Blood oxygen saturation measurement methods and devices, electronic equipment and storage media

Abstract

This application provides a method, apparatus, electronic device, and storage medium for measuring blood oxygen saturation, belonging to the field of blood oxygen detection. The method is applied to a blood oxygen saturation measuring device, which includes a red light source, an infrared light source, and a photodetector. The method includes: acquiring the distance between the photodetector and the red light source to obtain a red light distance; acquiring the distance between the photodetector and the infrared light source to obtain an infrared light distance; performing photoelectric detection on the red and infrared light sources based on the photodetector to obtain blood oxygen characteristic values; correcting the blood oxygen characteristic values ​​based on the red and infrared light distances to obtain corrected characteristic values; and performing a lookup operation on a preset blood oxygen mapping table based on the corrected characteristic values ​​to obtain blood oxygen saturation. This application embodiment can accurately measure blood oxygen saturation even when the physical distributions of the red and infrared light sources are inconsistent.

Description

Technical Field

[0001] This application relates to the field of blood oxygen detection, and more particularly to a method and apparatus for measuring blood oxygen saturation, an electronic device, and a storage medium. Background Technology

[0002] In traditional pulse oximetry module detection equipment, the red light source and the infrared light source are usually designed to be as close as possible in physical layout, so that the geometric conditions when the two wavelengths reach the same photodetector are as consistent as possible. This can avoid systematic errors introduced due to inconsistent geometric paths.

[0003] However, in size-constrained wearable devices such as smart rings, the red and infrared light sources are spatially separated due to factors such as power consumption, heat dissipation, and device layout space. When the physical layout of the red and infrared light sources is separate, differences arise in physical quantities such as the average optical path length, scattering distribution, and attenuation degree of the two light sources in the tissue, ultimately leading to errors in the measured blood oxygen saturation. Therefore, accurately measuring blood oxygen saturation under conditions of inconsistent physical distribution of the red and infrared light sources has become an urgent problem to be solved. Summary of the Invention

[0004] The main objective of this application is to provide a method, device, electronic equipment, and storage medium for measuring blood oxygen saturation, aiming to accurately measure blood oxygen saturation even when the physical distributions of red and infrared light sources are inconsistent.

[0005] To achieve the above objectives, a first aspect of this application provides a method for measuring blood oxygen saturation, applied to a blood oxygen saturation measuring device, the blood oxygen saturation measuring device including a red light source, an infrared light source, and a photodetector, the method comprising: In some embodiments, the distance between the photodetector and the red light source is obtained to obtain the red light distance, and the distance between the photodetector and the infrared light source is obtained to obtain the infrared light distance; Based on the photodetector, photoelectric detection is performed on the red light source and the infrared light source to obtain blood oxygen characteristic values; Based on the red light distance and the infrared light distance, the blood oxygen characteristic value is corrected to obtain the corrected characteristic value; Based on the corrected feature value, a lookup process is performed on the preset blood oxygen mapping table to obtain the blood oxygen saturation.

[0006] In some embodiments, the step of performing photoelectric detection on the red light source and the infrared light source based on the photodetector to obtain blood oxygen characteristic values ​​includes: The red light source is photoelectrically detected using the photodetector to obtain red light characteristic values. The infrared light source is photoelectrically detected using the photodetector to obtain infrared light characteristic values. The blood oxygen characteristic value is obtained by calculating the ratio between the red light characteristic value and the infrared light characteristic value.

[0007] In some embodiments, the step of correcting the blood oxygen characteristic value based on the red light distance and the infrared light distance to obtain a corrected characteristic value includes: The distance difference is calculated by comparing the red light distance and the infrared light distance. The compensation factor is calculated based on the difference between the distance difference and the preset equivalent attenuation coefficient. The blood oxygen characteristic value is corrected according to the compensation factor to obtain the corrected characteristic value.

[0008] In some embodiments, the blood oxygen saturation measuring device includes at least two of the aforementioned photodetectors, and after correcting the blood oxygen characteristic value based on the red light distance and the infrared light distance to obtain the corrected characteristic value, it further includes: Outlier removal is performed on each of the modified feature values ​​to obtain the cluster feature value; The weighted average of each of the aforementioned cluster eigenvalues ​​is used to obtain the weighted eigenvalue; The weighted eigenvalues ​​are used as the corrected eigenvalues.

[0009] In some embodiments, the outlier removal process for each of the modified feature values ​​to obtain a cluster feature value includes: Obtain the median data of each of the corrected feature values ​​to obtain the feature median; The difference between each of the corrected feature values ​​and the median of the feature is obtained to obtain multiple median absolute deviations; The absolute deviations of the medians are sorted to obtain a sorted sequence; Obtain the median deviation of the median of the sorted sequence; Outlier removal is performed on each of the corrected feature values ​​based on the median deviation and the median feature value to obtain the cluster feature value.

