Patent ID: 12232869

DETAILED DESCRIPTION

The following detailed description of example implementations refers to the accompanying drawings. The same reference numbers in different drawings may identify the same or similar elements. Some aspects of the following description use a spectrometer as an example. However, the measurement principles, procedures, and methods described herein may be used with any sensor, including but not limited to other optical sensors and spectral sensors.

A sensor device may be used to perform health-related measurements, such as blood pressure measurements, blood oxygen measurements (e.g., peripheral capillary oxygen saturation (SpO2) measurements), glucose measurements, surface measurements (e.g., measurements of skin hydration, skin tone, bilirubin levels, and/or the like) and/or the like. Many blood pressure measurement approaches use contact means, such as wearable devices, measurement instrumentation, and/or the like. This provides blood pressure data at a particular point of contact.

It may be beneficial to perform blood pressure measurements at multiple different points (e.g., different spatial points, different points in time, at different depths in a measurement target, and/or the like). Also, it may be beneficial to combine blood pressure measurements with other types of health-related measurements, such as those described above. However, the determination of blood pressure measurements at multiple points using contact means may require a large, costly, and complicated apparatus that can contact multiple points on the measurement target. This may be infeasible for some types of wearable devices or instrumentation. Furthermore, a wearable device or instrumentation may require other contact measurement devices to perform the other types of health-related measurements.

Implementations described herein provide measurement of a measurement target's blood pressure using a pulse transit time measurement, determined using an image sensor of a sensor device. For example, the pulse transit time may be determined with reference to two or more measurement locations on a measurement target, where the two or more locations are included in an image or video stream captured by the image sensor. This may enable the measurement of blood pressure at many different locations on the measurement target. Furthermore, the usage of the image sensor may enable the determination of other health-related measurements at the locations used to determine the pulse transit time measurement and/or at other locations on the surface or under the surface of the measurement target. Thus, implementations described herein provide for examination of optical changes in a volume of tissue that contains blood flow. By using the image sensor to perform such measurements, size, cost, and complexity are reduced relative to a device that uses contact means to perform such measurements. Furthermore, the spacing between measurement locations may be increased relative to a device using contact means, since the device using contact means may need to be at least as large as the distance between the measurement points. Still further, the implementations described herein can perform pulse transit time and/or other measurements for multiple measurement targets (e.g., persons, regions of a person, and/or the like) at once, which may not be possible for a contact-based measurement device.

FIGS.1A and1Bare diagrams of an overview of an example implementation100described herein. As shown, example implementation100includes an image sensor105and a processor110. The components of image sensor105and processor110are described in more detail in connection withFIGS.2and3. Image sensor105and processor110may be associated with a sensor device, which is described in more detail elsewhere herein. References to a sensor device in the description accompanyingFIGS.1A and1Bmay refer to one or more of image sensor105, processor110, and user device155shown inFIG.1B.

As shown, example implementation100includes a measurement target115. Measurement target115may be tissue (e.g., human tissue, animal tissue, and/or the like). As further shown, measurement target115may include a blood vessel120. The sensor device may perform a pulse transit time measurement based on the blood vessel120, as described below.

As shown by reference number125, image sensor105may collect image data. For example, image sensor105may generate a signal for an image stream, a video stream, and/or the like based on receiving light of one or more wavelengths. In some implementations, image sensor105may be configured to sense multiple different wavelengths (e.g., λ1, λ2, and λ3inFIG.1A), which may enable the determination of different measurements at different measurement locations (e.g., surface measurement locations or sub-surface measurement locations). In some implementations, image sensor105may be configured to sense a single wavelength, which may reduce complexity and cost of image sensor105.

As shown, measurement target115may be associated with two sub-surface measurement locations130. The sensor device may determine a pulse transit time measurement and/or another type of measurement based on the sub-surface measurement locations130(e.g., based on information determined using the light associated with21and22), as described in more detail elsewhere herein. In some implementations, measurement target115may be associated with any number of sub-surface measurement locations130. The usage of a larger number of sub-surface measurement locations130may provide additional pulse transit time measurements, blood pressure measurements, and/or the like, whereas the usage of a smaller number of sub-surface measurement locations130may reduce the complexity and processor usage of the pulse transit time determination. As shown, measurement target115may be associated with a surface measurement location135. The sensor device may perform a health-related measurement based on the light associated with λ3to determine a health parameter, such as a bilirubin content, a temperature, a skin hydration, or another type of health-related parameter. In some implementations, the sensor device may perform the measurements described herein based on a non-contact sensing operation. In a non-contact sensing operation, the sensor device may not be in contact with measurement target115. For example, the sensor device may be any distance from measurement target115. Performing the measurement using the non-contact sensing operation may improve versatility of the sensor device and may enable measurements without contacting measurement target115, which improves safety and efficiency of performing measurements, as described elsewhere herein.

