Sensor device and methods of use

Abstract

The present invention discloses a multi-spectral sensor device, which may include a sensor array comprising a plurality of channels and one or more processors, the one or more processors being configured to: determine that a time-sensitive measurement will be performed, wherein the time-sensitive measurement will be performed using data collected by one or more of the plurality of channels; cause the data to be collected by an appropriate subset of the plurality of channels, wherein the appropriate subset of channels includes the one or more channels; and determine the time-sensitive measurement based on the data.

Description

Technical Field

[0001] This invention relates to a sensor device and a method of using it. Prior Technology

[0002] Multispectral sensing devices can be used to acquire information. For example, the multispectral sensing device can acquire information about a set of electromagnetic frequencies. The multispectral sensing device may include a set of sensing elements (e.g., optical sensors, spectrum sensors, and / or image sensors) for acquiring this information. For example, an array of sensing elements can be used to acquire information about multiple frequencies. A particular sensing element in the array of sensing elements may be associated with a filter that constrains and directs the filter toward a frequency range of the particular sensing element. The filter may be associated with a specific bandwidth that corresponds to the width of the filter through a spectral range toward the particular sensing element. Summary of the Invention

[0003] In some possible implementations, a multi-spectral sensor device may include a sensor array comprising a plurality of channels and one or more processors configured to: determine that a time-sensitive measurement will be performed, wherein the time-sensitive measurement will be performed using data collected by one or more of the plurality of channels; cause the data to be collected by an appropriate subset of the plurality of channels, wherein the appropriate subset of channels includes the one or more channels; and determine the time-sensitive measurement based on the data.

[0004] In some possible implementations, a method may include: determining, by means of a multispectral sensor device, that a measurement will be performed, wherein the measurement will be performed using data collected by one or more channels of the plurality of channels of the multispectral sensor device, and wherein the measurement is associated with a time sensitivity; causing, by means of the multispectral sensor device, that the data will be collected by an appropriate subset of the plurality of channels, wherein the appropriate subset of channels includes the one or more channels; and determining the measurement by means of the multispectral sensor device based on the data.

[0005] In some possible implementations, a non-transitory computer-readable medium may store one or more instructions that, when executed by one or more processors of a multispectral sensor device, cause the one or more processors to: determine that a first measurement and a second measurement will be performed, wherein the first measurement is performed using first data collected by one or more first channels of a plurality of channels of the multispectral sensor device, wherein the second measurement is performed using second data collected by one or more second channels of the plurality of channels, and wherein the first measurement is associated with a greater time sensitivity than the second measurement; cause the first data to be collected by an appropriate subset of the plurality of channels, wherein the appropriate subset of channels includes the one or more first channels; cause the second data to be collected, wherein the multispectral sensor device is configured to activate all channels of the plurality of channels so that the second data will be collected; determine the first measurement based on the first data; and determine the second measurement based on the second data. Simple Explanation of the Diagram

[0006] [Figures 1A to 1D] are diagrams providing an overview of the exemplary implementations described herein. [Figure 2] is a diagram illustrating an environment in which the systems and / or methods described herein can be implemented. [Figure 3] is a diagram illustrating components of one or more of the devices in Figure 2. [Figure 4] is a flowchart of an example procedure for processing the region of interest (ROI) for time-sensitive measurements. [Figure 5] is a flowchart of another example procedure for processing the region of interest (ROI) for time-sensitive measurements. Implementation

[0007] The following detailed description of illustrative embodiments is provided with reference to the accompanying drawings. The same reference numerals in different drawings can identify the same or similar elements.

[0008] Frame rates for time-dependent optical measurements, such as those found in health monitoring applications (e.g., heart rate, blood pressure), sometimes range from 250 to 500 samples per second (sps). In multi-spectral sensors utilizing multiple pixel regions of a single image sensor, high readout speeds for the entire sensor can be limited by the maximum data transfer rate achievable in the imaging system. This can be a problem with the image sensor readout architecture and the system bus. High-resolution, high-speed sensors with high bit depth require complex circuitry that increases device cost and size. For sensors with good size, cost, bit depth, and responsiveness, 250 sps at full resolution may not be achievable. In space-constrained consumer electronics applications where size and cost are design considerations, high frame rates at high resolutions with high bit depth can be difficult to achieve.