[0010] In some embodiments, after performing a lookup process on a preset blood oxygen mapping table based on the modified feature value to obtain the blood oxygen saturation, the method further includes: Get historical saturation; The confidence level of the blood oxygen saturation is calculated based on the historical saturation to obtain confidence data; Based on the confidence level data, a wearing prompt is output.

[0011] To achieve the above objectives, a second aspect of this application provides a blood oxygen saturation measuring device, applied to a blood oxygen saturation measuring equipment. The blood oxygen saturation measuring equipment includes a red light source, an infrared light source, and a photodetector. The device comprises: The data acquisition module is used to acquire the distance between the photodetector and the red light source to obtain the red light distance, and to acquire the distance between the photodetector and the infrared light source to obtain the infrared light distance; The photoelectric detection module is used to perform photoelectric detection on the red light source and the infrared light source based on the photoelectric detector to obtain blood oxygen characteristic values; The feature value correction module is used to correct the blood oxygen feature value based on the red light distance and the infrared light distance to obtain the corrected feature value; The blood oxygen lookup table module is used to perform a lookup process on a preset blood oxygen mapping table based on the corrected feature value to obtain blood oxygen saturation.

[0012] To achieve the above objectives, a third aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method described in the first aspect.

[0013] To achieve the above objectives, a fourth aspect of the present application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in the first aspect.

[0014] This application proposes a method, apparatus, electronic device, and storage medium for measuring blood oxygen saturation. The method acquires the distance between a photodetector and a red light source to obtain the red light distance, and acquires the distance between the photodetector and an infrared light source to obtain the infrared light distance. Then, it performs photoelectric detection on the red and infrared light sources based on the photodetector to obtain blood oxygen characteristic values. Further, it corrects the blood oxygen characteristic values ​​based on the red and infrared light distances to obtain corrected characteristic values. Finally, it performs a lookup operation on a preset blood oxygen mapping table based on the corrected characteristic values ​​to obtain the blood oxygen saturation. Through the above technical solution, this application, based on the acquired blood oxygen characteristic values, introduces red and infrared light distances to correct the blood oxygen characteristic values, enabling the blood oxygen characteristic values ​​to reflect the differences in propagation paths, scattering, and attenuation caused by inconsistent physical layouts of the red and infrared light sources, thereby reducing measurement errors introduced by the different spatial distances between the two light sources. Attached Figure Description

[0015] Figure 1 This is a flowchart of the blood oxygen saturation measurement method provided in the embodiments of this application; Figure 2 yes Figure 1 The flowchart of step S102 in the document; Figure 3 yes Figure 1 The flowchart of step S103 in the process; Figure 4 This is a flowchart of a blood oxygen saturation measurement method provided in another embodiment of this application; Figure 5 yes Figure 4 The flowchart of step S401 in the process; Figure 6 yes Figure 4 The flowchart of step S402 in the document; Figure 7 This is a flowchart of a blood oxygen saturation measurement method provided in another embodiment of this application; Figure 8 This is a schematic diagram of the blood oxygen saturation measuring device provided in the embodiments of this application; Figure 9 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application; Figure 10 This is a schematic diagram of the blood oxygen saturation measuring device provided in the embodiments of this application; Figure 11 This is a schematic diagram of the blood oxygen saturation measurement module provided in an embodiment of this application; Figure 12 This is a distance diagram provided in an embodiment of this application; Figure 13 This is a comparison chart of R values ​​provided in the embodiments of this application. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0017] It should be noted that although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0019] In traditional pulse oximetry module detection equipment, the red light source and the infrared light source are usually designed to be as close as possible in physical layout, so that the geometric conditions when the two wavelengths reach the same photodetector are as consistent as possible. This can avoid systematic errors introduced due to inconsistent geometric paths.

[0020] However, in size-constrained wearable devices such as smart rings, the red and infrared light sources are spatially separated due to factors such as power consumption, heat dissipation, and device layout space. When the physical layout of the red and infrared light sources is separate, differences arise in physical quantities such as the average optical path length, scattering distribution, and attenuation degree of the two light sources in the tissue, ultimately leading to errors in the measured blood oxygen saturation. Therefore, accurately measuring blood oxygen saturation under conditions of inconsistent physical distribution of the red and infrared light sources has become an urgent problem to be solved.

[0021] Based on this, embodiments of this application provide a method and apparatus for measuring blood oxygen saturation, an electronic device and a storage medium, which aim to accurately measure blood oxygen saturation when the physical distribution of red light source and infrared light source is inconsistent.