In some implementations, the sensor device may identify the locations130and/or135. For example, the sensor device may identify the locations130and/or135using a computer vision technique and based on information associated with the image captured by image sensor105, (e.g., spatial information, a particular wavelength response in the image captured by image sensor105, and/or the like). In some implementations, the sensor device may identify the locations130and/or135based on which measurement is to be performed. For example, the sensor device may identify the sub-surface measurement locations130for a pulse transit time measurement, a measurement of a health parameter (such as a blood oxygen content measurement (e.g., SpO2) or a heart rate measurement, among other examples), and/or the like, and may identify the surface measurement location135for a skin hydration measurement, a bilirubin measurement, and/or the like.

As shown, the sub-surface measurement locations130may be associated with wavelengths λ1and λ2. In some implementations, λ1and λ2may be the same wavelength. In some implementations, λ1and λ2may be different wavelengths in a same wavelength range. In some implementations, λ1and λ2may be in different wavelength ranges. In some implementations, λ1and/or λ2may be associated with a near-infrared (NIR) range, which may enable taking measurement at sub-surface measurement locations130. In some implementations, λ1and/or λ2may be associated with another wavelength that can penetrate to a corresponding sub-surface measurement location (e.g., sub-surface measurement location130).

As shown, the surface measurement location135may be associated with a wavelength λ3. In some implementations, λ3may be a visible-range wavelength, which may enable color-based measurements and/or the like. Thus, λ3may provide visible-range measurement information regarding the measurement target. In some implementations, λ3may be in a same wavelength range as λ1and/or λ2. In some implementations, λ3may be in a different wavelength range than λ1and/or λ2. Measurements using λ3in a different wavelength range than λ1and/or λ2may increase the diversity of measurements that can be performed using the sensor device, whereas measurements using λ3in a same wavelength range as λ1and/or λ2may reduce complexity of the sensor device.

WhileFIG.1shows the sensor device receiving light at discrete wavelengths with regard to different measurement locations, it should be understood that the sensor device can receive spectral data associated with multiple wavelengths for a given measurement location. For example, the sensor device may receive light in a frequency range (which may include any one or more of λ1λ2, and/or λ3, depending on the material properties of the measurement target and/or the measurement locations) with regard to any one or more of the measurement locations shown inFIG.1Thus, the sensor device may gather spectrally diverse data measurement associated with multiple different frequencies with regard to a given measurement location. Furthermore, the sensor device may gather spatially diverse measurement data with regard to one or more frequencies at a plurality of different measurement locations. Still further, the sensor device may gather temporally diverse measurement data by performing measurements on spatially and/or spectrally diverse measurement data over time.

As shown inFIG.1B, and by reference number140, processor110may determine a pulse transit time using λ1and λ2. For example, processor110may determine the pulse transit time based on measurements at sub-surface measurement locations130. In some implementations, processor110may sample the image data or video stream captured by image sensor105(e.g., multiple times per second and/or the like), may identify a pulse at a first sub-surface measurement location130, and may identify the pulse at the second sub-surface measurement location130. Based on a time difference (e.g., a number of samples) between identifying the pulse at the first sub-surface measurement location130and at the second sub-surface measurement location130, processor110may determine the pulse transit time. In some implementations, processor110may determine a blood pressure value based on the pulse transit time. For example, processor110may determine the blood pressure value based on a relationship between pulse transit time and blood pressure.

