PPG light leakage self-checking method, wearable device and computer readable storage medium

Abstract

The invention discloses a PPG light leakage self-checking method, wearable equipment and a computer readable storage medium, and relates to the technical field of equipment detection.The PPG light leakage self-checking method is applied to the wearable equipment, the wearable equipment is integrated with a PPG sensor, the PPG sensor comprises a photoelectric detector and a light source, and the method comprises the steps that a PPG light leakage self-checking instruction is received; acquiring first photoelectric data detected by the photoelectric detector when the light source is turned on and second photoelectric data detected by the photoelectric detector when the light source is turned off, and determining PPG light leakage data according to the first photoelectric data and the second photoelectric data; determining a current monitoring scene, and dynamically determining a current light leakage data threshold according to the current monitoring scene; under the condition that the PPG light leakage data is larger than the current light leakage data threshold value, it is determined that the PPG sensor leaks light. According to the application, the convenience of light leakage detection is improved, and meanwhile, whether the PPG sensor of the wearable equipment leaks light or not can be more accurately and sensitively judged.

Description

Technical Field

[0001] This application relates to the technical field of device detection, and particularly to a PPG light leakage self-checking method, a wearable device, and a computer-readable storage medium. Background Art

[0002] Currently, most intelligent wearable devices are equipped with PPG (Photoplethysmography) sensors, which obtain physiological information by measuring the attenuation degree of light beams passing through or reflected by human tissues, so as to non-invasively measure key health indicators such as blood pressure and heart rate of the human body and provide real-time health monitoring for users.

[0003] In order to ensure the accuracy and reliability of the data collected by the PPG sensor, it is necessary to perform light leakage detection on the PPG sensor. However, traditional PPG light leakage detection needs to be carried out in a strictly controlled darkroom environment to exclude the interference of natural light and other light sources. The creation of a darkroom environment requires the use of a closed detection box and a special light-shielding structure, with high equipment costs and complex operation processes, which is not conducive to performing light leakage detection on the device during daily use and has great limitations. Summary of the Invention

[0004] The main purpose of this application is to provide a PPG light leakage self-checking method, a wearable device, and a computer-readable storage medium, aiming to solve the technical problem that traditional PPG light leakage detection depends on a strictly controlled darkroom environment and has low convenience.

[0005] To achieve the above object, this application provides a PPG light leakage self-checking method. The PPG light leakage self-checking method is applied to a wearable device, and the wearable device is integrated with a PPG sensor. The PPG sensor includes a photodetector and a light source. The method includes:

[0006] Receiving a PPG light leakage self-checking instruction;

[0007] Obtaining first photoelectric data detected by the photodetector when the light source is turned on, and second photoelectric data detected by the photodetector when the light source is turned off, and determining PPG light leakage data according to the first photoelectric data and the second photoelectric data;

[0008] Determining the current monitoring scenario started by the wearable device by selecting from multiple health indicator monitoring scenarios, and dynamically determining the current light leakage data threshold according to the current monitoring scenario, where multiple health indicator monitoring scenarios include at least three of a heart rate monitoring scenario, a blood oxygen saturation monitoring scenario, a blood pressure monitoring scenario, and a respiratory rate monitoring scenario, and the current light leakage data thresholds determined by different health indicator monitoring scenarios are different;

[0009] When the PPG light leakage data is greater than the current light leakage data threshold, it is determined that the PPG sensor has light leakage.

[0010] In one embodiment, the step of dynamically determining the current light leakage data threshold according to the current monitoring scenario includes:

[0011] Query the light leakage data threshold mapped by the current monitoring scenario from a preset scenario mapping threshold table according to the current monitoring scenario;

[0012] Use the mapped light leakage data threshold as the current light leakage data threshold.

[0013] In one embodiment, the step of dynamically determining the current light leakage data threshold according to the current monitoring scenario includes:

[0014] Dynamically detect the current optical sensitivity CTR of the PPG sensor;

[0015] Determine the current light source color of the light source corresponding to the current monitoring scenario according to the current monitoring scenario;

[0016] Dynamically determine the current light leakage data threshold according to the current light source color and the current CTR.

[0017] In one embodiment, the step of dynamically determining the current light leakage data threshold according to the current light source color and the current CTR includes:

[0018] When the current light source color is green, dynamically calculate the product of the current CTR and 3.7%, obtain a first product result, and dynamically determine the current light leakage data threshold based on the dynamically calculated first product result;

[0019] When the current light source color is red, dynamically calculate the product of the current CTR and 1.5%, obtain a second product result, and dynamically determine the current light leakage data threshold based on the dynamically calculated second product result.

