a threshold number of samples prior to the end of the cardiac phase transition window.

3. The biometric identification system of claim 1, wherein the cardiac phase transition window corresponds to a systole-to-diastole transition.

4. The biometric identification system of claim 1, wherein the cardiac phase transition window corresponds to a diastole-to-systole transition.

5. The biometric identification system of claim 1, wherein the heart rate waveform analyzer is further configured to obtain the heart rate waveform based on a data stream received from a cardiac activity sensor.

6. The biometric identification system of claim 1, wherein the control system is further configured to: determine a blood pressure based on the plethysmography data; and display the blood pressure on a display.

7. The biometric identification system of claim 6, wherein the control system is further configured to determine the blood pressure based on systole period data included in the plethysmography data without reference to diastole period data included in the plethysmography data.

8. The biometric identification system of claim 1, wherein the plethysmography data is photoacoustic plethysmography (PAPG) data.

9. The biometric identification system of claim 8, wherein the control system is further configured to generate a two-dimensional (2D) PAPG image based on the PAPG data.

10. The biometric identification system of claim 9, wherein the 2D PAPG image includes a depth-time dimension and a pulse-time dimension.

11. A biometric identification method comprising: monitoring a heart rate waveform associated with a subject to detect a cardiac cycle marker; determining a cardiac phase transition window based on the cardiac cycle marker; initiating a photoacoustic sampling system at a start of the cardiac phase transition window, the photoacoustic sampling system comprising a piezoelectric receiver and a light source system; ​ during the cardiac phase transition window: control the light source system to emit a plurality of light pulses into biological tissue of the subject, the biological tissue including blood and blood vessels located deep within the biological tissue; receive, from the piezoelectric receiver, signals corresponding to acoustic waves emitted from portions of the biological tissue, the acoustic waves corresponding to photoacoustic emissions from the blood and the blood vessels caused by the plurality of light pulses; and obtain plethysmography data based on the signals; and deactivate the photoacoustic sampling system at an end of the cardiac phase transition window.

12. The method of biorecognition according to claim 11, further comprising: deactivate the photoacoustic sampling system prior to an end of the cardiac phase transition window in response to determining that the plethysmography data includes at least a threshold number of samples prior to the end of the cardiac phase transition window.

13. The biometric method of claim 11, wherein the cardiac phase transition window corresponds to a systole-to-diastole transition.

14. The biometric method of claim 11, wherein the cardiac phase transition window corresponds to a diastole-to-systole transition.

15. The method of biorecognition of claim 11, further comprising: obtain the heart rate waveform based on a data stream received from a heart activity sensor.

16. The biometric method of claim 11, further comprising: determine a blood pressure based on the plethysmography data; and display the blood pressure on a display.

17. The method of biorecognition according to claim 16, further comprising: determine the blood pressure based on systole data included in the plethysmography data without reference to diastole data included in the plethysmography data.

18. The biometric method of claim 11, wherein the plethysmography data is photoacoustic plethysmography (PAPG) data.

19. The method of biorecognition according to claim 18, further comprising: generate a two-dimensional (2D) PAPG image based on the PAPG data.

20. The biometric method of claim 19, wherein the 2D PAPG image includes a depth-time dimension and a pulse-time dimension.

21. One or more non-transitory media having software stored thereon, the software including instructions for controlling one or more devices to perform a biometric method, the biometric method comprising: monitor a heart rate waveform associated with a subject to detect a cardiac cycle marker; determine a cardiac phase transition window based on the cardiac cycle marker; activate a photoacoustic sampling system at a beginning of the cardiac phase transition window, the photoacoustic sampling system including a piezoelectric receiver and a light source system; during the cardiac phase transition window: control the light source system to emit a plurality of light pulses into biological tissue of the subject, the biological tissue including blood and blood vessels located deep within the biological tissue; receive, from the piezoelectric receiver, signals corresponding to acoustic waves emitted from portions of the biological tissue, the acoustic waves corresponding to photoacoustic emissions from the blood and the blood vessels caused by the plurality of light pulses; and obtain plethysmography data based on the signals; and deactivate the photoacoustic sampling system at an end of the cardiac phase transition window.

22. The one or more non-transitory media of claim 21, wherein the biometric method further comprises: deactivate the photoacoustic sampling system prior to an end of the cardiac phase transition window in response to determining that the plethysmography data includes at least a threshold number of samples prior to the end of the cardiac phase transition window.

23. The one or more non-transitory media of claim 21, wherein the cardiac phase transition window corresponds to a systole-to-diastole transition.

24. The one or more non-transitory media of claim 21, wherein the cardiac phase transition window corresponds to a diastole-to-systole transition.

25. The one or more non-transitory media of claim 21, wherein the biometric method further comprises: obtaining the heart rate waveform based on a data stream received from a heart activity sensor.

26. The one or more non-transitory media of claim 21, wherein the biometric method further comprises: determining a blood pressure based on the plethysmography data; and displaying the blood pressure on a display.

27. The one or more non-transitory media of claim 26, wherein the biometric method further comprises: determining the blood pressure based on systole data included in the plethysmography data without reference to diastole data included in the plethysmography data.

28. The one or more non-transitory media of claim 21, wherein the plethysmography data is photoacoustic plethysmography (PAPG) data.

29. An apparatus, the apparatus comprising: a photoacoustic system, the photoacoustic system comprising: a piezoelectric receiver; and a light source system; and a control system configured to: receive heart rate waveform data from a heart rate waveform analyzer; initiate a photoacoustic sampling system at a start of a cardiac phase transition window, the cardiac phase transition window indicated by the heart rate waveform data; during the cardiac phase transition window: control the light source system to emit a plurality of light pulses into biological tissue of a subject, the biological tissue including blood and blood vessels located deep within the biological tissue; receive, from the piezoelectric receiver, signals corresponding to acoustic waves emitted from portions of the biological tissue, the acoustic waves corresponding to photoacoustic emissions from the blood and the blood vessels caused by the plurality of light pulses; and obtain plethysmography data based on the signals; and deactivate the photoacoustic sampling system at an end of the cardiac phase transition window.

30. The apparatus of claim 29, wherein the control system is further configured to deactivate the photoacoustic sampling system prior to the end of the cardiac phase transition window in response to determining that the plethysmography data includes at least a threshold number of samples prior to the end of the cardiac phase transition window.

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