[0022] This application provides a method, apparatus, electronic device, and storage medium for measuring blood oxygen saturation, which will be specifically described through the following embodiments. First, the method for measuring blood oxygen saturation in this application embodiment will be described.

[0023] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0024] Foundational technologies for artificial intelligence generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interactive systems, and mechatronics. AI software technologies mainly encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0025] The blood oxygen saturation measurement method provided in this application relates to the field of blood oxygen detection. The blood oxygen saturation measurement method provided in this application can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, etc.; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application implementing the blood oxygen saturation measurement method, but is not limited to the above forms.

[0026] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0027] It should be noted that in all specific embodiments of this application, when processing data related to user identity or characteristics, such as user information, user behavior data, user historical data, and user location information, user permission or consent is obtained first. Furthermore, the collection, use, and processing of this data comply with relevant laws, regulations, and standards. In addition, when embodiments of this application require access to sensitive personal information of users, separate permission or consent from the user is obtained through pop-ups or redirection to confirmation pages. Only after obtaining the user's separate permission or consent is the necessary user-related data required for the proper functioning of these embodiments acquired.

[0028] Figure 1 This is an optional flowchart of the blood oxygen saturation measurement method provided in the embodiments of this application. Figure 1The method may include, but is not limited to, steps S101 to S106, and is applied to a blood oxygen saturation measuring device, which includes a red light source, an infrared light source, and a photodetector.

[0029] Step S101: Obtain the distance between the photodetector and the red light source to obtain the red light distance; obtain the distance between the photodetector and the infrared light source to obtain the infrared light distance. Step S102: Photoelectric detection of red and infrared light sources is performed based on a photodetector to obtain blood oxygen characteristic values; Step S103: Based on the red light distance and infrared light distance, the blood oxygen characteristic value is corrected to obtain the corrected characteristic value; Step S104: Based on the corrected feature value, perform a lookup process on the preset blood oxygen mapping table to obtain the blood oxygen saturation.

[0030] In the embodiments of this application, steps S101 to S104 involve obtaining the distance between the photodetector and the red light source to obtain the red light distance, and obtaining the distance between the photodetector and the infrared light source to obtain the infrared light distance. Then, photoelectric detection is performed on the red and infrared light sources based on the photodetector to obtain blood oxygen characteristic values. Further, the blood oxygen characteristic values ​​are corrected based on the red and infrared light distances to obtain corrected characteristic values. Finally, a lookup table is performed on a preset blood oxygen mapping table based on the corrected characteristic values ​​to obtain blood oxygen saturation. Through the above technical solution, this application, based on the obtained blood oxygen characteristic values, introduces red and infrared light distances to correct the blood oxygen characteristic values, enabling the blood oxygen characteristic values ​​to reflect the differences in propagation paths, scattering, and attenuation caused by inconsistent physical layouts of the red and infrared light sources, thereby reducing measurement errors introduced by the different spatial distances between the two light sources.

[0031] In step S101 of some embodiments, the photodetector is used to receive the light signal propagated through biological tissue and convert the received light signal into a corresponding electrical signal for subsequent extraction of blood oxygen feature values ​​and calculation of blood oxygen saturation. Exemplarily, the photodetector can be any of a photodiode, a phototransistor, or a CMOS optical sensor.

[0032] A red light source is used to emit red light signals within a preset wavelength range, and an infrared light source is used to emit infrared light signals within a preset wavelength range. For example, the red light source can be a red light-emitting diode (LED), and the infrared light source can be an infrared LED. Since red and infrared light have different absorption characteristics in blood, blood oxygen saturation can be calculated based on the photoelectric detection results corresponding to the two wavelengths.

[0033] In some embodiments, the red light distance and infrared light distance can be pre-written into memory during the product manufacturing stage. Specifically, after the terminal device completes device assembly, the red light distance between the photodetector and the red light source, and the infrared light distance between the photodetector and the infrared light source are pre-determined, and the corresponding distance parameters are written into the device's memory. During subsequent device operation, the pre-stored red light distance and infrared light distance can be directly read for subsequent blood oxygen characteristic value correction processing.

[0034] In other embodiments, the red light distance and infrared light distance can also be obtained through real-time measurement. Specifically, the terminal device can detect the relative positions between the photodetector, the red light source, and the infrared light source based on sensors, thereby obtaining the red light distance and infrared light distance in real time.

[0035] Please see Figure 2 In some embodiments, step S102 may include, but is not limited to, steps S201 to S203: Step S201: Perform photoelectric detection on the red light source based on the photodetector to obtain the red light characteristic value; Step S202: Perform photoelectric detection on the infrared light source based on the photodetector to obtain infrared light characteristic values; Step S203: Calculate the ratio of red light characteristic value and infrared light characteristic value to obtain blood oxygen characteristic value.

