Sensor device

Abstract

To measure the blood pressure of a measurement target using pulse transit time measurement determined using an image sensor of a sensor device.SOLUTION: From image data collected by an image sensor 105 of a sensor device 100, the sensor device may obtain, first image data regarding a first sub-surface measurement location 130 of a measurement target 115, and second image data regarding a second sub-surface measurement location of the measurement target. The sensor device determines, based on the first image data and the second image data, a pulse transit time measurement, and determines a blood pressure value based on the pulse transit time.SELECTED DRAWING: Figure 1A

Description

Cross - reference to related applications

[0001] This patent application was filed on October 18, 2019, and claims priority to U.S. Provisional Patent Application No. 62 / 923,247 entitled "SENSOR DEVICE" and U.S. Non - Provisional Patent Application No. 16 / 949,156 entitled "SENSOR DEVICE" filed on October 15, 2020, which are hereby expressly incorporated by reference herein.

Background Art

[0002] Sensor devices can perform measurements for various purposes. For example, a sensor device may determine a measurement based on an interaction with a target. An example of such a target is the human body, and for this purpose, the sensor device may perform health - related measurements.

Summary of the Invention

[0003] According to some embodiments, a method according to the present invention comprises: obtaining, by a sensor device, first image data regarding a first measurement position of a measurement target from image data collected by a sensor of the sensor device; obtaining, by the sensor device, second image data regarding a second measurement position of the measurement target from the image data, wherein the first measurement position and the second measurement position are subsurface measurement positions within the measurement target; determining, by the sensor device, a pulse transit time measurement value based on the first image data and the second image data; and providing, by the sensor device, information for identifying the pulse transit time measurement value. ​

[0004] According to some embodiments, the sensor device according to the present invention includes a sensor and one or more processors operably coupled to the sensor, and the processor uses the sensor to collect image data, and from the image data, obtain first image data regarding a first measurement position of the measurement target, obtain second image data regarding a second measurement position of the measurement target from the image data, where the first measurement position and the second measurement position are sub-surface measurement positions within the measurement target, and based on the first image data and the second image data, determine a pulse transit time measurement and be configured to provide information for identifying the pulse transit time measurement. According to some embodiments, the non-transitory computer-readable medium according to the present invention can store one or more instructions. When the one or more instructions are executed by the one or more processors of the sensor device, the one or more processors are caused to obtain first image data regarding a first measurement position of the measurement target and second image data regarding a second measurement position of the measurement target, where the first measurement position and the second measurement position are sub-surface measurement positions within the measurement target, the first image data and the second image data are obtained from a video stream, based on the first image data and the second image data, determine a pulse transit time measurement value, and cause the sensor device to provide information for identifying the pulse transit time measurement value.

[0005] BRIEF DESCRIPTION OF THE DRAWINGS

[0006] ​​​​​​​​​​​​​​​

Figure 1A

Figure 1B

Figure 2

Figure 3

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Figure 6

DETAILED DESCRIPTION OF THE INVENTION

[0007] The following detailed description of the embodiments refers to the accompanying drawings. The same reference numerals in different drawings may identify the same or similar elements. Some aspects of the following description are by way of example using a spectrometer. However, the measurement principles, procedures, and methods described in this specification can be used with any sensor, including but not limited to other optical sensors and spectral sensors.

[0008] The sensor device can be used to perform health-related measurements such as blood pressure measurement, blood oxygen measurement (e.g., measurement of peripheral capillary oxygen saturation (SpO2)), glucose measurement, and / or surface measurement (e.g., measurement of skin hydration, skin color tone , and / or measurement of bilirubin level, etc.). Many blood pressure measurement approaches involve wearable devices and / or measuring instruments, etc. Contact means are used. Thereby, blood pressure data at specific contact points is provided.

[0009] It may be beneficial to perform blood pressure measurements at multiple different points (e.g., different spatial points, different points in time, and / or different depths in the measurement target, etc.). Also, it may be beneficial to combine blood pressure measurements with other types of health-related measurements as described above. However, determining blood pressure measurement values at multiple points using contact means requires a large, costly, and complex device that can contact multiple points on the measurement target, which may not be feasible for certain types of wearable devices or gauges. Furthermore, wearable devices or gauges may require other contact-type measurement devices to perform other types of health-related measurements. However, determining blood pressure measurement values at multiple points using contact means requires a large, costly, and complex device that can contact multiple points on the measurement target, which may not be feasible for certain types of wearable devices or gauges. Furthermore, wearable devices or gauges may require other contact-type measurement devices to perform other types of health-related measurements. This may not be possible for certain types of wearable devices or gauges. Furthermore, wearable devices or gauges may require other contact-type measurement devices to perform other types of health-related measurements. This may not be possible for certain types of wearable devices or gauges. Furthermore, wearable devices or gauges may require other contact-type measurement devices to perform other types of health-related measurements. This may not be possible for certain types of wearable devices or gauges. Furthermore, wearable devices or gauges may require other contact-type measurement devices to perform other types of health-related measurements.

[0010] The embodiments described herein provide for measuring the blood pressure of a measurement target using pulse transit time measurements 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 positions on the measurement target, and the two or more positions may be included in an image or video stream acquired by the image sensor. Thereby, it may be possible to measure blood pressure at many different positions on the measurement target. and the two or more positions may be included in an image or video stream acquired by the image sensor. Thereby, it may be possible to measure blood pressure at many different positions on the measurement target. and the two or more positions may be included in an image or video stream acquired by the image sensor. Thereby, it may be possible to measure blood pressure at many different positions on the measurement target. Furthermore, the use of the image sensor enables determination of other health-related measurement values at positions used to determine pulse transit time measurements and / or at other positions on or under the surface of the measurement target. Thus, the embodiments described herein Furthermore, the use of the image sensor enables determination of other health-related measurement values at positions used to determine pulse transit time measurements and / or at other positions on or under the surface of the measurement target. Thus, the embodiments described herein Furthermore, the use of the image sensor enables determination of other health-related measurement values at positions used to determine pulse transit time measurements and / or at other positions on or under the surface of the measurement target. Thus, the embodiments described herein provide for examination of optical changes in the volume of tissue containing blood flow. Using the image sensor, By performing such measurements using it, the size, cost, and complexity are reduced compared to a device that performs such measurements using contact means Furthermore, the contact means The device using needs to be at least as large as the distance between the measurement points Therefore, the interval between the measurement points can be increased compared to the device using the contact means And further, the embodiments described herein can perform pulse propagation time and / or other measurements on a plurality of measurement targets (e.g., such as a person and / or a person's area, etc.) at once, which may not be possible with a contact-type measurement device

[0011] Figures 1A and 1B are diagrams showing an overview of an exemplary sensor device 100 described herein As shown, the exemplary sensor device 100 includes an image sensor 105 and a processor 110. The components of the image sensor 105 and the processor 110 will be described in more detail in connection with FIGS. 2 and 3. The image sensor 105 and the processor 110 may be associated with a sensor device described in more detail elsewhere herein References to the sensor device in the descriptions accompanying FIGS. 1A and 1B may refer to one or more of the image sensor 105, the processor 110, and the user device 15 5 shown in FIG. 1B

[0012] As shown, the exemplary sensor device 100 includes a measurement target 115 The measurement target 115 may be tissue (e.g., human tissue and / or animal tissue, etc.) Furthermore, as shown, the measurement target 115 may include a blood vessel 120. The sensor ​The device may perform pulse transit time measurement based on the blood vessel 120 as described below. It may be.