As shown by reference number145, processor110may determine another measurement using the light associated with λ3(e.g., at the surface measurement location135). In some implementations, processor110may determine the other measurement contemporaneously with determining the pulse transit time measurement. This may enable the determination of temporally correlated health-related measurements, which may provide therapeutic benefits, accuracy benefits, and/or the like. Temporally correlated health-related measurements may be difficult to capture using two or more different sensor devices that are each configured to perform a respective health-related measurement, due to different delays associated with the two or more different sensor devices, difficulty in coordinating operations of the two or more sensor devices, and/or the like. In example implementation100, the other measurement is a bilirubin measurement (e.g., based on a color associated with the surface measurement location135, such as a skin color), though the other measurement may include any health-related measurement that can be captured via imaging.

In some implementations, processor110may determine a plurality of pulse transit time values based on image data. For example, processor110may obtain additional image data regarding one or more other measurement locations, and may determine the plurality of pulse transit time values based on the additional image data. For example, the plurality of pulse transit time values may relate to different regions of the measurement target115, different blood vessels120, and/or the like. This may also enable differential measurement of pulse transit times, thereby enabling the detection of discrepancies in pulse transit time, blood pressure, and/or the like at different locations on a measurement target. The determination of pulse transit time values based on image data may also enable the measurement of pulse transit time for multiple, different measurement targets (e.g., multiple, different people) using a single image sensor, since the multiple different measurement targets can be captured in a single image, thereby conserving resources associated with implementing multiple different sensor devices.

As shown by reference number150, the processor110may provide information identifying the measurements determined in connection with reference numbers140and145to a user device155. In some implementations, user device155may be the sensor device. For example, processor110and image sensor105may be components of user device155. In some implementations, user device155may be separate from the sensor device.

As shown by reference number160, user device155may provide a visual interface for the health-related measurements determined by the sensor device. Here, the visual interface is shown as a health interface. As shown by reference number165, the visual interface indicates a blood pressure measurement determined based on the pulse transit time. Furthermore, the visual interface indicates the sub-surface measurement locations used to determine the pulse transit time (e.g., sub-surface measurement locations130, shown inFIG.1A). As shown by reference number170, the visual interface indicates that a bilirubin measurement may be abnormal (e.g., based on a color of the measurement target115at the surface measurement location135ofFIG.1A). Furthermore, the visual interface indicates the surface measurement location used to determine the bilirubin measurement (e.g., surface measurement location135, shown inFIG.1A).

In some implementations, user device155may update the visual interface. For example, user device155may update a blood pressure measurement based on images captured over time, may provide additional measurements determined based on images captured by the sensor device, and/or the like. In some implementations, user device155may provide information based on an interaction with the visual interface. For example, user device155may provide additional detail regarding the blood pressure measurement (e.g., the pulse transit time, a heart rate associated with the pulse transit time, additional pulse transit times and/or blood pressures for different measurement locations of the measurement target115, and/or the like) based on receiving an interaction (e.g., a user interaction and/or the like) with the visual representation of the blood pressure measurement. As another example, user device155may modify a measurement location based on an interaction (e.g., an interaction to move the visual representation of the measurement location, an interaction to specify a new location for the measurement location, and/or the like). As yet another example, user device155or processor110may perform a measurement based on an interaction. For example, the interaction may select the measurement to be performed (e.g., from a menu of available measurements) or may specify a location for the measurement. User device155and/or processor110may perform the measurement at the location, and may provide information indicating a result of the measurement.

In some implementations, processor110may perform a measurement based on a result of another measurement. For example, processor110may determine that a blood pressure measurement or a heart rate measurement satisfies a threshold, and may perform another measurement (e.g., a blood oxygen measurement, a body temperature measurement, a skin hydration measurement, and/or the like) based on the blood pressure measurement or the heart rate measurement satisfying the threshold. In some implementations, processor110may perform the measurement without user interaction (e.g., automatically), thereby conserving processor resources that would otherwise be used in association with manual triggering of the measurement. In some implementations, processor110may provide information identifying the measurement (e.g., via the visual interface, as a notification or alert, and/or the like). In some implementations, processor110may trigger an action to be performed based on the measurement (e.g., dispatching a nurse, administering a medication, providing a notification for a user to perform an activity, and/or the like).

In some implementations, processor110or user device155may determine a blood pressure based on a pulse transit time. For example, processor110or user device155may determine the blood pressure based on an estimated pressure difference between the measurement locations130based on a pulse wave velocity (e.g., by dividing the distance traveled between the measurement locations130by the pulse transit time). In some implementations, processor110or user device155may determine the blood pressure based on the pulse transit time using a different technique than the one described above.