[0036] Steps S201 to S203, as shown in the embodiments of this application, firstly, photoelectric detection of the red light source is performed based on a photodetector to obtain red light characteristic values; then, photoelectric detection of the infrared light source is performed based on a photodetector to obtain infrared light characteristic values; further, the ratio of the red light characteristic values ​​and the infrared light characteristic values ​​is calculated to obtain blood oxygen characteristic values. Through the above technical solution, this application achieves the detection of blood oxygen characteristic values.

[0037] In some embodiments, the calculation method of blood oxygen characteristic value in steps S201 to S203 is as shown in equation (1): (1), in, The red light alternating current component is used to characterize the pulse wave component in the red light signal, thus obtaining the corresponding red light photoelectric signal. The red light DC component is used to characterize the fundamental light intensity component in the red light signal. After the red light source emits red light into biological tissue, the photodetector samples and detects the transmitted or reflected light to obtain the red light AC component and the red light DC component.

[0038] The infrared light AC component is used to characterize the pulse wave component in infrared light signals. It is the DC component of infrared light, used to characterize the fundamental light intensity component in infrared light signals.

[0039] It is a characteristic value of red light. It is an infrared light characteristic value. It is a characteristic value of blood oxygen.

[0040] Please see Figure 3 In some embodiments, step S103 may include, but is not limited to, steps S301 to S303: Step S301: Calculate the difference between the red light distance and the infrared light distance to obtain the distance difference; Step S302: Calculate the compensation factor based on the difference between the distance difference and the preset equivalent attenuation coefficient; Step S303: Correct the blood oxygen characteristic value according to the compensation factor to obtain the corrected characteristic value.

[0041] Steps S301 to S303, as illustrated in this embodiment, firstly, the difference between the red light distance and the infrared light distance is calculated to obtain a distance difference value; then, a compensation factor is calculated based on the difference between the distance difference value and a preset equivalent attenuation coefficient; further, the blood oxygen characteristic value is corrected based on the compensation factor to obtain a corrected characteristic value. This application first quantifies the distance difference between the red light source and the infrared light source relative to the photodetector to obtain a distance difference value, and then constructs a corresponding compensation factor by combining the equivalent attenuation characteristics of different wavelengths of light in biological tissues. This allows for the compensation and correction of path errors in the blood oxygen characteristic value, enabling the corrected characteristic value to more accurately reflect the true blood oxygenation state.

[0042] In some embodiments, the calculation method of the modified feature value in steps S301 to S303 is as shown in equation (2): (2), in, The difference is the equivalent attenuation coefficient, which is usually 0.15. For red light distance, Infrared distance, As a compensation factor, To correct the eigenvalues, This represents the characteristic value of blood oxygen.

[0043] Please see Figure 4 In some embodiments, after step S103, the procedure may include, but is not limited to, steps S401 to S403, and the blood oxygen saturation measuring device may include at least two photodetectors: Step S401: Remove outliers from each corrected feature value to obtain the cluster feature value. Step S402: Calculate a weighted average of the group characteristics to obtain the weighted characteristic value; Step S403: Use the weighted eigenvalues ​​as the corrected eigenvalues.

[0044] In the embodiments of this application, steps S401 to S403 involve outlier removal for each corrected feature value to obtain a clustered feature value; then, a weighted average is performed on each clustered feature value to obtain a weighted feature value; finally, the weighted feature value is used as the corrected feature value. This application first identifies and removes outlier data from multiple corrected feature values, thereby reducing the impact of abnormal measurement results caused by interference, noise, loose fitting, or instantaneous light signal fluctuations on blood oxygen detection; subsequently, a weighted average is performed on the remaining clustered feature values, allowing different feature values ​​to be fused according to their corresponding weights to obtain a more stable and accurate weighted feature value.

[0045] Please see Figure 5 In some embodiments, step S401 includes, but is not limited to, steps S501 to S505: Step S501: Obtain the median data of each corrected feature value to obtain the feature median; Step S502: Obtain the difference between each corrected eigenvalue and the eigenmedian, and obtain multiple median absolute deviations; Step S503: Sort the absolute deviations of the medians to obtain a sorted sequence; Step S504: Obtain the median deviation of the sorted sequence data; Step S505: Based on the median deviation and the median characteristic, outlier removal is performed on each corrected characteristic value to obtain the cluster characteristic value.