[0009] The implementation described herein can maintain high resolution, high bit depth, and high frame rate without exceeding the data transfer rate of the imaging system by processing only a region of interest (ROI) from the sensor image. For example, specific time-sensitive spectral channel measurements can be performed at a high frame rate (e.g., at full ROI resolution and / or bit depth). Time-sensitive measurements can be used, for example, to process time-dependent parameters, such as certain health parameters. Full-spectrum sensors operate at a slower rate for measurements requiring the full spectral channel set and / or at an intermediate frame rate for any mix of data parameters that does not exceed the data bus rate of the spectrum analyzer. ROI processing can be performed by the camera's sensor via partial scanning (for charge-coupled device (CCD) devices) or windowing (for complementary metal-oxide-semiconductor (CMOS) devices). By performing ROI processing using partial scans or windowing for time-sensitive or frequently performed measurements, the data bus rate of a multi-spectral sensor can be kept within limits, thus preserving the time dimension of time-sensitive measurements and improving measurement accuracy. Furthermore, some of the implementations described herein can be executed on the chip of the multi-spectral sensor device (e.g., before data is transmitted to the control unit), reducing latency and improving the time measurement accuracy.

[0010] Figures 1A to 1D are diagrams outlining the exemplary embodiment 100 described herein. As shown in Figure 1A, exemplary embodiment 100 can be performed by a multi-spectral sensing device, such as a multi-spectral sensing device using a CMOS device or a multi-spectral sensing device using a CCD (e.g., multi-spectral sensing device 220 of Figure 2). In some embodiments, certain operations of exemplary embodiment 100 can be performed by another device of the environment 200 of Figure 2 (such as a control device 210).

[0011] As shown in Figure 1, the multi-spectral sensor device may include a sensor array 105. As shown, the sensor array 105 may include channels 110-1 to 110-64. For example, the sensor array may include multiple sensor elements configured to obtain information about multiple corresponding frequencies. Alternatively, the sensor array may include multiple sensor elements configured to obtain information associated with a single frequency. The sensor elements may correspond to channel 110.

[0012] As shown in Figure 1B and by reference numeral 120, the multispectral sensor device can perform measurements based on region 115. The execution of measurements is described in more detail below in conjunction with Figures 1C and 1D. As shown by reference numeral 125, the multispectral sensor device can perform measurement 1 using channels 10, 11, 18, and 19 of sensor array 105. As further shown, the multispectral sensor device can perform measurement 2 using all channels of the multispectral sensor device. Here, measurement 1 uses four channels, which can be collectively referred to as pixel regions or regions of interest (ROIs). As shown, measurement 2 uses all channels of sensor array 105. In some implementations, measurement 2 can use fewer than all channels of sensor array 105.

[0013] For illustrative purposes, it is assumed that measurement 1 is a time-sensitive measurement, and measurement 2 is not a time-sensitive measurement. As used herein, a time-sensitive measurement may refer to a measurement associated with a threshold frame rate, a threshold data rate, an accurate time measurement for which accuracy is required, and / or the like. A non-time-sensitive measurement may refer to a measurement not associated with a threshold frame rate or data rate, an accurate time measurement not required, and / or the like. In some implementations, time-sensitive sensing may be associated with a specific frame rate and / or resolution that generally exceeds the bus data rate of the multi-spectral sensor device. When the bus data rate is exceeded, data may be queued, thereby losing the time dimension of the data. This can reduce the accuracy of some time-sensitive measurements.

[0014] As shown in Figure 1C and by reference numeral 130, the multispectral sensor device can determine that measurement 1 is a time-sensitive measurement. As further shown, the multispectral sensor device can collect data only for the channels associated with measurement 1 (channels 10, 11, 18, and 19 shown by diagonal lines). In some implementations, the multispectral sensor device can collect data using a ROI window, as described in more detail below. In some implementations, the multispectral sensor device can collect data using a partial scan of sensor array 105, as also described in more detail below.

[0015] In some implementations, such as when the multispectral sensor device includes a CCD-type device, the multispectral sensor device may use partial scans of the sensor array 105 to collect data. For example, a partial scan may be achieved by performing a number of (e.g., sequential) vertical shifts to a readout register and discarding unwanted or unnecessary charges (e.g., unwanted or unnecessary data associated with channels other than channels 10, 11, 18, and 19). Vertical transfer can be performed faster than reading the entire column when not requiring every pixel in the output column, due to the increased frame rate provided by fewer columns output per frame by the sensor. Once the ROI scan for measurement 1 has been completed, the sensor array 105 can operate normally, thereby outputting pixels from the appropriate columns, as described in more detail below in conjunction with Figure 1D.

[0016] In some implementations, such as when the multispectral sensor device includes a CMOS-type device, the multispectral sensor device can use ROI windowing to collect data. For example, for some architectures of CMOS sensors, both vertical and horizontal windowing can be performed. In some implementations, this allows for a corresponding increase in frame rate, as the pixel signal is transmitted in parallel via a set of line amplifiers, then horizontally analog-to-digital converters (A / D) and finally to a high-speed multiplexer that transmits the digitized data off-chip. The integration of parallel on-chip A / D into the CMOS chip allows for high pixel clock speeds with high frame rates.