[0013] As shown by reference numeral 125, the image sensor 105 may collect image data. For example, the image sensor 105 may generate signals for an image stream, and / or a video stream, etc. based on receiving light of one or more wavelengths. In some embodiments, the image sensor 105 may be configured to sense a plurality of different wavelengths (e.g., λ1, λ2, and λ3 in FIG. 1A), thereby enabling different measurements at different measurement positions (e.g., surface measurement positions or subsurface measurement positions). In some embodiments, the image sensor 105 may be configured to sense a single wavelength, which may reduce the complexity and cost of the image sensor 105. As shown in the figure, the measurement target 115 may be associated with two subsurface measurement positions 130. The sensor device may determine pulse transit time measurement and / or another type of measurement based on the subsurface measurement position 130 (e.g., based on information determined using light associated with λ1 and λ2), as described in more detail elsewhere in this specification. In some embodiments, the measurement target 115 may be associated with any number of subsurface measurement positions 130. The use of more subsurface measurement positions 130 can provide additional pulse transit time measurements, and / or blood pressure measurements, etc., while the use of a smaller number of subsurface measurement positions 130 can reduce the complexity and processor usage of pulse transit time determination. In some embodiments, the image sensor 105 may be configured to sense a single wavelength, which may reduce the complexity and cost of the image sensor 105. This can reduce the complexity and cost of the image sensor 105.

[0014] As shown in the illustration, the measurement target 115 may be associated with two subsurface measurement positions 130. The sensor device may, as described in more detail elsewhere in this specification, Based on the subsurface measurement position 130 (e.g., based on information determined using light associated with λ1 and λ2) Determine pulse transit time measurement and / or another type of measurement. In some embodiments, the measurement target 115 may be associated with any number of subsurface measurement positions 1 30. The use of more subsurface measurement positions 130 can provide additional Pulse transit time measurement, and / or blood pressure measurement, etc., and the use of a smaller number of surface Lower measurement positions 130 can reduce the complexity and processor usage of pulse transit time determination It can be done. As shown, the measurement target 115 may be associated with the surface measurement position 135. The sensor device may be associated with λ3 to perform health-related measurements based on the light associated with λ3 to determine bilirubin content, body temperature, skin hydration, or other types of health-related parameters. It can be done. As shown, the measurement target 115 may be associated with the surface measurement position 135. In some embodiments, the sensor device may perform the measurements described herein based on non-contact sensing operations. In non-contact sensing operations, the sensor device may not be in contact with the measurement target 115. For example, the sensor device may be at any distance from the measurement target 115. Performing measurements using non-contact sensing operations can improve the versatility of the sensor device, enable measurements without contacting the measurement target 115, and may improve the safety and efficiency of performing measurements, as described elsewhere herein. In some embodiments, the sensor device may perform the measurements described herein based on non-contact sensing operations. In non-contact sensing operations, the sensor device may not be in contact with the measurement target 115. For example, the sensor device may be at any distance from the measurement target 115. Performing measurements using non-contact sensing operations can improve the versatility of the sensor device, enable measurements without contacting the measurement target 115, and may improve the safety and efficiency of performing measurements, as described elsewhere herein. In some embodiments, the sensor device may perform the measurements described herein based on non-contact sensing operations. In non-contact sensing operations, the sensor device may not be in contact with the measurement target 115. For example, the sensor device may be at any distance from the measurement target 115. Performing measurements using non-contact sensing operations can improve the versatility of the sensor device, enable measurements without contacting the measurement target 115, and may improve the safety and efficiency of performing measurements, as described elsewhere herein. In some embodiments, the sensor device may perform the measurements described herein based on non-contact sensing operations. In non-contact sensing operations, the sensor device may not be in contact with the measurement target 115. For example, the sensor device may be at any distance from the measurement target 115. Performing measurements using non-contact sensing operations can improve the versatility of the sensor device, enable measurements without contacting the measurement target 115, and may improve the safety and efficiency of performing measurements, as described elsewhere herein. In some embodiments, the sensor device may perform the measurements described herein based on non-contact sensing operations. In non-contact sensing operations, the sensor device may not be in contact with the measurement target 115. For example, the sensor device may be at any distance from the measurement target 115. Performing measurements using non-contact sensing operations can improve the versatility of the sensor device, enable measurements without contacting the measurement target 115, and may improve the safety and efficiency of performing measurements, as described elsewhere herein. In some embodiments, the sensor device may perform the measurements described herein based on non-contact sensing operations. In non-contact sensing operations, the sensor device may not be in contact with the measurement target 115. For example, the sensor device may be at any distance from the measurement target 115. Performing measurements using non-contact sensing operations can improve the versatility of the sensor device, enable measurements without contacting the measurement target 115, and may improve the safety and efficiency of performing measurements, as described elsewhere herein. In some embodiments, the sensor device may perform the measurements described herein based on non-contact sensing operations. In non-contact sensing operations, the sensor device may not be in contact with the measurement target 115. For example, the sensor device may be at any distance from the measurement target 115. Performing measurements using non-contact sensing operations can improve the versatility of the sensor device, enable measurements without contacting the measurement target 115, and may improve the safety and efficiency of performing measurements, as described elsewhere herein.

[0015] In some embodiments, the sensor device may identify the positions 130 and / or 135. For example, the sensor device may use computer vision technology to identify the positions 130 and / or 135 based on information related to the image captured by the image sensor 105 (e.g., spatial information and / or specific wavelength responses in the image captured by the image sensor 105). In some embodiments, the sensor device may identify the positions 130 and / or 135 based on which measurements are being performed. For example, the sensor device may perform measurements of pulse transit time, health parameters (among other examples, blood oxygen concentration measurement (e.g., SpO2) or heart rate measurement, etc.). In some embodiments, the sensor device may identify the positions 130 and / or 135. For example, the sensor device may use computer vision technology to identify the positions 130 and / or 135 based on information related to the image captured by the image sensor 105 (e.g., spatial information and / or specific wavelength responses in the image captured by the image sensor 105). In some embodiments, the sensor device may identify the positions 130 and / or 135 based on which measurements are being performed. For example, the sensor device may perform measurements of pulse transit time, health parameters (among other examples, blood oxygen concentration measurement (e.g., SpO2) or heart rate measurement, etc.). In some embodiments, the sensor device may identify the positions 130 and / or 135. For example, the sensor device may use computer vision technology to identify the positions 130 and / or 135 based on information related to the image captured by the image sensor 105 (e.g., spatial information and / or specific wavelength responses in the image captured by the image sensor 105). In some embodiments, the sensor device may identify the positions 130 and / or 135 based on which measurements are being performed. For example, the sensor device may perform measurements of pulse transit time, health parameters (among other examples, blood oxygen concentration measurement (e.g., SpO2) or heart rate measurement, etc.). In some embodiments, the sensor device may identify the positions 130 and / or 135. For example, the sensor device may use computer vision technology to identify the positions 130 and / or 135 based on information related to the image captured by the image sensor 105 (e.g., spatial information and / or specific wavelength responses in the image captured by the image sensor 105). In some embodiments, the sensor device may identify the positions 130 and / or 135 based on which measurements are being performed. For example, the sensor device may perform measurements of pulse transit time, health parameters (among other examples, blood oxygen concentration measurement (e.g., SpO2) or heart rate measurement, etc.). In some embodiments, the sensor device may identify the positions 130 and / or 135. For example, the sensor device may use computer vision technology to identify the positions 130 and / or 135 based on information related to the image captured by the image sensor 105 (e.g., spatial information and / or specific wavelength responses in the image captured by the image sensor 105). In some embodiments, the sensor device may identify the positions 130 and / or 135 based on which measurements are being performed. For example, the sensor device may perform measurements of pulse transit time, health parameters (among other examples, blood oxygen concentration measurement (e.g., SpO2) or heart rate measurement, etc.). In some embodiments, the sensor device may identify the positions 130 and / or 135. For example, the sensor device may use computer vision technology to identify the positions 130 and / or 135 based on information related to the image captured by the image sensor 105 (e.g., spatial information and / or specific wavelength responses in the image captured by the image sensor 105). In some embodiments, the sensor device may identify the positions 130 and / or 135 based on which measurements are being performed. For example, the sensor device may perform measurements of pulse transit time, health parameters (among other examples, blood oxygen concentration measurement (e.g., SpO2) or heart rate measurement, etc.). In some embodiments, the sensor device may identify the positions 130 and / or 135. For example, the sensor device may use computer vision technology to identify the positions 130 and / or 135 based on information related to the image captured by the image sensor 105 (e.g., spatial information and / or specific wavelength responses in the image captured by the image sensor 105). In some embodiments, the sensor device may identify the positions 130 and / or 135 based on which measurements are being performed. For example, the sensor device may perform measurements of pulse transit time, health parameters (among other examples, blood oxygen concentration measurement (e.g., SpO2) or heart rate measurement, etc.). In some embodiments, the sensor device may identify the positions 130 and / or 135. For example, the sensor device may use computer vision technology to identify the positions 130 and / or 135 based on information related to the image captured by the image sensor 105 (e.g., spatial information and / or specific wavelength responses in the image captured by the image sensor 105). In some embodiments, the sensor device may identify the positions 130 and / or 135 based on which measurements are being performed. For example, the sensor device may perform measurements of pulse transit time, health parameters (among other examples, blood oxygen concentration measurement (e.g., SpO2) or heart rate measurement, etc.). The subsurface measurement position 130 may be identified for any purpose, and the surface measurement position 135 may be identified for skin hydration measurement and / or bilirubin measurement, etc. As shown in the figure, the subsurface measurement position 130 may be associated with wavelengths λ1 and λ2.