In this way, pulse transit time measurement using an image sensor105is performed. Furthermore, additional measurements using the image sensor105may be determined in association with (e.g., contemporaneously with) the pulse transit time measurement, thereby enabling temporal correlation of such measurements. Thus, complexity of sensor devices is reduced and flexibility of measurements is improved. Furthermore, the pulse transit time may be performed for any two or more measurement locations at any suitable spacing from each other, thereby improving the usefulness of the pulse transit time data and reducing the mechanical complexity of the sensor device in comparison to a sensor device with contact means for determining the pulse transit time at an adjustable spacing.

In some implementations, image sensor105and/or processor110may be included in a sensor device such as sensor device210, described in connection withFIG.2, below. Sensor device210may be capable of sampling spectra across multiple points in a scene and providing an image in which features and locations can be identified to provide multiple points for spectral comparison. Thus, the sensor device can perform a pulse transit time-based blood pressure measurement and/or one or more other measurements described herein. Furthermore, sensor device210may provide more flexibility than a device employing sensors at different points in space. For example, sensor device210may be capable of performing measurements for multiple users, including users not wearing sensor device210, and in a non-contact fashion. Furthermore, sensor device210may be more resilient to suboptimal sensor placement than devices employing respective sensors at different points in space. For example, sensor device210may be capable of capturing an image associated with a field of view (FOV) and may analyze multiple subjects within the FOV, which may be particularly beneficial in a healthcare environment such as a care home, where sensor device210may be capable of recognizing and monitoring an individual's health emergency instantaneously while they move within common use spaces. Furthermore, in some implementations, sensor device210may perform the operations described herein in a non-contact fashion (e.g., without contacting a measurement target of sensor device210) and may provide spectral data at multiple points (e.g., every point, a plurality of points) in a scene within the sensor device210's FOV.

As indicated above,FIGS.1A and1Bare provided merely as one or more examples. Other examples may differ from what is described with regard toFIGS.1A and1B.

FIG.2is a diagram of an example environment200in which systems and/or methods described herein may be implemented. As shown inFIG.2, environment200may include a user device240, a network250, and a sensor device210that may include a processor220and an image sensor230. Devices of environment200may interconnect via wired connections, wireless connections, or a combination of wired and wireless connections.

Sensor device210may include an optical device capable of storing, processing, and/or routing information associated with sensor determination and/or one or more devices capable of performing a sensor measurement on an object. For example, sensor device210may include a spectrometer device that performs spectroscopy, such as a spectral sensor device (e.g., a binary multispectral sensor device that performs vibrational spectroscopy, such as a near infrared (NIR) spectrometer, a mid-infrared spectroscopy (mid-IR), Raman spectroscopy, and/or the like). For example, sensor device210may perform a health parameter monitoring determination, a pulse transit time determination, a biometric authentication determination, a liveness detection determination, and/or the like. In this case, sensor device210may utilize the same wavelengths, different wavelengths, a combination of the same wavelengths and different wavelengths, and/or the like for such determinations. In some implementations, sensor device210may be incorporated into user device240, such as a wearable spectrometer and/or the like. In some implementations, sensor device210may receive information from and/or transmit information to another device in environment200, such as user device240.

In some implementations, sensor device210may comprise a spectral imaging camera. A spectral imaging camera is a device that can capture an image of a scene. A spectral imaging camera (or a processor220associated with the spectral imaging camera) may be capable of determining spectral content or changes in spectral content at different points in an image of a scene, such as any point in an image of a scene.

In some implementations, sensor device210may comprise a spectral imaging camera capable of performing hyperspectral imaging. For example, sensor device210may include a spectral filter array (e.g., a tiled spectral filter array). In some implementations, the spectral filter array may be placed on image sensor230. In some implementations, sensor device210may comprise a diffuser. For example, the diffuser may be configured to diffuse light en route to image sensor230. Each point in an image captured by sensor device210may map to a unique pseudorandom pattern on the spectral filter array, which encodes multiplexed spatio-spectral information. Thus, a hyperspectral volume with sub-super-pixel resolution can be recovered by solving a sparsity-constrained inverse problem. Sensor device210can include contiguous spectral filters or non-contiguous spectral filters, which may be chosen for a given application. The usage of the diffuser and the computation approach for determining the hyperspectral volume with sub-super-pixel resolution may improve sampling of spectral content, which enables imaging using a spectral filter such as a hyperspectral filter array. Thus, fabrication of sensor device210is simplified in relation to fabrication of a filter on the order of dimension of each pixel. In some implementations, sensor device210may comprise a lens.