[0017] In some implementations, using CMOS sensors to open windows can extend beyond a single window to multiple windows by properly addressing the correct columns and rows of interest. With multiple windows or ROIs, multi-spectral sensor devices can improve the sensor output bandwidth for useful information without exceeding the bus data rate. In this way, multi-spectral sensor devices can improve the measurement frequency and accuracy of time-sensitive measurements.

[0018] As shown in Figure 1D and by reference numeral 135, in some implementations, the multispectral sensor device can determine that measurement 2 is not time-sensitive. Therefore, the multispectral sensor device can collect data using the entire sensor array 105 and can determine measurement 2 based on the collected data. For example, the multispectral sensor device can collect data from each channel of the sensor array 105. In some implementations, the multispectral sensor device can collect data from the remaining channels other than channels 10, 11, 18, and / or 19, thus conserving resources that would otherwise be used to collect unnecessary data from channels 10, 11, 18, and / or 19. In some implementations, the multispectral sensor device collects data at full resolution for all channels of the sensor array 105, which makes the determination of non-time-sensitive measurements more accurate.

[0019] As an example of the operation described above in conjunction with Figures 1A to 1D, consider the following scenario: A 64-channel multispectral sensor is achieved by integrating a single multispectral filter onto a pixelated sensor (such as a common silicon CMOS image sensor), serving as a biomonitoring device to measure heart rate, blood pressure, SpO2, blood glucose, hydration, and / or other health parameters. Cardiopulmonary function parameters such as heart rate, blood pressure, and SpO2 may require time-sensitive (e.g., greater than 250 sps) measurements of time-dependent spectral signals in a few wavelengths. Using multispectral ROI windowing technology, data in specific channels corresponding to a few wavelengths can adequately meet time sampling requirements and calculate the necessary measurement speed determination. When the time-sensitive measurement is determined to be complete, the multispectral sensor can perform a full sensor readout, capturing the remaining channels of data from the full readout (e.g., all 64 channels). This information can be used to determine other spectral health parameters that are not time-dependent but may require highly resolved spectral content, such as blood glucose and hydration.

[0020] In this way, multi-spectral ROI windowing technology achieves high resolution, high bit depth, and high frame rate, which would otherwise necessitate a complex architecture that significantly increases device cost and size. For example, other techniques, such as stacking wafers to directly integrate dedicated readout circuitry to each pixel or creating dedicated circuitry for extremely fast data collection, may not be suitable for achieving low cost and high manufacturability. Furthermore, without using ROI technology to discard unnecessary extraneous data, a large amount of data would need to be processed before useful signals can be computed and reports returned to the user, thus disrupting the time-sensitive nature of measurements.

[0021] An example of implementing a two-dimensional sensor array is described herein. However, the implementation described herein can also be applied to a three-dimensional sensor array. For example, the region of interest of this sensor array can be one-dimensional (e.g., a single channel or a row of channels), two-dimensional (e.g., a single layer of channels), or three-dimensional (e.g., two or more layers of one or more channels).

[0022] As indicated above, Figures 1A through 1D are provided only as examples. Other examples are possible and may differ from those described with respect to Figures 1A through 1D.

[0023] Figure 2 is a diagram of an exemplary environment 200 in which the systems and / or methods described herein may be implemented. As shown in Figure 2, environment 200 may include a control device 210, a multi-spectral sensor device 220, and a network 230. The devices in environment 200 may be interconnected via wired connections, wireless connections, or a combination of wired and wireless connections.

[0024] Control device 210 includes one or more devices capable of storing, processing, and / or routing information associated with multispectral sensing. For example, control device 210 may include a server, computer, wearable device, cloud computing device, and / or the like. In some implementations, control device 210 may be associated with a specific multispectral sensor device 220. In some implementations, control device 210 may be associated with multiple multispectral sensor devices 220. In some implementations, control device 210 may receive information from and / or transmit information to another device in environment 100, such as multispectral sensor device 220.

[0025] Multispectral sensing device 220 includes means for performing measurements on light directed toward the multispectral sensing device 220. For example, multispectral sensing device 220 may include an image sensor, a multispectral sensor, and / or the like, which can perform sensor measurements on light directed toward the multispectral sensing device 220. Multispectral sensing device 220 may utilize one or more sensing technologies, such as complementary metal-oxide-semiconductor (CMOS) technology, charge-coupled device (CCD) technology, and / or the like. Multispectral sensing device 220 may include a plurality of sensing elements (e.g., an array of sensing elements referred to as a sensor array), each configured to acquire information. A sensing element may correspond to a channel, such as channel 115 described in FIG. 1A.