[0016] As shown, the subsurface measurement position 130 may be associated with wavelengths λ1 and λ2. In some embodiments, λ1 and λ2 may be the same wavelength. In some embodiments In some embodiments, λ1 and λ2 may be different wavelengths within the same wavelength range. In some embodiments In some embodiments, λ1 and λ2 may be different wavelength ranges. In some embodiments, λ 1 and / or λ2 may be associated with the near-infrared (NIR) range, which may enable measurements to be taken at the subsurface measurement position 130. In some embodiments, λ1 and / or λ2 may be associated with another wavelength that can penetrate to the corresponding subsurface measurement position (e.g., subsurface measurement position 130).

[0017] As shown in the figure, the surface measurement position 135 may be associated with wavelength λ3. In some embodiments, λ3 may be a visible wavelength, which may enable color-based measurements and / or etc. Thus, λ3 may provide visible measurement information regarding the measurement target. In some embodiments, λ3 may be in the same wavelength range as λ1 and / or λ2. In some embodiments, λ3 may be in a different wavelength range from λ1 and / or λ2. Measurements using λ3 in a wavelength range different from λ1 and / or λ2 may increase the diversity of measurements that can be performed using a sensor device, while measurements using λ3 in the same wavelength range as λ1 and / or λ2 may reduce the complexity of the sensor device.

[0018] FIG. 1 shows a sensor device that receives light at discrete wavelengths for different measurement positions However, it should be understood that the sensor device can receive spectral data related to multiple wavelengths for a given measurement position For example, the sensor device can receive light in a frequency range (which may include any one or more of λ1, λ2, and / or λ3 depending on the measurement target and / or the material properties of the measurement position) for any one or more of the measurement positions shown in FIG. 1 Thus, the sensor device can collect spectrally diverse data measurements related to multiple different frequencies for a given measurement position Furthermore, the sensor device can collect spatially diverse measurement data for one or more frequencies at multiple different measurement positions And further, the sensor device can collect temporally diverse measurement data by performing spatially and / or spectrally diverse measurement data measurements over time As shown in FIG. 1B and also by reference numeral 140, the processor 110 may determine the pulse propagation time using λ1 and λ2 For example, the processor 110 may determine the pulse propagation time based on measurements at the subsurface measurement position 130 In some embodiments, the processor 110 may sample the image data or video stream captured by the image sensor 105 (e.g., multiple times per second), identify the pulse at the first subsurface measurement position 130, and identify the pulse at the second subsurface measurement position 130 Identifying the pulse at the first subsurface measurement position 130 and the second subsurface measurement position 130

[0019] Based on the time difference (e.g., number of samples) between identifying the pulse at the fixed position 130, the processor 110 may determine the pulse propagation time. In some embodiments, the proces sor 110 may determine a blood pressure value based on the pulse propagation time. For example, the processor 1 10 may determine a blood pressure value based on the relationship between the pulse propagation time and blood pressure.

[0020] As indicated by reference numeral 145, the processor 110 may determine another measurement using light associated with λ3 (e.g at the surface measurement position 135). In some embodiments, the proces sor 110 may determine another measurement simultaneously with determining the measurement of the pulse propagation time. This may enable determining temporally correlated health-related measurements that may provide therapeutic advantages, and / or advantages in accuracy, etc. Temporally correlated health-related measurements may be difficult to capture using two or more different sensor devices each configured to perform its respective health-related measurement due to different delays associated with two or more different sensor devices, and / or the difficulty of coordinating the operation of two or more sensor devices. In the exemplary sensor device 100, another measurement is a bili rubin measurement (e.g., based on a color associated with the surface measurement position 135 such as skin color), but another measurement may include any health-related measurement that can be captured via imaging. In some embodiments, the processor 110 may determine a plurality of pulse propagation time values based on the image data. For example, the processor 110 may obtain additional image data regarding one or more other measurement positions and determine a plurality of pulse propagation time values based on the additional image data.

[0021] ​​​​​may be determined. For example, the plurality of pulse propagation times may be related to different regions of the measurement target 115 , and / or different blood vessels 120, etc. Thereby, differential measurement of the pulse propagation time is also possible, and it may be possible to detect discrepancies such as pulse propagation times at different positions on the measurement target, and / or blood pressure. Also, the determination of the pulse propagation time value based on the image data can capture a plurality of different measurement targets in a single image, so that it is possible to measure the pulse propagation times of a plurality of different measurement targets (e.g., a plurality of different people) using a single image sensor, thereby potentially saving resources associated with the implementation of a plurality of different sensor devices. As indicated by reference numeral 150, the processor 110 may provide the user device 155 with information identifying the measurements determined in relation to reference numerals 140 and 145. In some embodiments, the user device 155 may be a sensor device. For example,

[0022] the processor 110 and the image sensor 105 may be components of the user device 155. In some embodiments, the user device 155 may be separate from the sensor device. As indicated by reference numeral 160, the user device 155 may 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 indicated by reference numeral 165, the visual interface may be a blood pressure determined based on the pulse propagation time. In some embodiments, the user device 155 may be separate from the sensor device.

[0023] As indicated by reference numeral 160, the user device 155 may 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 indicated by reference numeral 165, the visual interface is shown as a health interface. As indicated by reference numeral 165, the visual interface may be a blood pressure determined based on the pulse propagation time. Shows blood pressure measurement. Further, the visual interface is used to determine the pulse transit time Shows the subsurface measurement location used (e.g., the subsurface measurement location 130 shown in FIG. 1A). As indicated by reference number 170, the visual interface indicates that there is a possibility that the bilirubin measurement is abnormal (e.g., based on the color of the measurement target 115 at the surface measurement location 135 in FIG. 1A). Further, the visual interface indicates the surface measurement location used to determine the bilirubin measurement (e.g., the surface measurement location 135 shown in FIG. 1A). In some embodiments, the user device 155 may update the visual interface. For example, the user device 155 may update the blood pressure measurement based on an image captured over time, and / or provide additional measurements determined based on an image captured by the sensor device. In some embodiments, the user device 155 may provide information based on an interaction with the visual interface. For example, the user device 155 may provide additional details regarding the blood pressure measurement (e.g., pulse transit time, heart rate associated with the pulse transit time, additional pulse transit times and / or blood pressures for different measurement locations of the measurement target 115, and / or etc.) based on receiving an interaction (e.g., user interaction, etc.) with the visual representation of the blood pressure measurement. As another example, the user device 155 may modify the measurement location based on an interaction (e.g., an interaction that moves the visual representation of the measurement location and / or an interaction that designates a new location for the measurement location, etc.). As yet another example, the user device 155 or a process Shows the surface measurement location used to determine the bilirubin measurement (e.g., the surface measurement location 135 shown in FIG. 1A).