Sensor device210may include a processor220. Processor220is described in more detail in connection withFIG.3.

Sensor device210may include an image sensor230. Image sensor230includes a device capable of sensing light. For example, image sensor230may include an image sensor, a multispectral sensor, a spectral sensor, and/or the like. In some implementations, image sensor230may include a charge-coupled device (CCD) sensor, a complementary metal-oxide semiconductor (CMOS) sensor, and/or the like. In some implementations, image sensor230may include a front-side illumination (FSI) sensor, a back-side illumination (BSI) sensor, and/or the like. In some implementations, image sensor230may be included in a camera of sensor device210and/or user device240.

User device240includes one or more devices capable of receiving, generating, storing, processing, and/or providing information associated with a sensor determination. For example, user device240may include a communication and/or computing device, such as a mobile phone (e.g., a smart phone, a radiotelephone, and/or the like), a computer (e.g., a laptop computer, a tablet computer, a handheld computer, and/or the like), a gaming device, a wearable communication device (e.g., a smart wristwatch, a pair of smart eyeglasses, and/or the like), or a similar type of device. In some implementations, user device240may receive information from and/or transmit information to another device in environment200, such as sensor device210.

Network250includes one or more wired and/or wireless networks. For example, network250may include a cellular network (e.g., a long-term evolution (LTE) network, a code division multiple access (CDMA) network, a 3G network, a 4G network, a 5G network, another type of next generation network, and/or the like), a public land mobile network (PLMN), a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a telephone network (e.g., the Public Switched Telephone Network (PSTN)), a private network, an ad hoc network, an intranet, the Internet, a fiber optic-based network, a cloud computing network, or the like, and/or a combination of these or other types of networks.

The number and arrangement of devices and networks shown inFIG.2are provided as an example. In practice, there may be additional devices and/or networks, fewer devices and/or networks, different devices and/or networks, or differently arranged devices and/or networks than those shown inFIG.2. Furthermore, two or more devices shown inFIG.2may be implemented within a single device, or a single device shown inFIG.2may be implemented as multiple, distributed devices. For example, although sensor device210and user device240are described as separate devices, sensor device210and user device240may be implemented as a single device. Additionally, or alternatively, a set of devices (e.g., one or more devices) of environment200may perform one or more functions described as being performed by another set of devices of environment200.

FIG.3is a diagram of example components of a device300. Device300may correspond to sensor device210and user device240. In some implementations, sensor device210and/or user device240may include one or more devices300and/or one or more components of device300. As shown inFIG.3, device300may include a bus310, a processor320, a memory330, a storage component340, an input component350, an output component360, and a communication interface370.

Bus310includes a component that permits communication among multiple components of device300. Processor320is implemented in hardware, firmware, and/or a combination of hardware and software. Processor320is a central processing unit (CPU), a graphics processing unit (GPU), an accelerated processing unit (APU), a microprocessor, a microcontroller, a digital signal processor (DSP), a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), or another type of processing component. In some implementations, processor320includes one or more processors capable of being programmed to perform a function. Memory330includes a random access memory (RAM), a read only memory (ROM), and/or another type of dynamic or static storage device (e.g., a flash memory, a magnetic memory, and/or an optical memory) that stores information and/or instructions for use by processor320.

Storage component340stores information and/or software related to the operation and use of device300. For example, storage component340may include a hard disk (e.g., a magnetic disk, an optical disk, and/or a magneto-optic disk), a solid state drive (SSD), a compact disc (CD), a digital versatile disc (DVD), a floppy disk, a cartridge, a magnetic tape, and/or another type of non-transitory computer-readable medium, along with a corresponding drive.

Input component350includes a component that permits device300to receive information, such as via user input (e.g., a touch screen display, a keyboard, a keypad, a mouse, a button, a switch, and/or a microphone). Additionally, or alternatively, input component350may include a component for determining location (e.g., a global positioning system (GPS) component) and/or a sensor (e.g., an accelerometer, a gyroscope, an actuator, another type of positional or environmental sensor, and/or the like). Output component360includes a component that provides output information from device300(via, e.g., a display, a speaker, a haptic feedback component, an audio or visual indicator, and/or the like).