[0020] In one embodiment, the step of determining the current light source color of the light source corresponding to the current monitoring scenario according to the current monitoring scenario includes:

[0021] When the current monitoring scenario is a blood oxygen saturation monitoring scenario, determine that the current light source color of the light source corresponding to the current monitoring scenario is red;

[0022] When the current monitoring scenario is a heart rate monitoring scenario, a blood pressure monitoring scenario, or a respiratory rate monitoring scenario, determine that the current light source color of the light source corresponding to the current monitoring scenario is green.

[0023] In one embodiment, the wearable device is further integrated with an ambient light detection device. After the step of receiving the PPG light leakage self-check instruction, the method further includes:

[0024] Obtain the ambient light data detected by the ambient light detection device within a sliding time window, and determine the degree of fluctuation of the ambient light data;

[0025] When the degree of fluctuation is the first degree of fluctuation, trigger the execution of the step of obtaining the first optoelectronic data detected by the photodetector when the light source is turned on;

[0026] When the degree of fluctuation is the second degree of fluctuation, output a preset ambient light fluctuation prompt, where the second degree of fluctuation is higher than the first degree of fluctuation.

[0027] In one embodiment, the method further includes:

[0028] When the PPG light leakage data is less than or equal to the current light leakage data threshold and the PPG light leakage data is not zero, generate PPG calibration data according to the PPG light leakage data, where the PPG calibration data is used to calibrate the PPG sensor.

[0029] In one embodiment, the photodetector includes a first photodetector and a second photodetector with different positions. The first optoelectronic data includes the third optoelectronic data detected by the first photodetector when the light source is turned on, and the fourth optoelectronic data detected by the second photodetector when the light source is turned on. The second optoelectronic data includes the fifth optoelectronic data detected by the first photodetector when the light source is turned off, and the sixth optoelectronic data detected by the second photodetector when the light source is turned off. The current light leakage data threshold includes a first light leakage data threshold dynamically determined based on the current monitoring scenario of the first photodetector, and a second light leakage data threshold dynamically determined based on the current monitoring scenario of the second photodetector;

[0030] The step of determining the PPG light leakage data according to the first optoelectronic data and the second optoelectronic data includes:

[0031] Determine the PPG light leakage data corresponding to the first photodetector according to the third optoelectronic data and the fifth optoelectronic data;

[0032] Determine the PPG light leakage data corresponding to the second photodetector according to the fourth optoelectronic data and the sixth optoelectronic data;

[0033] The step of determining that the PPG sensor has light leakage when the PPG light leakage data is greater than the current light leakage data threshold includes:

[0034] Determining that the PPG sensor has light leakage when the PPG light leakage data corresponding to the first photodetector is greater than the first light leakage data threshold, or the PPG light leakage data corresponding to the second photodetector is greater than the second light leakage data threshold.

[0035] In addition, to achieve the above object, the present application further provides a wearable device, which includes: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, the steps of the PPG light leakage self-check method as described above are implemented.

[0036] In addition, to achieve the above object, the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the PPG light leakage self-check method as described above are implemented.

[0037] In addition, to achieve the above object, the present application further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the PPG light leakage self-check method as described above is implemented.

[0038] The embodiments of the present application provide a PPG light leakage self - inspection method, a wearable device, and a computer - readable storage medium. The PPG light leakage self - inspection method is applied to a wearable device integrated with a PPG sensor, and the PPG sensor includes a photodetector and a light source. The technical solution of the embodiments of the present application is to receive a PPG light leakage self - inspection instruction, obtain first optoelectronic data detected by the photodetector when the light source is turned on, and second optoelectronic data detected when the light source is turned off. Then, determine the PPG light leakage data based on the first optoelectronic data and the second optoelectronic data. Next, determine the current monitoring scenario that the wearable device selects to start from multiple health index monitoring scenarios. According to the current monitoring scenario, dynamically determine the current light leakage data threshold. Among them, the multiple health index monitoring scenarios include at least three of a heart rate monitoring scenario, a blood oxygen saturation monitoring scenario, a blood pressure monitoring scenario, and a respiratory rate monitoring scenario. The current light leakage data thresholds determined for different health index monitoring scenarios are different. When the PPG light leakage data is greater than the current light leakage data threshold, it is determined that the PPG sensor has light leakage. Thus, the embodiments of the present application creatively transform the physical light shielding in a dark - room detection into a noise suppression model of optoelectronic signal differential calculation, breaking through the traditional dependence on a dark room, enabling the end - user to complete high - precision self - inspection in a daily environment, solving the technical problems that traditional PPG light leakage detection depends on a strictly controlled dark - room environment, with high equipment costs and complex operation processes, which is not conducive to light leakage detection in daily use, and significantly improving the convenience of PPG light leakage detection.