[0024] In some embodiments, the user device 155 may update the visual interface. For example, the user device 155 may update the blood pressure measurement based on an image captured over time and / or provide additional measurements determined based on an image captured by the sensor device. In some embodiments the user device 155 may provide information based on an interaction with the visual interface. For example, the user device 155 may provide additional details regarding the blood pressure measurement (e.g., pulse transit time, heart rate associated with the pulse transit time, additional pulse transit times and / or blood pressures for different measurement locations of the measurement target 115, and / or etc.) based on receiving an interaction (e.g., user interaction, etc.) with the visual representation of the blood pressure measurement. (e.g., pulse transit time, heart rate associated with the pulse transit time, additional pulse transit times and / or blood pressures for different measurement locations of the measurement target 115, and / or etc.) In some embodiments, the user device 155 may update the visual interface. For example, the user device 155 may update the blood pressure measurement based on an image captured over time, and / or provide additional measurements determined based on an image captured by the sensor device. In some embodiments, the user device 155 may provide information based on an interaction with the visual interface. For example, the user device 155 may provide additional details regarding the blood pressure measurement (e.g., pulse transit time, heart rate associated with the pulse transit time, additional pulse transit times and / or blood pressures for different measurement locations of the measurement target 115, and / or etc.) based on receiving an interaction (e.g., user interaction, etc.) with the visual representation of the blood pressure measurement. As another example, the user device 155 may modify the measurement location based on an interaction (e.g., an interaction that moves the visual representation of the measurement location and / or an interaction that designates a new location for the measurement location, etc.). As yet another example, the user device 155 or a process For example, the user device 155 may provide additional details regarding the blood pressure measurement (e.g., pulse transit time, heart rate associated with the pulse transit time, additional pulse transit times and / or blood pressures for different measurement locations of the measurement target 115, and / or etc.) based on receiving an interaction (e.g., user interaction, etc.) with the visual representation of the blood pressure measurement. As another example, the user device 155 may modify the measurement location based on an interaction (e.g., an interaction that moves the visual representation of the measurement location and / or an interaction that designates a new location for the measurement location, etc.). As yet another example, the user device 155 or a process The sensor 110 may perform measurements based on the interactions. For example, the interactions may affect the measurements to be performed. may be selected (e.g., from a menu of available measurements) or a location may be specified for the measurement. The user device 155 and / or the processor 110 may measure the may be performed and information indicative of the results of the measurements may be provided.

[0025] In some embodiments, the processor 110 performs a measurement based on the results of another measurement. For example, the processor 110 may determine that a blood pressure measurement or a heart rate measurement meets a threshold. and may take another measurement (e.g., blood pressure measurement) based on the blood pressure measurement or heart rate measurement meeting a threshold. Some blood oxygen measurements, temperature measurements, and / or skin hydration measurements may be performed. In this embodiment, the processor 110 may perform the measurements without user interaction (e.g., automatically). thereby saving processor resources used in connection with manually triggering a measurement. In some embodiments, the processor 110 may include information identifying the measurement. Provide information (e.g., via a visual interface and / or as notifications or alerts) In some implementations, the processor 110 may provide a measurement-based The system may also trigger an action to be taken (e.g., dispatch a nurse or administer medication). and / or provide notifications to prompt users to perform activities).

[0026] In some embodiments, the processor 110 or the user device 155 may be configured to The blood pressure may be determined based on time. For example, the processor 110 or the user device 1 55 based on an estimated pressure difference between measurement locations 130 based on the pulse wave velocity (e.g., The blood pressure may be determined by dividing the moving distance between positions 130 by the pulse propagation time. In several embodiments, the processor 110 or the user device 155 may use a technique different from the above-described technique to determine the blood pressure based on the pulse propagation time.

[0027] In this way, the pulse propagation time measurement using the image sensor 105 is performed. Further more, additional measurements using the image sensor 105 may be determined in relation to the pulse propagation time measurement (e.g., simultaneously), thereby enabling a temporal correlation of such measurements. Accordingly, the complexity of the sensor device is reduced and the flexibility of the measurement is improved. Further, the pulse propagation time may be performed for any two or more measurement positions at any appropriate intervals with respect to each other, thereby improving the usefulness of the pulse propagation time data and reducing the mechanical complexity of the sensor device as compared to a sensor device having contact means for determining the pulse propagation time at adjustable intervals. In some embodiments, the image sensor 105 and / or the processor 110 may be included in a sensor device such as the sensor device 210 described in connection with FIG. 2 below.

[0028] The sensor device 210 may be capable of sampling the spectrum over a plurality of points in a scene and providing an image whose features and positions can be identified to provide a plurality of points for spectrum comparison. Therefore, the sensor device may perform blood pressure measurement based on the pulse propagation time and / or one or more other measurements described herein. Further, the sensor device 210 may employ sensors at different points in space. It can provide more flexibility than a chair. For example, the sensor device 210 can perform measurements in a non-contact manner on a plurality of users, including users who are not wearing the sensor device 210. Further, the sensor device 210 can be more resilient to sub-optimal sensor placements than a device that employs respective sensors at different points in space. For example, the sensor device 210 can capture an image related to a field of view (FOV), and may analyze a plurality of subjects within the FOV, which can be particularly beneficial in a healthcare environment such as a care home where the sensor device 210 can instantaneously recognize and monitor an individual's health emergency while moving within a common use space. Further, in some embodiments, the sensor device 210 can perform the operations described herein in a non-contact manner (e.g., without contacting the measurement target of the sensor device 210), and can provide spectral data at a plurality of points (e.g., all points, a plurality of points) in a scene within the FOV of the sensor device 210. As shown above, FIGS. 1A and 1B are provided merely as one or more examples. Other examples may be different from those described with respect to FIGS. 1A and 1B. As shown above, FIGS. 1A and 1B are provided merely as one or more examples. Other examples may be different from those described with respect to FIGS. 1A and 1B. FIG. 2 is a diagram of an exemplary environment 200 in which the systems and / or methods described herein may be implemented. As shown in FIG. 2, the environment 200 may include a user device 240, a network 250, and a sensor device 210 that may include a processor 220 and an image sensor 230. The

[0029] devices of the environment 200 may be connected by a wired connection, a wireless connection, or As shown above, FIGS. 1A and 1B are provided merely as one or more examples. Other examples may be different from those described with respect to FIGS. 1A and 1B.

[0030] FIG. 2 is a diagram of an exemplary environment 200 in which the systems and / or methods described herein may be implemented. As shown in FIG. 2, the environment 200 may include a user device 240, a network 250, and a sensor device 210 that may include a processor 220 and an image sensor 230. The devices of the environment 200 may be connected by a wired connection, a wireless connection, or As shown in FIG. 2, the environment 200 may include a user device 240, a network 250, and a sensor device 210 that may include a processor 220 and an image sensor 230. The devices of the environment 200 may be connected by a wired connection, a wireless connection, or They may be interconnected via a combination of wired and wireless connections.

[0031] The sensor device 210 may include an optical device capable of storing, processing, and / or routing information related to sensor determination, and / or one or more devices capable of performing sensor measurements on an object. For example, the sensor device 210 may include a spectroscopic device that performs spectroscopy, such as a spectroscopic sensor device (e.g., a near-infrared (NIR) spectrometer, a mid-infrared spectrometer (mid-IR), and / or a binary multichannel spectroscopic sensor device that performs vibrational spectroscopy such as a Raman spectrometer). For example, the sensor device 210 may perform health parameter monitoring determination, pulse transit time determination, biometric authentication determination, and / or activity detection determination, etc. In this case, the sensor device 210 may utilize the same wavelength, different wavelengths, and / or a combination of the same wavelength and different wavelengths for such determinations. In some embodiments, the sensor device 2 10 may be incorporated into a user device 240 such as a wearable spectrometer and / or the like. In some embodiments, the sensor device 210 may receive information from another device within the environment 200 such as the user device 2 40, and / or transmit information to another device. In some embodiments, the sensor device 210 may include a spectroscopic image camera. The spectroscopic image camera is a device capable of capturing an image of a scene. The spectroscopic image camera (or the processor 220 associated with the spectroscopic image camera) may perform any In some embodiments, the sensor device 210 may be incorporated into another device within the environment 200 such as the user device 2 40, and / or transmit information to another device. In some embodiments, the sensor device 210 may receive information from another device within the environment 200 such as the user device 2

[0032] In some embodiments, the sensor device 210 may include a spectroscopic image camera. The spectroscopic image camera is a device capable of capturing an image of a scene. The spectroscopic image camera (or the processor 220 associated with the spectroscopic image camera) may perform any It may also be possible to determine spectral content or changes in spectral content at different points within the image of the scene, such as points of interest.