Communication interface370includes a transceiver-like component (e.g., a transceiver, a separate receiver, a separate transmitter, and/or the like) that enables device300to communicate with other devices, such as via a wired connection, a wireless connection, or a combination of wired and wireless connections. Communication interface370may permit device300to receive information from another device and/or provide information to another device. For example, communication interface370may include an Ethernet interface, an optical interface, a coaxial interface, an infrared interface, a radio frequency (RF) interface, a universal serial bus (USB) interface, a Wi-Fi interface, a cellular network interface, and/or the like.

Device300may perform one or more processes described herein. Device300may perform these processes based on processor320executing software instructions stored by a non-transitory computer-readable medium, such as memory330and/or storage component340. As used herein, the term “computer-readable medium” refers to a non-transitory memory device. A memory device includes memory space within a single physical storage device or memory space spread across multiple physical storage devices.

Software instructions may be read into memory330and/or storage component340from another computer-readable medium or from another device via communication interface370. When executed, software instructions stored in memory330and/or storage component340may cause processor320to perform one or more processes described herein. Additionally, or alternatively, hardware circuitry may be used in place of or in combination with software instructions to perform one or more processes described herein. Thus, implementations described herein are not limited to any specific combination of hardware circuitry and software.

The number and arrangement of components shown inFIG.3are provided as an example. In practice, device300may include additional components, fewer components, different components, or differently arranged components than those shown inFIG.3. Additionally, or alternatively, a set of components (e.g., one or more components) of device300may perform one or more functions described as being performed by another set of components of device300.

FIG.4is a flow chart of an example process400for pulse transit time determination using an image sensor. In some implementations, one or more process blocks ofFIG.4may be performed by a sensor device (e.g., sensor device210, the sensor device described in connection withFIG.1, and/or the like). In some implementations, one or more process blocks ofFIG.4may be performed by another device or a group of devices separate from or including the sensor device, such as a user device (e.g., user device155, user device240, and/or the like) and/or the like.

As shown inFIG.4, process400may include obtaining first image data regarding a first measurement location of a measurement target (block410). For example, the sensor device (e.g., using processor320, memory330, communication interface370, and/or the like) may obtain first image data regarding a first measurement location of a measurement target, as described above.

As further shown inFIG.4, process400may include obtaining second image data regarding a second measurement location of the measurement target, wherein the first measurement location and the second measurement location are sub-surface measurement locations within the measurement target (block420). For example, the sensor device (e.g., using processor320, memory330, communication interface370, and/or the like) may obtain second image data regarding a second measurement location of the measurement target, as described above. In some implementations, the first measurement location and the second measurement location are sub-surface measurement locations within the measurement target.

As further shown inFIG.4, process400may include determining, based on the first image data and the second image data, a pulse transit time measurement (block430). For example, the sensor device (e.g., using processor320, memory330, communication interface370and/or the like) may determine, based on the first image data and the second image data, a pulse transit time measurement, as described above.

As further shown inFIG.4, process400may include providing information identifying the pulse transit time measurement (block440). For example, the sensor device (e.g., using processor320, memory330, communication interface370, and/or the like) may provide information identifying the pulse transit time measurement, as described above.

Process400may include additional implementations, such as any single implementation or any combination of implementations described below and/or in connection with one or more other processes described elsewhere herein.

In a first implementation, the sensor comprises an image sensor of a camera of the sensor device.

In a second implementation, alone or in combination with the first implementation, process400includes determining a blood pressure value using the pulse transit time measurement.

In a third implementation, alone or in combination with one or more of the first and second implementations, the image data includes multispectral image data.

In a fourth implementation, alone or in combination with one or more of the first through third implementations, process400includes determining an other measurement, other than the pulse transit time measurement, using the image data.

In a fifth implementation, alone or in combination with one or more of the first through fourth implementations, the other measurement is performed using visible-range information.

In a sixth implementation, alone or in combination with one or more of the first through fifth implementations, the other measurement relates to a skin color of the measurement target.

In a seventh implementation, alone or in combination with one or more of the first through sixth implementations, the other measurement comprises a health parameter.