[0046] Steps S501 to S505, as illustrated in this embodiment, firstly, the median data of each corrected feature value is obtained to obtain the feature median; then, the difference between each corrected feature value and the feature median is obtained to obtain multiple median absolute deviations, and the median absolute deviations are sorted to obtain a sorted sequence; further, the median data of the sorted sequence is obtained to obtain the deviation median; finally, outlier removal is performed on each corrected feature value based on the deviation median and the feature median to obtain a clustered feature value. This application, by constructing the median absolute deviation and judging outliers based on the deviation standard, identifies abnormal corrected feature values ​​caused by motion interference, changes in illumination, loose wearing, or instantaneous sampling abnormalities, thereby avoiding abnormal data from participating in subsequent blood oxygen calculations and improving the accuracy of blood oxygen detection.

[0047] In steps S501 to S506 of some embodiments, outlier removal is performed on each corrected feature value using a method based on the absolute deviation of the median.

[0048] For example, suppose the obtained modified feature values ​​are as follows: R1=0.96, R2=1.00, R3=1.03, R4=1.08, R5=1.42.

[0049] After sorting the various modified eigenvalues, we get 0.96, 1.00, 1.03, 1.08, and 1.42.

[0050] The median data was obtained, and the feature median was 1.03.

[0051] The differences between each corrected eigenvalue and the eigenmedian are obtained, resulting in multiple median absolute deviations, which are 0.07, 0.03, 0, 0.05, and 0.39, respectively.

[0052] After sorting, we get 0, 0.03, 0.05, 0.07, 0.39.

[0053] The median deviation was 0.05.

[0054] Outlier removal is performed on each corrected eigenvalue based on the median deviation and the median characteristic, resulting in the cluster eigenvalue as shown in equation (3): (3), Where z is the outlier, R is the corrected eigenvalue, M is the eigenmedian, and MAD is the median deviation.

[0055] For example, for 1.42, its outlier is (0.675)*(1.42-1.03) / 0.05=5.2611. Therefore, 1.42 needs to be removed.

[0056] Please see Figure 6 In some embodiments, step S402 includes, but is not limited to, steps S601 to S603: Step S601: Calculate the signal-to-noise ratio (SNR) of the cluster feature values ​​to obtain the SNR data; Step S602: Perform a geometric mean on the signal-to-noise ratio data to obtain the eigenvalue weights; Step S603: The cluster feature values ​​are weighted and summed according to the feature value weights to obtain the weighted feature values.

[0057] Steps S601 to S603, as illustrated in this embodiment, firstly, the signal-to-noise ratio (SNR) of the group eigenvalues ​​is calculated to obtain SNR data; then, the SNR data is geometrically averaged to obtain eigenvalue weights; further, the group eigenvalues ​​are weighted and summed according to the eigenvalue weights to obtain weighted eigenvalues. Since the group eigenvalues ​​corresponding to photodetectors at different locations may still be affected by factors such as environmental noise, changes in wearing status, and human movement, the stability and reliability of different group eigenvalues ​​vary. This application, by introducing a SNR-based weight allocation mechanism, can increase the contribution of high-quality signals in the weighted calculation and reduce the impact of low-quality signals on the results.

[0058] In step S601 of some embodiments, the signal-to-noise ratio (SNR) is used to characterize the signal quality corresponding to the group eigenvalue. The SNR data includes the red light source SNR and the infrared light source SNR.

[0059] In step S602 of some embodiments, the geometric mean is calculated as shown in equation (4): (4), in, For the first The signal-to-noise ratio of the electrical signal obtained by a photodetector detecting a red light source. For the first The signal-to-noise ratio of the electrical signal obtained by a photodetector detecting an infrared light source. For weighted eigenvalues, that is, the th The signal-to-noise ratio of the electrical signals detected by each photodetector.

[0060] In step S603 of some embodiments, the weighted summation is performed as follows: , For weighted eigenvalues, Let j be the cluster eigenvalue. These are the eigenvalue weights.

[0061] In step S104 of some embodiments, the preset blood oxygen mapping table is established through experimental data. The experimental data is obtained as follows: 20 healthy subjects, aged 20-60 years and with a BMI of 18-30, are selected to undergo a controlled hypoxia experiment (SpO2 range of 70-100%, with a calibration point every 5%). Steady-state data for 60 seconds is collected at each calibration point, the median R value is taken, and then a fitting model is used: SpO2 = a0 + a1·R + a2·R². Table 1 is obtained.

[0062]

[0063] Table 1 Please see Figure 7In some embodiments, after step S104, steps S701 to S703 may also be included, but are not limited to: Step S701: Obtain historical saturation; Step S702: Calculate the confidence level of blood oxygen saturation based on historical saturation to obtain confidence level data; Step S703: Output wearing prompts based on confidence data.