[0033] In some embodiments, sensor device 210 may include a spectral image camera capable of performing hyperspectral imaging. For example, sensor device 210 may include a spectral filter array (e.g., a tiled spectral filter array). In some embodiments, the spectral filter array may be disposed on image sensor 2 30. In some embodiments, sensor device 210 may include a diffuser. For example, the diffuser may be configured to diffuse light along the path to image sensor 230. Each point within the image captured by sensor device 210 may be mapped to a unique pseudo-random pattern on a spectral filter array that encodes multiplexed spatio-spectral information. Thus, a hyperspectral volume having sub-superpixel resolution can be recovered by solving a sparse-constrained inverse problem. Sensor device 210 may include a continuous spectral filter or a discontinuous spectral filter, which may be selected for a given application. The use of a diffuser and computational approach to determine a hyperspectral volume at sub-superpixel resolution can improve the sampling of spectral content, thereby enabling imaging using a spectral filter such as a hyperspectral filter array. ​​​​​​​​Therefore, the manufacture of the sensor device 210 is simplified in relation to the manufacture of filters on the order of the dimensions of each pixel. In some embodiments, the sensor device 210 may include a lens.

[0034] The sensor device 210 may include a processor 220. The processor 220 will be described in more detail in relation to FIG. 3.

[0035] The sensor device 210 may include an image sensor 230. The image sensor 230 includes devices capable of sensing light. For example, the image sensor 230 may include an image sensor, a multispectral sensor, and / or a spectral sensor, etc. In some embodiments, the image sensor 230 may include a charge-coupled device (CCD) sensor, and / or a complementary metal-oxide-semiconductor (CMOS) sensor, etc. In some embodiments, the image sensor 230 may include a front-side illumination (FSI) sensor, and / or a back-side illumination (BSI) sensor, etc. In some embodiments, the image sensor 230 may be included in the camera of the sensor device 210 and / or the user device 240.

[0036] The user device 240 includes one or more devices capable of receiving, generating, storing, processing, and / or providing information related to sensor determination. For example, the user device 240 may be a mobile phone (e.g., a smartphone, and / or a wireless phone, etc.), a computer (e.g., a laptop computer, a tablet computer, and / or a portable computer, etc.), a game device, a wearable communication device (e.g., a smartwatch, and so on). and / or communication devices such as smart glasses, or devices of a similar type, and / or may include computing devices. In some embodiments, user device 240 may receive information from another device within environment 200, such as sensor device 210, and / or may transmit information to another device within environment 200.

[0037] Network 250 includes one or more wired networks and / or wireless networks. For example, network 250 may be a cellular network (e.g., Long Term Evolution (LTE) network, Code Division Multiple Access (CDMA) network, 3G network, 4G network, 5G network, and / or another type of next-generation network, etc.), Public Land Mobile Network (PLMN), Local Area Network (LAN), Wide Area Network (WAN), Metropolitan Area Network (MAN), telephone network (e.g., Public Switched Telephone Network (PSTN)), private network, ad hoc network, intranet, Internet, fiber-optic-based network, cloud computing network, etc., and / or a combination of these or other types of networks may be included.

[0038] The number and arrangement of devices and networks shown in FIG. 2 are provided by way of example. In practice, there may be additional devices and / or networks, fewer devices and / or networks, different devices and / or networks, or devices and / or networks in a different arrangement than shown in FIG. 2. Furthermore, the devices and networks shown in FIG. 2 Two or more devices may be implemented within a single device, or as shown in FIG. 2 A single device may be implemented as a plurality of distributed devices. For example, sensor de vice 210 and user device 240 are described as separate devices, but sensor device 210 and user device 240 may be implemented as a single device In addition, or alternatively, a set of devices in environment 200 (e.g., one or more devices) may perform one or more functions described as being performed by another set of devices in environment 200 FIG. 3 is a diagram of exemplary components of device 300. Device 300 may correspond to sensor de

[0039] vice 210 and user device 240. In some embodiments sensor device 210 and / or user device 240 may include one or more de vices 300 and / or one or more components of device 300. As shown in FIG. 3 device 300 may include bus 310, processor 320, memory 330, storage component 340, input component 350, output component 360, and communication interface 370. Bus 310 includes components that permit communication among the plurality of components of device 300. Processor 320 is implemented in hardware, firmware, and / or a combination of hardware and software. Processor 320 may be a central processing unit (CPU), a graphics processing unit (GPU), an accelerated processing unit (APU), a micro

[0040] processor, or other suitable processing component. Memory 330 stores data and instructions for use by processor 320. Storage component 340 may include a hard disk drive, a solid state drive, a flash drive, a compact disc read only memory (CD-ROM), a digital versatile disc (DVD), or other suitable storage medium. Input component 350 may include a keyboard, a mouse, a touch screen, a microphone, or other suitable input device. Output component 360 may include a monitor, a speaker, a printer, or other suitable output device. Communication interface 370 permits device 300 to communicate with other devices, such as other devices in environment 200. processor, or other suitable processing component. Memory 330 stores data and instructions for use by processor 320. Storage component 340 may include a hard disk drive, a solid state drive, a flash drive, a compact disc read only memory (CD-ROM), a digital versatile disc (DVD), or other suitable storage medium. Input component 350 may include a keyboard, a mouse, a touch screen, a microphone, or other suitable input device. Output component 360 may include a monitor, a speaker, a printer, or other suitable output device. Communication interface 370 permits device 300 to communicate with other devices, such as other devices in environment 200. processor, or other suitable processing component. Memory 330 stores data and instructions for use by processor 320. Storage component 340 may include a hard disk drive, a solid state drive, a flash drive, a compact disc read only memory (CD-ROM), a digital versatile disc (DVD), or other suitable storage medium. Input component 350 may include a keyboard, a mouse, a touch screen, a microphone, or other suitable input device. Output component 360 may include a monitor, a speaker, a printer, or other suitable output device. Communication interface 370 permits device 300 to communicate with other devices, such as other devices in environment 200. processor, or other suitable processing component. Memory 330 stores data and instructions for use by processor 320. Storage component 340 may include a hard disk drive, a solid state drive, a flash drive, a compact disc read only memory (CD-ROM), a digital versatile disc (DVD), or other suitable storage medium. Input component 350 may include a keyboard, a mouse, a touch screen, a microphone, or other suitable input device. Output component 360 may include a monitor, a speaker, a printer, or other suitable output device. Communication interface 370 permits device 300 to communicate with other devices, such as other devices in environment 200. A processor, a microcontroller, a digital signal processor (DSP), a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), or other types of processing components. In some embodiments, the processor 320 includes one or more processors that can be programmed to perform functions. The memory 330 stores random access memory (RAM), read only memory (ROM), and / or other types of dynamic or static storage devices (e.g., flash memory, magnetic memory, and / or optical memory) for information and / or instructions used by the processor 320. The storage component 340 stores information and / or software related to the operation and use of the device 300. For example, the storage component 340 can include a hard disk (e.g., a magnetic disk, an optical disk, and / or a magneto-optical disk), a solid state drive (SSD), a compact disk (CD), a digital versatile disk (DVD), a floppy disk, a cartridge, a magnetic tape, and / or another type of non-transitory computer-readable medium, along with a corresponding drive. The input component 350 includes components that enable the device 300 to receive information, such as through 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, the input component 350 includes components for determining a position. including one or more processors that can be programmed to perform functions. The memory 330 stores random access memory (RAM), read only memory (ROM), and / or other types of dynamic or static storage devices (e.g., flash memory, magnetic memory, and / or optical memory) for information and / or instructions used by the processor 320. stores random access memory (RAM), read only memory (ROM), and / or other types of dynamic or static storage devices (e.g., flash memory, magnetic memory, and / or optical memory) for information and / or instructions used by the processor 320. random access memory (RAM), read only memory (ROM), and / or other types of dynamic or static storage devices (e.g., flash memory, magnetic memory, and / or optical memory) for information and / or instructions used by the processor 320. and / or other types of dynamic or static storage devices (e.g., flash memory, magnetic memory, and / or optical memory) for information and / or instructions used by the processor 320. for information and / or instructions used by the processor 320.