In an eighth implementation, alone or in combination with one or more of the first through seventh implementations, the health parameter comprises at least one of a heart rate measurement, or an SpO2 measurement.

In a ninth implementation, alone or in combination with one or more of the first through eighth implementations, the first image data and the second image data are associated with a wavelength that penetrates the measurement target to the first measurement location and the second measurement location, respectively.

AlthoughFIG.4shows example blocks of process400, in some implementations, process400may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted inFIG.4. Additionally, or alternatively, two or more of the blocks of process400may be performed in parallel.

FIG.5is a flow chart of an example process500for pulse transit time determination using an image sensor. In some implementations, one or more process blocks ofFIG.5may be performed by a sensor device (e.g., sensor device210, the sensor device described in connection withFIG.1, and/or the like). In some implementations, one or more process blocks ofFIG.5may be performed by another device or a group of devices separate from or including the sensor device, such as a user device (e.g., user device155, user device240, and/or the like) and/or the like.

As shown inFIG.5, process500may include collecting image data using the sensor (block510). For example, the sensor device (e.g., using processor320, memory330, communication interface370, and/or the like) may collect image data using the sensor, as described above.

As further shown inFIG.5, process500may include obtaining, from the image data, first image data regarding a first measurement location of a measurement target (block520). For example, the sensor device (e.g., using processor320, memory330, communication interface370, and/or the like) may obtain, from the image data, first image data regarding a first measurement location of a measurement target, as described above.

As further shown inFIG.5, process500may include obtaining, from the image data, second image data regarding a second measurement location of the measurement target, wherein the first measurement location and the second measurement location are sub-surface measurement locations within the measurement target (block530). For example, the sensor device (e.g., using processor320, memory330, communication interface370, and/or the like) may obtain, from the image data, second image data regarding a second measurement location of the measurement target, as described above. In some implementations, the first measurement location and the second measurement location are sub-surface measurement locations within the measurement target.

As further shown inFIG.5, process500may include determining, based on the first image data and the second image data, a pulse transit time measurement (block540). For example, the sensor device (e.g., using processor320, memory330, communication interface370, and/or the like) may determine, based on the first image data and the second image data, a pulse transit time measurement, as described above.

As further shown inFIG.5, process500may include providing information identifying the pulse transit time measurement (block550). For example, the sensor device (e.g., using processor320, memory330, communication interface370, and/or the like) may provide information identifying the pulse transit time measurement, as described above.

Process500may include additional implementations, such as any single implementation or any combination of implementations described below and/or in connection with one or more other processes described elsewhere herein.

In a first implementation, the first image data and the second image data are based on light generated by the sensor device.

In a second implementation, alone or in combination with the first implementation, the first image data and the second image data are associated with a near-infrared spectral range.

In a third implementation, alone or in combination with one or more of the first and second implementations, process500includes obtaining additional image data regarding one or more other measurement locations, and determining one or more other pulse transit time values based on the additional image data.

In a fourth implementation, alone or in combination with one or more of the first through third implementations, an input of the sensor is filtered by the filter based on a binary multispectral technique.

In a fifth implementation, alone or in combination with one or more of the first through fourth implementations, the first image data is associated with a first wavelength that is passed to the sensor and the second image data is associated with a second wavelength that is passed to the sensor.

AlthoughFIG.5shows example blocks of process500, in some implementations, process500may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted inFIG.5. Additionally, or alternatively, two or more of the blocks of process500may be performed in parallel.

FIG.6is a flow chart of an example process600for pulse transit time determination using an image sensor. In some implementations, one or more process blocks ofFIG.6may be performed by a sensor device (e.g., sensor device210, the sensor device described in connection withFIG.1, and/or the like). In some implementations, one or more process blocks ofFIG.6may be performed by another device or a group of devices separate from or including the sensor device, such as a user device (e.g., user device155, user device240, and/or the like) and/or the like.

As shown inFIG.6, process600may include obtaining first image data regarding a first measurement location of a measurement target and second image data regarding a second measurement location of the measurement target, wherein the first measurement location and the second measurement location are sub-surface measurement locations within the measurement target, and wherein the first image data and the second image data are obtained from a video stream (block610). For example, the sensor device (e.g., using processor320, memory330, communication interface370, and/or the like) may obtain first image data regarding a first measurement location of a measurement target and second image data regarding a second measurement location of the measurement target, as described above. In some implementations, the first measurement location and the second measurement location are sub-surface measurement locations within the measurement target. In some implementations, the first image data and the second image data are obtained from a video stream.