[0026] Network 230 includes one or more wired and / or wireless networks. For example, network 230 may include cellular networks (e.g., long-term evolution (LTE) networks, code division multiple access (CDMA) networks, 3G networks, 4G networks, 5G networks, another type of next-generation network, etc.), public land mobile networks (PFMN), local area networks (LANs), wide area networks (WANs), metropolitan area networks (MANs), telephone networks (e.g., public switched telephone networks (PSTNs)), private networks, special-purpose networks, corporate intranets, the Internet, fiber optic networks, cloud computing networks, or similar networks, and / or combinations of these or other types of networks.

[0027] The number and configuration of the devices and networks shown in Figure 2 are provided as an example. In practice, compared to the devices and / or networks shown in Figure 2, there may be additional devices and / or networks, fewer devices and / or networks, different devices and / or networks, or devices and / or networks configured in different ways. Furthermore, two or more devices shown in Figure 2 may be implemented within a single device, or the single device shown in Figure 2 may be implemented as multiple distributed devices. Alternatively or concurrently, the 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.

[0028] Figure 3 is a diagram illustrating the components of device 300. Device 300 may correspond to control device 210 and / or multi-spectral sensor device 220. In some implementations, control device 210 and / or multi-spectral sensor device 220 may include one or more devices 300 and / or one or more components of device 300. As shown in Figure 3, device 300 may include bus 310, processor 320, memory 330, storage component 340, input component 350, output component 360, and communication interface 370.

[0029] Bus 310 includes components that enable communication between components of device 300. Processor 320 is implemented in hardware, firmware, or a combination of hardware and software. Processor 320 may take the form of a central processing unit (CPU), graphics processing unit (GPU), accelerated processing unit (APU), microprocessor, microcontroller, field-programmable gate array (FPGA), application-specific integrated circuit (ASIC), or another type of processing component. In some implementations, processor 320 includes one or more processors that can be programmed to perform functions. Memory 330 includes random access memory (RAM), read-only memory (ROM), and / or another type of dynamic or static storage device (e.g., flash memory, magnetic memory, and / or optical memory) that stores information and / or instructions for use by processor 320.

[0030] Storage component 340 stores information and / or software related to the operation and use of device 300. For example, storage component 340 may include hard disks (e.g., magnetic disks, optical disks, magneto-optical disks and / or solid-state disks), optical disks (CDs), digital multifunction discs (DVDs), floppy disks, cassettes, magnetic tapes and / or other types of non-transitory computer-readable media along with corresponding drives.

[0031] Input component 350 includes components that allow device 300 to receive information, such as via user input devices (e.g., touchscreen display, keyboard, keypad, mouse, buttons, switches, and / or microphone). Alternatively, input component 350 may include sensors for sensing information (e.g., a Global Positioning System (GPS) component, accelerometer, gyroscope, and / or actuator). Output component 360 includes components that provide information output from device 300 (e.g., a display, speaker, and / or one or more light-emitting diodes (LEDs)).

[0032] Communication interface 370 includes transceiver components (e.g., transceivers and / or separate receivers and transmitters) that enable device 300 to communicate with other devices, such as via wired connections, wireless connections, or a combination of wired and wireless connections. Communication interface 370 may allow device 300 to receive information from another device and / or provide information to another device. For example, communication interface 370 may 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, or the like.

[0033] Device 300 can execute one or more programs described herein. Device 300 can execute these programs based on processor 320 executing software instructions stored in non-transitory computer-readable media (such as memory 330 and / or storage component 340). Computer-readable media are defined herein as non-transitory memory devices. Memory devices include memory space within a single physical storage device or memory space distributed across multiple physical storage devices.

[0034] Software instructions may be read from another computer-readable medium or from another device via communication interface 370 into memory 330 and / or storage component 340. Upon execution, the software instructions stored in memory 330 and / or storage component 340 may cause processor 320 to execute one or more programs described herein. Alternatively or additionally, hardware circuitry may be used in place of or in combination with software instructions to execute one or more programs described herein. Therefore, the implementations described herein are not limited to any particular combination of hardware circuitry and software.

[0035] The number and configuration of components shown in Figure 3 are provided as an example. In practice, compared to those shown in Figure 3, device 300 may include additional components, fewer components, different components, or components configured in a different manner. Alternatively, one set of components of device 300 (e.g., one or more components) may perform one or more functions described as being performed by another set of components of device 300.

[0036] Figure 4 is a flowchart of an example procedure 400 for opening a window for multispectral measurement of the ROI. In some implementations, one or more program blocks of Figure 4 may be executed by the multispectral sensor device 220. In some implementations, one or more program blocks of Figure 4 may be executed by another device or another group of devices that are separate from or include the multispectral sensor device 220, such as the control device 210.