[0041] The storage component 340 stores information and / or software related to the operation and use of the device 300. For example, the storage component 340 can include a hard disk (e.g., a magnetic disk, an optical disk, and / or a magneto-optical disk), a solid state drive (SSD), a compact disk (CD), a digital versatile disk (DVD), a floppy disk, a cartridge, a magnetic tape, and / or another type of non-transitory computer-readable medium, along with a corresponding drive. stores information and / or software related to the operation and use of the device 300. For example, the storage component 340 can include a hard disk (e.g., a magnetic disk, an optical disk, and / or a magneto-optical disk), a solid state drive (SSD), a compact disk (CD), a digital versatile disk (DVD), a floppy disk, a cartridge, a magnetic tape, and / or another type of non-transitory computer-readable medium, along with a corresponding drive. include a hard disk (e.g., a magnetic disk, an optical disk, and / or a magneto-optical disk), a solid state drive (SSD), a compact disk (CD), a digital versatile disk (DVD), a floppy disk, a cartridge, a magnetic tape, and / or another type of non-transitory computer-readable medium, along with a corresponding drive. a hard disk (e.g., a magnetic disk, an optical disk, and / or a magneto-optical disk), a solid state drive (SSD), a compact disk (CD), a digital versatile disk (DVD), a floppy disk, a cartridge, a magnetic tape, and / or another type of non-transitory computer-readable medium, along with a corresponding drive. a solid state drive (SSD), a compact disk (CD), a digital versatile disk (DVD), a floppy disk, a cartridge, a magnetic tape, and / or another type of non-transitory computer-readable medium, along with a corresponding drive. a digital versatile disk (DVD), a floppy disk, a cartridge, a magnetic tape, and / or another type of non-transitory computer-readable medium, along with a corresponding drive.

[0042] The input component 350 includes components that enable the device 300 to receive information, such as through 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, the input component 350 includes components for determining a position. such as through 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, the input component 350 includes components for determining a position. through 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, the input component 350 includes components for determining a position. Additionally, or alternatively, the input component 350 includes components for determining a position. a positioning component (e.g., a Global Positioning System (GPS) component) and / or may include sensors (e.g., accelerometers, gyroscopes, actuators, and / or other types of position or environmental sensors, etc.). The output component 36 0 includes components that provide output information from the device 300 (e.g., via displays, speakers, haptic feedback components, and / or audio or visual indicators, etc.).

[0043] The communication interface 370 includes a component such as a transceiver that enables the device 300 to communicate with other devices via a wired connection, a wireless connection, or a combination of wired and wireless connections (e.g., a transceiver, another receiver, and / or another transmitter, etc.). The communication interface 370 may enable the device 300 to receive information from other devices and / or provide information to other devices. For example, the communication interface 370 may include an Ethernet interface, an optical interface, a coaxial interface, an infrared interface, a radio frequency (R F) interface, a Universal Serial Bus (USB) interface, a Wi- Fi interface, and / or a cellular network interface, etc. The device 300 may perform one or more of the processes described herein. The device 300 includes a processor 320 that executes software instructions stored by a non-transitory computer-readable medium such as the memory 330 and / or the storage component 340.

[0044] Based on this, these processes may be implemented. As used herein, the term "computer" "readable medium" refers to a non-transitory memory device. The memory device may be a memory space within a single physical storage device, or may include memory spaces spanning multiple physical storage devices.

[0045] Software instructions may be read into the memory 330 and / or the storage component 3 40 from another computer-readable medium or from another device via the communication interface 37 0. When executed, the software instructions stored in the memory 330 and / or the storage component 3 40 may cause the processor 320 to perform one or more processes described herein. Additionally, or alternatively, a hardware circuit may be used to perform one or more processes described herein instead of, or in combination with, the software instructions. Accordingly, the embodiments described herein are not limited to any particular combination of hardware circuit and software. The number and arrangement of components shown in FIG. 3 are provided by way of example. In practice, the device 300 may include additional components, fewer components, different components, or components arranged differently than those shown in FIG. 3.

[0046] Additionally, or alternatively, a set of components of the device 300 (e.g., one or more components) may perform one or more functions described as being performed by another set of components of the device 300.

[0047] Figure 4 is an exemplary process 400 for determining pulse transit time using an image sensor. In some embodiments, one or more process blocks of FIG. 4 may be performed by a sensor device (e.g., sensor device 210 and / or a sensor device described in connection with FIG. 1). In some embodiments, one or more process blocks of FIG. 4 may be performed by a device other than the sensor device, such as a user device (e.g., user device 155 and / or user device 240), or by a group of devices. As shown in FIG. 4, process 400 may include obtaining first image data regarding a first measurement position of a measurement target (block 410). For example, the sensor device may obtain first image data regarding a first measurement position of the measurement target as described above (e.g., using processor 320, memory 330, and / or communication interface 370).

[0048] As further shown in FIG. 4, process 400 may include obtaining second image data regarding a second measurement position of the measurement target, where the first measurement position and the second measurement position are subsurface measurement positions within the measurement target (block 420). For example, the sensor device may obtain second image data regarding a second measurement position of the measurement target as described above (e.g., using processor 320, memory 330, and / or communication interface 370). In some embodiments, the first measurement position and the second measurement position are subsurface measurement positions within the measurement target.

[0049] As further shown in FIG. 4, process 400 may include obtaining second image data regarding a second measurement position of the measurement target, where the first measurement position and the second measurement position are subsurface measurement positions within the measurement target (block 420). For example, the sensor device may obtain second image data regarding a second measurement position of the measurement target as described above (e.g., using processor 320, memory 330, and / or communication interface 370). In some embodiments, the first measurement position and the second measurement position are subsurface measurement positions within the measurement target. In some embodiments, the first measurement position and the second measurement position are subsurface measurement positions within the measurement target. ​

[0050] As further shown in FIG. 4, process 400 may include determining a pulse transit time measurement based on the first image data and the second image data (block 430). For example, the sensor device (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) may determine a pulse transit time measurement based on the first image data and the second image data as described above. on, as described above. For example, the sensor device (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) may determine a pulse transit time measurement based on the first image data and the second image data as described above. on, as described above. As further shown in FIG. 4, process 400 may include providing information identifying the pulse transit time measurement (block 440). For example, the sensor device (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) may provide information identifying the pulse transit time measurement as described above.

[0051] As further shown in FIG. 4, process 400 may include providing information identifying the pulse transit time measurement (block 440). For example, the sensor device (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) may provide information identifying the pulse transit time measurement as described above. For example, the sensor device (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) may provide information identifying the pulse transit time measurement as described above. For example, the sensor device (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) may provide information identifying the pulse transit time measurement as described above. process 400 may include additional embodiments such as any single embodiment described below or any combination thereof, and / or embodiments related to one or more other processes described elsewhere in this specification.

[0052] process 400 may include additional embodiments such as any single embodiment described below or any combination thereof, and / or embodiments related to one or more other processes described elsewhere in this specification. In a first embodiment, the sensor comprises an image sensor of a camera of the sensor device. In a second embodiment, alone or in combination with the first embodiment, step 400 includes determining a blood pressure value using the pulse transit time measurement.

[0053] In a first embodiment, the sensor comprises an image sensor of a camera of the sensor device. .

[0054] In a second embodiment, alone or in combination with the first embodiment, process 400 includes determining a blood pressure value using the pulse transit time measurement. In a third embodiment, alone or in combination with one or more of the first and second embodiments,

[0055] In a third embodiment, alone or in combination with one or more of the first and second embodiments, The image data includes multispectral image data.