As further shown inFIG.6, process600may include determining, based on the first image data and the second image data, a pulse transit time measurement (block620). For example, the sensor device (e.g., using processor320, memory330, communication interface370, and/or the like) may determine, based on the first image data and the second image data, a pulse transit time measurement, as described above.

As further shown inFIG.6, process600may include providing information identifying the pulse transit time measurement (block630). For example, the sensor device (e.g., using processor320, memory330, communication interface370, and/or the like) may provide information identifying the pulse transit time measurement, as described above.

Process600may include additional implementations, such as any single implementation or any combination of implementations described below and/or in connection with one or more other processes described elsewhere herein.

In a first implementation, the sensor device comprises a smartphone.

In a second implementation, alone or in combination with the first implementation, process600includes providing a visual representation of the video stream with information identifying the pulse transit time or information determined based on the pulse transit time.

In a third implementation, alone or in combination with one or more of the first and second implementations, process600includes determining another measurement, other than the pulse transit time measurement, using the video stream.

AlthoughFIG.6shows example blocks of process600, in some implementations, process600may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted inFIG.6. Additionally, or alternatively, two or more of the blocks of process600may be performed in parallel.

The foregoing disclosure provides illustration and description, but is not intended to be exhaustive or to limit the implementations to the precise forms disclosed. Modifications and variations may be made in light of the above disclosure or may be acquired from practice of the implementations.

As used herein, the term “component” is intended to be broadly construed as hardware, firmware, and/or a combination of hardware and software.

As used herein, satisfying a threshold may, depending on the context, refer to a value being greater than the threshold, more than the threshold, higher than the threshold, greater than or equal to the threshold, less than the threshold, fewer than the threshold, lower than the threshold, less than or equal to the threshold, equal to the threshold, or the like.

Certain user interfaces have been described herein and/or shown in the figures. A user interface may include a graphical user interface, a non-graphical user interface, a text-based user interface, and/or the like. A user interface may provide information for display. In some implementations, a user may interact with the information, such as by providing input via an input component of a device that provides the user interface for display. In some implementations, a user interface may be configurable by a device and/or a user (e.g., a user may change the size of the user interface, information provided via the user interface, a position of information provided via the user interface, etc.). Additionally, or alternatively, a user interface may be pre-configured to a standard configuration, a specific configuration based on a type of device on which the user interface is displayed, and/or a set of configurations based on capabilities and/or specifications associated with a device on which the user interface is displayed.

It will be apparent that systems and/or methods described herein may be implemented in different forms of hardware, firmware, or a combination of hardware and software. The actual specialized control hardware or software code used to implement these systems and/or methods is not limiting of the implementations. Thus, the operation and behavior of the systems and/or methods are described herein without reference to specific software code—it being understood that software and hardware can be designed to implement the systems and/or methods based on the description herein.

Even though particular combinations of features are recited in the claims and/or disclosed in the specification, these combinations are not intended to limit the disclosure of various implementations. In fact, many of these features may be combined in ways not specifically recited in the claims and/or disclosed in the specification. Although each dependent claim listed below may directly depend on only one claim, the disclosure of various implementations includes each dependent claim in combination with every other claim in the claim set.

No element, act, or instruction used herein should be construed as critical or essential unless explicitly described as such. Also, as used herein, the articles “a” and “an” are intended to include one or more items, and may be used interchangeably with “one or more.” Further, as used herein, the article “the” is intended to include one or more items referenced in connection with the article “the” and may be used interchangeably with “the one or more.” Furthermore, as used herein, the term “set” is intended to include one or more items (e.g., related items, unrelated items, a combination of related and unrelated items, etc.), and may be used interchangeably with “one or more.” Where only one item is intended, the phrase “only one” or similar language is used. Also, as used herein, the terms “has,” “have,” “having,” or the like are intended to be open-ended terms. Further, the phrase “based on” is intended to mean “based, at least in part, on” unless explicitly stated otherwise. Also, as used herein, the term “or” is intended to be inclusive when used in a series and may be used interchangeably with “and/or,” unless explicitly stated otherwise (e.g., if used in combination with “either” or “only one of”).