[0037] As shown in Figure 4, program 400 may include determining that a time-sensitive measurement will be performed, wherein the time-sensitive measurement will be performed using data collected from one or more of a plurality of channels (block 410). For example, multi-spectral sensor device 220 (e.g., using processor 320 and / or the like) may determine that a time-sensitive measurement will be performed. The time-sensitive measurement may be performed using data collected from one or more channels of a sensor array (e.g., a region of interest associated with the time-sensitive measurement). In some implementations, the measurement may be determined automatically by multi-spectral sensor device 220 (e.g., based on feedback). In some implementations, the measurement may be configured (e.g., a particular measurement requires 250 sps).

[0038] As further illustrated in Figure 4, procedure 400 may include collecting data from an appropriate subset of a plurality of channels, wherein the appropriate subset of channels includes one or more channels (block 420). For example, multispectral sensor device 220 (e.g., using processor 320) may collect data from an appropriate subset of a plurality of channels (e.g., fewer than all channels). The appropriate subset of channels may include one or more channels in the region of interest. In some implementations, multispectral sensor device 220 may collect data using an ROI windowing method or a partial scan method, as described in more detail elsewhere herein.

[0039] As further illustrated in Figure 4, program 400 may include determining time-sensitive measurements based on data (block 430). For example, multi-spectral sensor device 220 (e.g., using processor 320) may determine time-sensitive measurements based on data. In this way, the data bus rate of multi-spectral sensor device 220 does not exceed the rate used for time-sensitive measurements. In some implementations, multi-spectral sensor device 220 may provide data to another device (e.g., control device 210) that can determine the data.

[0040] Program 400 may include additional implementations, such as any single implementation or any combination of implementations described below and / or in conjunction with one or more other programs described elsewhere herein.

[0041] In some implementations, the appropriate channel subset includes only one or more channels. In some implementations, the appropriate channel subset includes one or more columns of sensors, wherein one or more columns include one or more channels. In some implementations, the multi-spectral sensor device 220 may discard data other than that collected by one or more channels. In some implementations, the multi-spectral sensor device 220 may cause data to be collected by the appropriate channel subset based on the time sensitivity of a time-sensitive measurement. In some implementations, the time-sensitive measurement is the first measurement, and the data is the first data. The multi-spectral sensor device 220 may determine that a second measurement will be performed, wherein the second measurement is associated with a less stringent time sensitivity than the first measurement; cause the second data to be collected by all channels of the plurality of channels; and perform the second measurement using at least a portion of the second data. In some implementations, the multi-spectral sensor device may perform multiple iterations of the first and second measurements, wherein the first measurement is performed more frequently than the second measurement. In some implementations, the first measurement is determined with a lower latency than the second measurement. In some implementations, the first measurement is performed more frequently than the second measurement.

[0042] In some implementations, the sensor array includes at least one of a charge-coupled device or a complementary metal-oxide-semiconductor device. In some implementations, the time-sensitive measurement is for biological or medical values.

[0043] In some embodiments, the multi-spectral sensor device 220 includes a complementary metal-oxide-semiconductor (CMOS) device. The multi-spectral sensor device 220 can perform vertical and horizontal windowing, allowing data to be collected using only one or more channels. In some embodiments, the multi-spectral sensor device 220 includes a charge-coupled device (CCD). The multi-spectral sensor device can perform one or more consecutive vertical shifts to a readout register and discard data other than the data to be collected. In some embodiments, specific data from one or more columns is not associated with one or more channels, and this specific data is discarded for determination measurement.

[0044] Although Figure 4 illustrates an example block of program 400, in some implementations, program 400 may include additional blocks, fewer blocks, different blocks, or blocks configured differently compared to those depicted in Figure 4. Alternatively, two or more blocks of program 400 may be executed in parallel.

[0045] Figure 5 is a flowchart of an example procedure 500 for opening a window for multispectral measurement of the ROI. In some implementations, one or more program blocks of Figure 5 may be executed by the multispectral sensor device 220. In some implementations, one or more program blocks of Figure 5 may be executed by another device or another group of devices that are separate from or include the multispectral sensor device 220, such as the control device 210.

[0046] As shown in Figure 5, program 500 may include determining that a first measurement and a second measurement will be performed, wherein the first measurement is associated with a greater time sensitivity than the second measurement (block 510). For example, multi-spectral sensor device 220 (e.g., using processor 320) may determine that the first measurement and the second measurement will be performed. The first measurement may be associated with a greater time sensitivity than the second measurement. In some implementations, the first measurement may be associated with a higher data rate, frame rate, and / or resolution than the second measurement.