[0064] Steps S701 to S703, as illustrated in this embodiment, obtain historical saturation levels and calculate the confidence level of the current blood oxygen saturation based on these historical levels to obtain confidence data. Then, based on the confidence data, a corresponding wearing prompt is output, enabling the reliability of the current blood oxygen detection result to be evaluated in conjunction with historical test results. Because wearable devices are easily affected by factors such as loosening, positional shifts, finger movement, ambient light interference, or changes in contact pressure during actual wear, the current blood oxygen detection result may fluctuate abnormally. Traditional solutions typically only output a single test result, lacking a mechanism to judge the reliability of the detection, which can easily lead to users obtaining inaccurate blood oxygen data.

[0065] In step S701 of some embodiments, historical saturation represents historical blood oxygen saturation data acquired before the current detection time. In some embodiments, the terminal device may store the corresponding blood oxygen saturation in a historical cache queue after each blood oxygen saturation calculation for use in subsequent confidence calculations. For example, the historical cache queue may store blood oxygen saturation data from the most recent 5, 10, or 30 seconds.

[0066] In step S702 of some embodiments, confidence is calculated based on the degree of dispersion among multiple modified feature values. First, the corresponding coefficient of variation is calculated based on the multiple modified feature values, as shown in equation (5): (5), in, To correct the coefficient of variation corresponding to the eigenvalues, The standard deviation of multiple corrected eigenvalues, It is the mean of multiple corrected eigenvalues.

[0067] Because the coefficient of variation reflects the degree of fluctuation among multiple modified characteristic values, it can be used to assess the reliability of the current blood oxygen saturation. For example: when At that time, it can be determined that the current blood oxygen saturation corresponds to a high confidence level; when At that time, the current blood oxygen saturation level can be determined with medium confidence. when When the level is >15%, the current blood oxygen saturation level can be determined to have a low confidence level.

[0068] In step S703 of some embodiments, for example, when the confidence data indicates that the current blood oxygen saturation corresponds to a high confidence level, a prompt message "Blood oxygen reading is reliable" can be output; when the confidence data indicates that the current blood oxygen saturation corresponds to a medium confidence level, a prompt message "Current blood oxygen reading is for reference only, it is recommended to remeasure after rest" can be output; when the confidence data indicates that the current blood oxygen saturation corresponds to a low confidence level, a prompt message "Current blood oxygen reading is unreliable, please adjust the wearing position and remeasure" can be output.

[0069] Please see Figure 10 The terminal device is a smart ring, which contains a light source component and a photoelectric detection component. The light source component includes a red light source and an infrared light source, and the photoelectric detection component includes a first photoelectric detector PD1 and a second photoelectric detector PD2.

[0070] For example, the red light source and the infrared light source can be integrated into the same LED package device. For instance, the SFH7018B device can be used, which includes both red and infrared light, wherein the red light corresponds to a wavelength of approximately 660 nm, the infrared light corresponds to a wavelength of approximately 940 nm, and the distance between the two is approximately 0.6 mm.

[0071] Furthermore, the first photodetector PD1 and the second photodetector PD2 can be symmetrically distributed on both sides of the red light source and the infrared light source. For example, the first photodetector PD1 and the second photodetector PD2 can be SFH 2707H photodetectors. The terminal device may also include an analog front-end (AFE) and a controller MCU; for example, the AFE can be a GH3310, and the MCU can be an Apollo330B.

[0072] In this embodiment, since there is a physical distance between red light and infrared light, the distance between the red light source and different photodetectors is different from the distance between the infrared light source and different photodetectors.

[0073] The red light distance between the red light source and the first photodetector PD1 is 3.15 mm, the infrared light distance between the infrared light source and the first photodetector PD1 is 3.45 mm, the red light distance between the red light source and the second photodetector PD2 is 3.20 mm, and the infrared light distance between the infrared light source and the second photodetector PD2 is 3.50 mm.

[0074] The first blood oxygen characteristic value can be calculated based on the red light characteristic value and the infrared light characteristic value corresponding to the first photodetector, respectively. Based on the red light characteristic value and infrared light characteristic value corresponding to the second photodetector, the second blood oxygen characteristic value is calculated. .

[0075] Because the distance for red light differs from that for infrared light, the first and second blood oxygen saturation characteristic values ​​can be corrected separately. For example, the correction method is as follows: Correspondingly, we can obtain: Similarly, we obtain ,in and These are the first and second modified eigenvalues, respectively.

[0076] Furthermore, the signal-to-noise ratio corresponding to the first corrected eigenvalue can be used as a basis. and the signal-to-noise ratio corresponding to the second corrected eigenvalue. Multiple modified eigenvalues ​​are weighted and fused to obtain weighted eigenvalues. Finally, blood oxygen saturation can be obtained by looking up a table based on the weighted eigenvalues.