[0056] In a fourth embodiment, alone or in combination with one or more of the first to third embodiments the process 400 uses the image data to determine other measurements other than pulse transit time measurement including doing so.

[0057] In a fifth embodiment, alone or in combination with one or more of the first to fourth embodiments the other measurements are performed using visible range information.

[0058] In a sixth embodiment, alone or in combination with one or more of the first to fifth embodiments the other measurements are related to the skin color of the measurement target.

[0059] In a seventh embodiment, alone or in combination with one or more of the first to sixth embodiments the other measurements include health parameters.

[0060] In an eighth embodiment, alone or in combination with one or more of the first to seventh embodiments the health parameters include at least one of heart rate measurement or SpO2 measurement.

[0061] In a ninth embodiment, alone or in combination with one or more of the first to eighth embodiments The first image data and the second image data are each associated with wavelengths that penetrate the measurement target at a first measurement position and a second measurement position respectively.

[0062] Figure 4 shows exemplary blocks of process 400, but in some embodiments process 400 may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted in Figure 4. Additionally, or alternatively ​ Two or more of the blocks of process 400 may be performed in parallel.

[0063] FIG. 5 is a flowchart of an exemplary process 500 for determining pulse propagation time using an image sensor. In some embodiments, one or more of the process blocks of FIG. 5 may be performed by a sensor device (e.g., sensor device 210 and / or the sensor device described in connection with FIG. 1, etc.). In some embodiments, one or more of the process blocks of FIG. 5 may be performed by a user device (e.g., user device 155 and / or user device 240, etc.) and / or by another device or group of devices in combination with a sensor device. As shown in FIG. 5, process 500 may include collecting image data using a sensor (block 510). For example, the sensor device may (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) collect image data using a sensor as described above. As further shown in FIG. 5, process 500 may include obtaining first image data regarding a first measurement position of a measurement target from the image data (block 520). For example, the sensor device may (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) obtain first image data regarding a first measurement position of a measurement target from the image data as described above.

[0064]

[0065]

[0066] ​​​​​​​​​As further shown in FIG. 5, process 500 may include obtaining second image data regarding a second measurement position of the measurement target from the image data, and the first measurement position and the second measurement position are subsurface measurement positions within the measurement target (block 530). For example, the sensor device may (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) obtain second image data regarding a second measurement position of the measurement target from the image data as described above. In some embodiments, the first measurement position and the second measurement position are subsurface measurement positions within the measurement target . .

[0067] As further shown in FIG. 5, process 500 may include determining a pulse transit time measurement based on the first image data and the second image data (block 540). For example, the sensor device may (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) determine a pulse transit time measurement based on the first image data and the second image data as described above.

[0068] As further shown in FIG. 5, process 500 may include providing information identifying the pulse transit time measurement (block 550). For example, the sensor device may (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) provide information identifying the pulse transit time measurement as described above.

[0069] Process 500 may be any single embodiment described below or any combination thereof related to one or more other processes described herein and / or elsewhere in this specification Embodiments, additional embodiments such as may be included.

[0070] In a first embodiment, the first image data and the second image data are based on light generated by a sensor device thereby.

[0071] In a second embodiment, alone or in combination with the first embodiment, the first image data and the second image data are related to the near-infrared spectral range.

[0072] In a third embodiment, alone or in combination with one or more of the first and second embodiments, step 500 includes obtaining additional image data regarding one or more other measurement positions and determining one or more other pulse transit time values based on the additional image data.

[0073] In a fourth embodiment, alone or in combination with one or more of the first through third embodiments, the input of the sensor is filtered by a filter based on binary multispectral technology .

[0074] In a fifth embodiment, alone or in combination with one or more of the first through fourth embodiments, the first image data is associated with a first wavelength passed to the sensor, and the second image data is associated with a second wavelength passed to the sensor.

[0075] FIG. 5 shows exemplary blocks of process 500, but in some embodiments, process 500 may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted in FIG. 5. Additionally, or alternatively Two or more of the blocks of process 500 may be performed in parallel.

[0076] FIG. 6 is a flowchart of an exemplary process 600 for determining pulse propagation time using an image sensor. In some embodiments, one or more of the process blocks of FIG. 6 may be performed by a sensor device (e.g., sensor device 210 and / or the sensor device described in connection with FIG. 1, etc.). In some embodiments, one or more of the process blocks of FIG. 6 may be performed by a user device (e.g., user device 155 and / or user device 240, etc.) and / or another device or group of devices different from the sensor device. As shown in FIG. 6, process 600 may include obtaining first image data regarding a first measurement position of a measurement target and second image data regarding a second measurement position of the measurement target, where the first measurement position and the second measurement position are subsurface measurement positions within the measurement target, and the first image data and the second image data are obtained from a video stream (block 610). For example, the sensor device may obtain, as described above, first image data regarding a first measurement position of the measurement target and second image data regarding a second measurement position of the measurement target (e.g., using processor 320, memory 330, and / or communication interface 370, etc.). In some embodiments, the first measurement position and the second measurement position are subsurface measurement positions within the measurement target. In some embodiments, the first image data and the second image data are obtained from a video stream.

[0077] As shown in FIG. 6, process 600 may include obtaining first image data regarding a first measurement position of a measurement target and second image data regarding a second measurement position of the measurement target, where the first measurement position and the second measurement position are subsurface measurement positions within the measurement target, and the first image data and the second image data are obtained from a video stream (block 610). For example, the sensor device may obtain, as described above, first image data regarding a first measurement position of the measurement target and second image data regarding a second measurement position of the measurement target (e.g., using processor 320, memory 330, and / or communication interface 370, etc.). In some embodiments, the first measurement position and the second measurement position are subsurface measurement positions within the measurement target. In some embodiments, the first image data and the second image data are obtained from a video stream. (block 610). For example, the sensor device may obtain, as described above, first image data regarding a first measurement position of the measurement target and second image data regarding a second measurement position of the measurement target (e.g., using processor 320, memory 330, and / or communication interface 370, etc.). In some embodiments, the first measurement position and the second measurement position are subsurface measurement positions within the measurement target. In some embodiments, the first image data and the second image data are obtained from a video stream. 330, and / or communication interface 370, etc.). In some embodiments, the first measurement position and the second measurement position are subsurface measurement positions within the measurement target. In some embodiments, the first image data and the second image data are obtained from a video stream. target and second image data regarding a second measurement position of the measurement target. In some embodiments, the first measurement position and the second measurement position are subsurface measurement positions within the measurement target. In some embodiments, the first image data and the second image data are obtained from a video stream. position and the second measurement position are subsurface measurement positions within the measurement target. In some embodiments, the first image data and the second image data are obtained from a video stream. (block 610). In some embodiments, the first measurement position and the second measurement position are subsurface measurement positions within the measurement target. In some embodiments, the first image data and the second image data are obtained from a video stream. .

[0078] As further shown in FIG. 6, process 600 may include determining a pulse transit time measurement based on first image data and second image data (block 620). For example, the sensor device may (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) determine a pulse transit time measurement based on the first image data and the second image data as described above. For example, the sensor device may (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) determine a pulse transit time measurement based on the first image data and the second image data as described above. For example, the sensor device may (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) determine a pulse transit time measurement based on the first image data and the second image data as described above. For example, the sensor device may (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) determine a pulse transit time measurement based on the first image data and the second image data as described above. For example, the sensor device may (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) determine a pulse transit time measurement based on the first image data and the second image data as described above.

[0079] As further shown in FIG. 6, process 600 may include providing information that identifies a pulse transit time measurement (block 630). For example, the sensor device may (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) provide information that identifies a pulse transit time measurement as described above. For example, the sensor device may (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) provide information that identifies a pulse transit time measurement as described above. For example, the sensor device may (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) provide information that identifies a pulse transit time measurement as described above. For example, the sensor device may (e.g., using processor 320, memory 330, and / or communication interface 370, etc.) provide information that identifies a pulse transit time measurement as described above.