[0047] As further illustrated in Figure 5, procedure 500 may include collecting first data from an appropriate subset of a plurality of channels, wherein the appropriate subset of channels includes one or more first channels (block 520). For example, multi-spectral sensor device 220 (e.g., using processor 320) may enable the first data to be collected from an appropriate subset of a plurality of channels. The appropriate subset of channels may include regions of interest corresponding to one or more first channels.

[0048] As further illustrated in Figure 5, program 500 may include enabling the collection of second data, wherein the multi-spectral sensor device 220 is configured to activate all channels of a plurality of channels to enable the collection of second data (block 530). For example, the multi-spectral sensor device 220 (e.g., using processor 320) may enable the collection of second data. The multi-spectral sensor device 220 may activate all channels of a plurality of channels to enable the collection of second data.

[0049] As further illustrated in Figure 5, program 500 may include determining a first measurement based on first data (block 540). For example, multi-spectral sensor device 220 (e.g., using processor 320) may determine the first measurement based on the first data. In some implementations, multi-spectral sensor device 220 may provide the first data to another device (e.g., control device 210) for determining the first measurement.

[0050] As further illustrated in Figure 5, program 500 may include determining a second measurement based on second data (block 550). For example, multi-spectral sensor device 220 (e.g., using processor 320) may determine the second measurement based on the second data. In some implementations, multi-spectral sensor device 220 may provide the second data to another device (e.g., control device 210) for determining the second measurement.

[0051] Program 500 may include additional implementations, such as any single implementation or any combination of implementations described below and / or in conjunction with one or more other programs described elsewhere herein.

[0052] In some embodiments, the multi-spectral sensor device 220 may perform multiple iterations of the first and second measurements, wherein the first measurement is performed more frequently than the second measurement. In some embodiments, the first measurement is determined with a lower latency than the second measurement. In some embodiments, the multi-spectral sensor device includes a charge-coupled device or a complementary metal-oxide-semiconductor device.

[0053] Although Figure 5 illustrates an example block of program 500, in some implementations, program 500 may include additional blocks, fewer blocks, different blocks, or blocks configured differently compared to those depicted in Figure 5. Alternatively, two or more blocks of program 500 may be executed in parallel.

[0054] In this way, multi-spectral ROI windowing technology achieves high resolution, high bit depth, and high frame rate, which would otherwise necessitate a complex architecture that significantly increases device cost and size. For example, other techniques, such as stacking wafers to directly integrate dedicated readout circuitry to each pixel or creating dedicated circuitry for extremely fast data collection, may not be suitable for achieving low cost and high manufacturability. Furthermore, without using ROI technology to discard unnecessary extraneous data, a large amount of data would need to be processed before useful signals can be computed and reports returned to the user, thus disrupting the time-sensitive nature of measurements.

[0055] The foregoing descriptions are provided for illustrative purposes only and are not intended to be exhaustive or to limit implementation to the precise form described. Modifications and variations are possible based on the foregoing descriptions or may be derived from practical application.

[0056] As used herein, the term "component" is intended to be interpreted broadly as hardware, firmware, and / or a combination of hardware and software.

[0057] This document describes some implementations in conjunction with threshold values. As used herein, a threshold value can refer to a value that is greater than, higher than, greater than or equal to, less than, less than, lower than, less than or equal to, equal to, and / or similar.

[0058] It will be apparent that the systems and / or methods described herein can be implemented in various forms, including hardware, firmware, or a combination of hardware and software. The actual dedicated control hardware or software code used to implement such systems and / or methods is not a limitation on implementation. Therefore, since the operation and behavior of systems and / or methods are described herein without reference to any specific software code, it should be understood that software and hardware can be designed to implement systems and / or methods based on the descriptions herein.

[0059] Although there are specific combinations of features described in the claims and / or in this specification, such combinations are not intended to limit the possible implementation of the description. In fact, many of these features can be combined in ways not specifically described in the claims and / or in this specification. Although each item listed below may be directly attached to only one claim, the possible implementation of the description includes each item in combination with each other claim in the claims.

[0060] The elements, actions, or instructions used herein should not be interpreted as essential or indispensable unless so explicitly stated. Furthermore, as used herein, the quantifier "a / an" is intended to include one or more items and is used interchangeably with "one or more". Additionally, 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 is used interchangeably with "one or more". The term "a" or similar language is used when only one item is intended. Furthermore, as used herein, the term "has / have / having" or its equivalents are intended to be open-ended terms. Furthermore, unless otherwise explicitly stated, the phrase "based on" is intended to mean "at least partially based on".