[0077] In this embodiment, by compensating for and correcting the difference in propagation path caused by the inconsistency between the red light distance and the infrared light distance, and by combining a weighted fusion method with multiple photodetectors, the accuracy of the correspondence between blood oxygen characteristic values ​​and the actual blood oxygen state can be improved.

[0078] The experimental results show that, based on a comparative test with a pulse oximeter using 20 subjects, the root mean square error (RMSE) of blood oxygen detection after compensation in this application is approximately 1.3%, while the RMSE without compensation is approximately 3.8%, indicating that this application can effectively improve the accuracy of blood oxygen detection in smart ring scenarios.

[0079] Please see Figure 11 In some embodiments, such as Figure 2 As shown, the terminal device can calculate blood oxygen saturation based on cross-LED pairing and compensate and correct the blood oxygen characteristic value in conjunction with the SDS correction module.

[0080] Specifically, after the red light source emits a red light signal, the photodetector collects the corresponding red light PPG signal to obtain the red light AC component. and the DC component of red light After an infrared light source emits an infrared light signal, a photodetector collects the corresponding infrared light PPG signal to obtain the infrared light AC component. and the DC component of infrared light .

[0081] Furthermore, the original blood oxygenation characteristic value can be obtained by calculating the ratios of the red light AC component, the red light DC component, the infrared light AC component, and the infrared light DC component. The calculation method is shown in (6): (6), Because the positions of the light sources corresponding to red and infrared light sources are different, the distance of red light is... Distance from infrared light There are differences. Correspondingly, the red light distance and infrared light distance can be input into the SDS correction module to correct the original blood oxygen characteristic values. Perform eigenvalue correction to obtain corrected eigenvalues. .

[0082] Finally, it is possible to base the modified eigenvalues The final blood oxygen saturation is obtained by performing a lookup operation on the preset mapping table.

[0083] In this embodiment, by introducing an SDS correction module, the propagation difference caused by the inconsistency between the red light path and the infrared light path is compensated, thereby improving the accuracy of the correspondence between blood oxygen characteristic values ​​and the true blood oxygen state, and improving the accuracy of blood oxygen saturation detection results.

[0084] Please see Figure 12 Since the red light source LED-A and the infrared light source LED-B are located on opposite sides of the photodetector PD, the distance of the red light is... Distance from infrared light There are differences. For example, the distance for red light is approximately 3.5 mm, and the distance for infrared light is approximately 4.2 mm.

[0085] Please see Figure 13 After correction, the R value in the normal SpO2 range on the X-axis is greater than the uncorrected R value.

[0086] Please see Figure 8 This application also provides a blood oxygen saturation measuring device, applied to a blood oxygen saturation measuring equipment. The blood oxygen saturation measuring equipment includes a red light source, an infrared light source, and a photodetector, and can realize the above-mentioned blood oxygen saturation measurement method. The device includes: The data acquisition module 801 is used to acquire the distance between the photodetector and the red light source to obtain the red light distance, and to acquire the distance between the photodetector and the infrared light source to obtain the infrared light distance; The photoelectric detection module 802 is used to perform photoelectric detection on red and infrared light sources based on a photoelectric detector to obtain blood oxygen characteristic values. The feature value correction module 803 is used to correct the blood oxygen feature value based on the red light distance and the infrared light distance to obtain the corrected feature value. The blood oxygen lookup module 804 is used to perform lookup processing on a preset blood oxygen mapping table based on the corrected feature value to obtain blood oxygen saturation.

[0087] The specific implementation of this blood oxygen saturation measuring device is basically the same as the specific implementation of the blood oxygen saturation measuring method described above, and will not be repeated here.

[0088] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described blood oxygen saturation measurement method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0089] Please see Figure 9 , Figure 9 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 901 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 902 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called and executed by the processor 901 using the blood oxygen saturation measurement method of the embodiments of this application. The 903 input / output interface is used to implement information input and output. The communication interface 904 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 905 transmits information between various components of the device (e.g., processor 901, memory 902, input / output interface 903, and communication interface 904); The processor 901, memory 902, input / output interface 903, and communication interface 904 are connected to each other within the device via bus 905.

[0090] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described blood oxygen saturation measurement method.

[0091] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0092] The blood oxygen saturation measurement method, device, electronic equipment, and storage medium provided in this application obtain the distance between a photodetector and a red light source to obtain the red light distance, and the distance between the photodetector and an infrared light source to obtain the infrared light distance. Then, photoelectric detection is performed on the red and infrared light sources based on the photodetector to obtain blood oxygen characteristic values. Further, the blood oxygen characteristic values ​​are corrected based on the red and infrared light distances to obtain corrected characteristic values. Finally, a lookup table is performed on a preset blood oxygen mapping table based on the corrected characteristic values ​​to obtain blood oxygen saturation. Through the above technical solution, this application introduces red and infrared light distances to correct blood oxygen characteristic values ​​based on the obtained blood oxygen characteristic values, so that the blood oxygen characteristic values ​​can reflect the differences in propagation paths, scattering, and attenuation caused by the inconsistent physical layout of the red and infrared light sources, thereby reducing the measurement error introduced by the different spatial distances between the two light sources.