[0080] Process 600 may include additional embodiments, such as any single embodiment described below or any combination thereof, and / or one or more other processes related embodiments described elsewhere in this specification. Process 600 may include additional embodiments, such as any single embodiment described below or any combination thereof, and / or one or more other processes related embodiments described elsewhere in this specification. Process 600 may include additional embodiments, such as any single embodiment described below or any combination thereof, and / or one or more other processes related embodiments described elsewhere in this specification.

[0081] In a first embodiment, the sensor device includes a smartphone.

[0082] In a second embodiment, alone or in combination with the first embodiment, process 600 includes providing a visual representation of a video stream having information that identifies a pulse transit time value or information determined based on the pulse transit time. In a second embodiment, alone or in combination with the first embodiment, process 600 includes providing a visual representation of a video stream having information that identifies a pulse transit time value or information determined based on the pulse transit time. In a second embodiment, alone or in combination with the first embodiment, process 600 includes providing a visual representation of a video stream having information that identifies a pulse transit time value or information determined based on the pulse transit time.

[0083] In a third embodiment, process 600 provides a video stream alone or in combination with the first and second Used in combination with one or more of the embodiments to determine another measurement other than pulse transit time measurement including doing so.

[0084] FIG. 6 shows exemplary blocks of process 600, but in some embodiments, process 600 can include additional blocks, fewer blocks, different blocks, or blocks in a different arrangement than those depicted in FIG. 6. Additionally, or alternatively , two or more of the blocks of process 600 may be performed in parallel.

[0085] The foregoing disclosure provides illustration and description, but is not intended to be exhaustive or to limit the embodiments to the exact form disclosed. Modifications and variations may be made in light of the above disclosure or obtained from practice of the embodiments. As used herein, the term "component" is intended to be broadly construed as hardware, firmware, and / or a combination of hardware and software.

[0086] As used herein, meeting a threshold may, depending on the context, refer to a value being greater than, more than, higher than, greater than or equal to, less than, lower than the threshold, or the same as the threshold, etc. A particular user interface is described herein and / or shown in the figures.

[0087] The user interface can include, for example, a graphical user interface, a non-graphical user interface, and / or a text-based user interface, etc.

[0088] A particular user interface is described herein and / or shown in the figures. The user interface can include a graphical user interface, a non-graphical user interface, and / or a text-based user interface, etc. It is possible. The user interface can provide information for display. In some embodiments, the user provides a user interface for display and can interact with the information, such as by providing input via an input component of the device. In some embodiments, the user interface may be configurable by the device and / or the user (e.g., the user can change the size of the user interface, the information provided through the user interface, the position of the information provided through the user interface, etc.). Additionally, or alternatively, the user interface may be pre-configured in a standard configuration, a specific configuration based on the type of device on which the user interface is displayed, and / or a set of configurations based on the capabilities and / or specifications related to the device on which the user interface is displayed.

[0089] It will be apparent that the systems and / or methods described herein can be implemented in different forms of hardware, firmware, or a combination of hardware and software. The actual special control hardware or software code used to implement these systems and / or methods does not limit the embodiments. Thus the operation and behavior of the systems and / or methods are described herein without reference to specific software code - it is understood that the software and hardware can be designed to implement the systems and / or methods based on the description herein.

[0090] A specific combination of features is recited in the claims and / or disclosed in the specification However, these combinations are not intended to limit the disclosure of the various embodiments. In fact, many of these features can be combined in ways not specifically recited in the claims and / or in ways not disclosed herein. Each dependent claim described below can only directly depend on one claim, but the various embodiments of the disclosure include each dependent claim in combination with all other claims in the claim set.

[0091] Any element, operation, or instruction used herein should not be construed as important or essential unless so expressly described. Also, as used herein, the indefinite 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 definite article "the" is intended to include one or more items referred to in relation to the definite article "the" and may be used interchangeably with "one or more." Further, as used herein, the term "set" is intended to include one or more items (e.g., related items, unrelated items, combinations of related and unrelated items, etc.) and may be used interchangeably with "one or more." When only one item is intended, the phrase "only one" or similar language is used. Also, as used herein, the terms "has," "have," "having," etc. are intended to be terms without limitation. Further, the phrase "based on" is intended to mean "at least partially based on" unless is intended to be inclusive and, unless expressly stated otherwise (e.g., when used in combination with "either " or "only one of either"), can be used interchangeably with "and / or". ​

Claims

1. A step of obtaining, by a sensor device, first image data regarding a first measurement position of a measurement target from image data collected by a sensor of the sensor device and, a step of obtaining, by the sensor device, second image data regarding a second measurement position of the measurement target from the image data, wherein the first measurement position and the second measurement position are measurement positions under the surface within the measurement target and, a step of determining, by the sensor device, a pulse transit time measurement value based on the first image data and the second image data and, a step of providing, by the sensor device, information for identifying the pulse transit time measurement value A method comprising the above steps.

2. The method according to claim 1, wherein the sensor comprises an image sensor of a camera of the sensor device.

3. The method according to claim 1, further comprising a step of determining a blood pressure value using the pulse transit time measurement value.

4. The method according to claim 1, wherein the step of obtaining the first image data and the step of obtaining the second image data are based on a non-contact sensing operation.

5. The method according to claim 1, further comprising a step of determining other measurement values other than the pulse transit time measurement value using the image data.

6. The method according to claim 5, wherein the other measurement values are related to the skin color of the measurement target.

7. The method according to claim 5, wherein the other measurement values are determined using visible range information.

8. The method according to claim 5, wherein the other measurement values include health parameters.

9. The method according to claim 8, wherein the health parameters include at least one of a heart rate measurement value or an SpO2 measurement value.

10. The method according to claim 1, wherein the first image data and the second image data are each associated with a wavelength that penetrates the measurement target to the first measurement position and the second measurement position.

11. A sensor device comprising a sensor, and one or more processors operably coupled to the sensor, wherein the processor collects image data using the sensor, ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ Extract first image data related to the first measurement position of the measurement target from the image data and obtain Extract second image data related to the second measurement position of the measurement target from the image data and obtain Here, the first measurement position and the second measurement position are surface-under measurement positions within the measurement target and Based on the first image data and the second image data, determine a pulse transit time measurement value, and further provide information for identifying the pulse transit time measurement A sensor device configured as such

12. The sensor device according to claim 11, wherein the first image data and the second image data are data based on light generated by the sensor device A sensor device

13. The sensor device according to claim 11, wherein the image data and the second image data are data related to the near-infrared spectrum range A sensor device

14. The sensor device according to claim 11, wherein the one or more processors further acquire additional image data related to one or more other measurement positions, and determine one or more other pulse transit time values based on the additional image data A sensor device configured as such

15. The sensor device according to claim 11, wherein the input of the sensor is configured to be filtered by a spectral filter array A sensor device

16. The sensor device according to claim 15, wherein the first image data is associated with a first wavelength passed to the sensor and the second image data is configured to be associated with a second wavelength passed to the sensor A sensor device

17. A non-transitory computer-readable medium storing instructions, the instructions being such that when one or more instructions are executed by one or more processors of a sensor device cause the one or more processors to collect image data using the sensor obtain first image data related to a first measurement position of a measurement target and second image data related to a second measurement position of the measurement target Here, the first measurement position and the second measurement position are surface-under measurement positions within the measurement target and the first image data and the second image data are obtained from a video stream ​ 、 Based on the first image data and the second image data, determine the pulse transit time measurement value, and further cause the sensor device to provide information for identifying the pulse transit time measurement value configured as follows, a non-transitory computer-readable medium.

18. The non-transitory computer-readable medium according to claim 17, wherein the sensor device includes a smartphone, a non-transitory computer-readable medium.

19. The non-transitory computer-readable medium according to claim 17, wherein when the one or more instructions are executed by the one or more processors, the one or more processors are caused to provide a visual representation of the video stream having information for identifying the pulse transit time measurement or information determined based on the pulse transit time configured as follows, a non-transitory computer-readable medium.

20. The non-transitory computer-readable medium according to claim 17, wherein when the one or more instructions are executed by the one or more processors, the one or more processors are caused to use the video stream to determine another measurement other than the pulse transit time measurement configured as follows, a non-transitory computer-readable medium. ​

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