[0061] Furthermore, this record includes embodiments based on the following terms: Clause 1: A multi-spectral sensor device comprising: A sensor array comprising a plurality of channels; and One or more processors are configured to: determine that a time-sensitive measurement will be performed, wherein the time-sensitive measurement will be performed using data collected from one or more of the plurality of channels; This ensures that the data will be collected from an appropriate subset of the plurality of channels, wherein the appropriate subset of channels includes one or more channels; and Based on this data, this time-sensitive measurement was determined. Clause 2: A multi-spectral sensor device as described in Clause 1, wherein the appropriate subset of channels includes only the one or more channels. Clause 3: A multi-spectral sensor device as described in Clause 1, wherein the appropriate subset of channels comprises one or more columns of sensors, wherein the one or more columns comprise the one or more channels. Clause 4: A multi-spectral sensor device as described in Clause 3, wherein the one or more processors are configured to: discard data other than the data collected by the one or more channels. Clause 5: A multi-spectral sensor device as described in Clause 1, wherein the one or more processors, when causing the data to be collected by the appropriate subset of channels, further use the processors to: cause the data to be collected by the appropriate subset of channels based on the time sensitivity of the time-sensitive measurement. Clause 6: A multi-spectral sensor device as described in Clause 1, wherein the time-sensitive measurement is a first measurement and the data is first data; and wherein the one or more processors are configured to: determine that a second measurement will be performed, wherein the second measurement is associated with a less stringent time sensitivity compared to the first measurement; such that the second data will be collected by all channels of the plurality of channels; and perform the second measurement using at least a portion of the second data. Clause 7: A multi-spectral sensor device as described in Clause 6, wherein the one or more processors are further configured to: perform multiple iterations of the first measurement and the second measurement, wherein the first measurement is performed more frequently than the second measurement. Clause 8: A multi-spectral sensor device as described in Clause 1, wherein the sensor array includes at least one of a charge-coupled device or a complementary metal-oxide-semiconductor device. Clause 9: A multi-spectral sensor device as described in Clause 1, wherein the time-sensitive measurement is a first measurement and the data is first data; and wherein the one or more processors are configured to: determine that a second measurement will be performed, wherein the second measurement is associated with a more stringent time sensitivity compared to the first measurement; such that the second data will be collected from a set of channels in the plurality of channels, the set of channels including fewer channels compared to the appropriate subset of channels; and perform the second measurement using at least a portion of the second data. Clause 10: A method comprising: The measurement to be performed is determined by a multi-spectral sensor device, wherein the measurement will be performed using data collected from one or more channels of a plurality of channels of the multi-spectral sensor device, and wherein the measurement is associated with time sensitivity; The multi-spectral sensor device enables the data to be collected from an appropriate subset of the plurality of channels, wherein the appropriate subset of channels includes one or more channels; and The measurement is determined based on the data using the multi-spectral sensor device. Clause 11: The method of Clause 10, wherein the multi-spectral sensor device includes a complementary metal-oxide-semiconductor device, and wherein causing the data to be collected further includes performing vertical and horizontal windowing such that the data is collected only by the one or more channels. Clause 12: The method of Clause 10, wherein the multi-spectral sensor device includes a charge coupling device, wherein causing the data to be collected further includes performing one or more successive vertical shifts to a readout register; and discarding data other than the data to be collected. Clause 13: The method of Clause 12, wherein specific data from the one or more columns is not associated with the one or more channels, and wherein the specific data is discarded for the purpose of determining the measurement. Clause 14: The method of Clause 10, wherein the measurement is a first measurement and the data is first data; and wherein the method further comprises: determining that a second measurement will be performed, wherein the second measurement is associated with a less stringent time sensitivity compared to the first measurement; such that the second data will be collected by all of the plurality of channels; and performing the second measurement using at least a portion of the second data. Clause 15: The method of Clause 14, wherein the comparison between the first measurement and the second measurement is determined by the lower latency. Clause 16: The method of Clause 14, wherein multiple iterations of the first measurement and the second measurement are performed, and wherein the first measurement is performed more frequently than the second measurement. Clause 17: A non-transitory computer-readable medium for storing instructions, the instructions comprising: One or more instructions, when executed by one or more processors of a multi-spectral sensor device, cause the one or more processors to perform the following operations: determine that a first measurement and a second measurement will be performed, wherein the first measurement will be performed using first data collected by one or more first channels of a plurality of channels of the multi-spectral sensor device, wherein the second measurement will be performed using second data collected by one or more second channels of the plurality of channels, and wherein the comparison between the first measurement and the second measurement is associated with a greater time sensitivity; This ensures that the first data will be collected by an appropriate subset of the plurality of channels, wherein the appropriate subset of channels includes one or more of the first channels; This allows the second data to be collected, wherein the multi-spectral sensor device is configured to activate all of the plurality of channels to allow the second data to be collected; The first measurement is determined based on the first data; and The second measurement is determined based on the second data. Clause 18: Non-transitory computer-readable media as in Clause 17, wherein the one or more instructions, when executed by the one or more processors, further cause the one or more processors to: perform multiple iterations of the first measurement and the second measurement, wherein the first measurement is performed more frequently than the second measurement. Clause 19: Non-transitory computer-readable media as in Clause 17, wherein the first measurement is compared with the second measurement based on the lower latency. Clause 20: Non-transitory computer-readable media as in Clause 17, wherein the multi-spectral sensing device includes a charge-coupled device or a complementary metal-oxide-semiconductor device.