[0093] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0094] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0095] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0096] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0097] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0098] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0099] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0100] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0101] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0102] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0103] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for measuring blood oxygen saturation, characterized in that, The method is applied to a blood oxygen saturation measuring device, which includes a red light source, an infrared light source, and a photodetector. The distance between the photodetector and the red light source is obtained to get the red light distance; the distance between the photodetector and the infrared light source is obtained to get the infrared light distance. Based on the photodetector, photoelectric detection is performed on the red light source and the infrared light source to obtain blood oxygen characteristic values; Based on the red light distance and the infrared light distance, the blood oxygen characteristic value is corrected to obtain the corrected characteristic value; Based on the corrected feature value, a lookup process is performed on the preset blood oxygen mapping table to obtain the blood oxygen saturation.

2. The method according to claim 1, characterized in that, The step of performing photoelectric detection on the red light source and the infrared light source based on the photodetector to obtain blood oxygen characteristic values ​​includes: The red light source is photoelectrically detected using the photodetector to obtain red light characteristic values. The infrared light source is photoelectrically detected using the photodetector to obtain infrared light characteristic values. The blood oxygen characteristic value is obtained by calculating the ratio between the red light characteristic value and the infrared light characteristic value.

3. The method according to claim 1, characterized in that, The step of correcting the blood oxygen characteristic value based on the red light distance and the infrared light distance to obtain the corrected characteristic value includes: The distance difference is calculated by comparing the red light distance and the infrared light distance. The compensation factor is calculated based on the difference between the distance difference and the preset equivalent attenuation coefficient. The blood oxygen characteristic value is corrected according to the compensation factor to obtain the corrected characteristic value.

4. The method according to claim 1, characterized in that, The blood oxygen saturation measuring device includes at least two photodetectors. After correcting the blood oxygen characteristic value based on the red light distance and the infrared light distance to obtain the corrected characteristic value, it further includes: Outlier removal is performed on each of the modified feature values ​​to obtain the cluster feature value; The weighted average of each of the aforementioned cluster eigenvalues ​​is used to obtain the weighted eigenvalue; The weighted eigenvalues ​​are used as the corrected eigenvalues.

5. The method according to claim 4, characterized in that, The outlier removal process for each of the modified feature values ​​to obtain a cluster feature value includes: Obtain the median data of each of the corrected feature values ​​to obtain the feature median; The difference between each of the corrected feature values ​​and the median of the feature is obtained to obtain multiple median absolute deviations; The absolute deviations of the medians are sorted to obtain a sorted sequence; Obtain the median deviation of the median of the sorted sequence; Outlier removal is performed on each of the corrected feature values ​​based on the median deviation and the median feature value to obtain the cluster feature value.

6. The method according to claim 4, characterized in that, The step of taking a weighted average of the various grouping feature values ​​to obtain a weighted feature value includes: The signal-to-noise ratio (SNR) of the grouping feature values ​​is calculated to obtain SNR data; The signal-to-noise ratio data are geometrically averaged to obtain the eigenvalue weights; The weighted feature value is obtained by weighting and summing the cluster feature values ​​according to the feature value weights.

7. The method according to claim 1, characterized in that, After performing a lookup process on the preset blood oxygen mapping table based on the corrected feature value to obtain the blood oxygen saturation, the method further includes: Get historical saturation; The confidence level of the blood oxygen saturation is calculated based on the historical saturation to obtain confidence data; Wearing prompts are output based on the confidence level data.

8. A blood oxygen saturation measuring device, characterized in that, An apparatus for measuring blood oxygen saturation, comprising a red light source, an infrared light source, and a photodetector, wherein the apparatus includes: The data acquisition module is used to acquire the distance between the photodetector and the red light source to obtain the red light distance, and to acquire the distance between the photodetector and the infrared light source to obtain the infrared light distance; The photoelectric detection module is used to perform photoelectric detection on the red light source and the infrared light source based on the photoelectric detector to obtain blood oxygen characteristic values; The feature value correction module is used to correct the blood oxygen feature value based on the red light distance and the infrared light distance to obtain the corrected feature value; The blood oxygen lookup table module is used to perform a lookup process on a preset blood oxygen mapping table based on the corrected feature value to obtain blood oxygen saturation.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the blood oxygen saturation measurement method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the blood oxygen saturation measurement method according to any one of claims 1 to 7.

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