[0062] 100: Implementation / Environment 105: Sensor Array 110, 110-1 to 110-64: Channels 115: Area / Passage 115-1, 115-2: District 120, 125, 130, 135: Reference numbers 200: Environment 210: Control device 220: Multi-spectral sensor device 230: Internet 300: Device 310: Busbar 320: Processor 330: Memory 340: Storage Components 350: Input Component 360: Output Component 370: Communication Interface

Claims

1. A biomonitoring device (220) configured to measure health parameters, the biomonitoring device (220) comprising: A sensor array (105) and at least one processor (320); the sensor array (105) includes a plurality of sensor elements (110); and the at least one processor (320) is configured to: determine that a cardiopulmonary function parameter measurement will be performed, wherein the cardiopulmonary function parameter measurement requires a time-sensitive measurement of a time-dependent spectral signal in several wavelengths; collect first data from an appropriate subset (10, 11, 18, 19) of the plurality of sensor elements (110) of the sensor array (105) corresponding to the several wavelengths of the cardiopulmonary function parameter; determine that other spectral health parameter measurements will be performed; collect second data from the remaining sensor elements other than the appropriate subset (10, 11, 18, 19) of the plurality of sensor elements (110); and obtain the cardiopulmonary function parameter measurement based on the first data; The other spectral health parameter measurement is obtained based on the second data; and multiple iterations of the cardiopulmonary function parameter measurement and the other spectral health parameter measurement are performed, wherein the cardiopulmonary function parameter measurement is performed more frequently than the other spectral health parameter measurement.

2. The biological monitoring device (220) as claimed in claim 1, wherein the appropriate subset of sensor elements (10, 11, 18, 19) comprises only one or more sensor elements (10, 11, 18, 19) or one or more columns of sensors, wherein the one or more columns of sensors comprise the one or more sensor elements (10, 11, 18, 19).

3. The biological monitoring device (220) as claimed in claim 2, wherein the at least one processor (320) is configured to: discard data other than the first data collected from the appropriate subset of sensor elements (10, 11, 18, 19).

4. The biological monitoring device (220) as claimed in claim 1, wherein the sensor array (105) comprises at least one of a charge-coupled device or a complementary metal-oxide-semiconductor device.

5. A method of using a sensor device, comprising: The biological monitoring device (220) configured to measure health parameters determines that a cardiopulmonary function parameter measurement will be performed, wherein the cardiopulmonary function parameter measurement requires a time-sensitive measurement of a time-dependent spectral signal in several wavelengths; the biological monitoring device (220) collects first data from a subset (10, 11, 18, 19) of appropriate sensor elements (110) of a plurality of sensor elements (105) corresponding to the several wavelengths of the cardiopulmonary function parameter measurement; the biological monitoring device (220) determines that other spectral health parameter measurements will be performed; the biological monitoring device (220) collects second data from the remaining sensor elements other than the appropriate subset (10, 11, 18, 19) of the plurality of sensor elements (110); The biological monitoring device (220) obtains the cardiopulmonary function parameter measurement based on the first data; and the biological monitoring device (220) obtains the other spectral health parameter measurement based on the second data; wherein the cardiopulmonary function parameter measurement is determined with a lower latency compared to the other spectral health parameter measurement.

6. The method of claim 5, wherein the biomonitoring device (220) comprises a complementary metal-oxide-semiconductor device, and collecting the first data further comprises performing vertical and horizontal windowing such that the first data is collected only by the one or more elements (100), or wherein the biomonitoring device (220) comprises a charge-coupled device, and collecting the first data further comprises: performing one or more consecutive vertical shifts to a readout register; and discarding data other than the first data to be collected.

7. The method of claim 5, wherein the cardiopulmonary function parameter measurement and the other spectral health parameter measurement are performed in multiple iterations, and wherein the cardiopulmonary function parameter measurement is performed more frequently than the other spectral health parameter measurement.

8. A non-transitory computer-readable medium for storing instructions, the instructions comprising: One or more instructions, when executed by at least one processor (320) of the sensing device, cause the at least one processor (320) to: perform the method as defined in any one of claims 5 to 7.

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