[0039] It is worth mentioning that the embodiments of the present application also adopt a technical solution of determining the current monitoring scenario that the wearable device selects to start from multiple health index monitoring scenarios and dynamically determining the current light leakage data threshold according to the current monitoring scenario. As a result, when the wearable device of the embodiments of the present application faces different health index monitoring scenarios (such as a heart rate monitoring scenario, a blood oxygen saturation monitoring scenario, a blood pressure monitoring scenario, or a respiratory rate monitoring scenario), it can adaptively adjust the size of the current light leakage data threshold, so as to facilitate selecting the most reasonable light leakage amount value as the current light leakage data threshold according to the current monitoring scenario. By dynamically and adaptively adjusting the current light leakage data threshold when the current monitoring scenario changes, no matter how the current monitoring scenario changes, the current light leakage data threshold can always dynamically and adaptively match the most accurate and appropriate light leakage amount value as the current light leakage data threshold based on the scenario type of the current monitoring scenario, which is convenient for comparing the most accurate and appropriate current light leakage data threshold with the actually detected PPG light leakage data later, thereby more accurately and sensitively determining whether there is light leakage in the PPG sensor of the wearable device, and effectively improving the accuracy of light leakage detection in daily use after the PPG light leakage detection is separated from the strictly controlled dark - room environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings here are incorporated into the specification and form a part of this specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0041] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings required for use in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on the structures shown in these drawings.

[0042] Figure 1 It is a schematic flowchart provided for the first embodiment of the PPG light leakage self-checking method of the present application;

[0043] Figure 2 It is a schematic flowchart provided for the second embodiment of the PPG light leakage self-checking method of the present application;

[0044] Figure 3 It is a schematic layout diagram of a light source and a photodetector in a specific embodiment of the present application;

[0045] Figure 4 It is a schematic scene diagram of PPG light leakage self-checking in a specific embodiment of the present application;

[0046] Figure 5 It is a schematic device structure diagram of the hardware operating environment involved in the PPG light leakage self-checking method in the embodiments of the present application.

[0047] The realization of the objectives, functional features, and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. Detailed Embodiments

[0048] Here, the exemplary embodiments will be described in detail, and the examples are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0049] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0050] Currently, traditional PPG light leakage detection methods require operation in a strictly controlled darkroom environment. Usually, a closed detection box and a specially designed light-shielding structure are needed to create a completely dark space to ensure that natural light and other external light sources can be excluded from interference.

[0051] However, this method has significant limitations and challenges. First of all, building such a darkroom environment not only has high equipment costs, but also requires additional space and resource investment, with relatively high hardware costs. Moreover, these devices are often bulky and difficult to move and deploy. On the other hand, the operation process is complex, including environmental settings, calibration steps, etc. This not only places high requirements on the professional skills of operators, but also prolongs the test preparation time and reduces the detection efficiency. In addition, in practical applications, especially for end-users, it becomes almost impossible to perform device self-checks during daily use. Since it is impossible to simulate ideal darkroom conditions anytime and anywhere, it is very difficult for end-users to detect problems with the optical path deterioration caused by long-term use in a timely manner, thus affecting the accuracy and reliability of health monitoring data.

[0052] In response to this, the main solution in the embodiments of this application is a PPG light leakage self-check method. The PPG light leakage self-check method is applied to a wearable device, and the wearable device is integrated with a PPG sensor. The PPG sensor includes a photodetector and a light source. The method includes: receiving a PPG light leakage self-check instruction; obtaining first photoelectric data detected by the photodetector when the light source is turned on, and second photoelectric data detected by the photodetector when the light source is turned off, and determining PPG light leakage data according to the first photoelectric data and the second photoelectric data; determining the current monitoring scenario selected and started by the wearable device from multiple health index monitoring scenarios, and dynamically determining the current light leakage data threshold according to the current monitoring scenario, where multiple health index monitoring scenarios include at least three of a heart rate monitoring scenario, a blood oxygen saturation monitoring scenario, a blood pressure monitoring scenario, and a respiratory rate monitoring scenario, and the current light leakage data thresholds determined by different health index monitoring scenarios are different; and determining that the PPG sensor has light leakage when the PPG light leakage data is greater than the current light leakage data threshold.

[0053] The embodiments of this application creatively transform the physical light shielding in darkroom detection into a noise suppression model for differential calculation of photoelectric signals, breaking through the dependence on traditional darkrooms, enabling end-users to complete high-precision self-checks in daily environments, solving the technical problems that traditional PPG light leakage detection depends on a strictly controlled darkroom environment, has relatively high equipment costs, and has a complex operation process, which is not conducive to light leakage detection during daily use, and significantly improving the convenience of PPG light leakage detection.

[0054] It is worth mentioning that, in the embodiments of the present application, a technical solution is also provided for determining the current monitoring scenario that the wearable device starts from multiple health index monitoring scenarios, and dynamically determining the current light leakage data threshold according to the current monitoring scenario. As a result, the wearable device in the embodiments of the present application can adaptively adjust the size of the current light leakage data threshold when facing different health index monitoring scenarios (such as a heart rate monitoring scenario, a blood oxygen saturation monitoring scenario, a blood pressure monitoring scenario, or a breathing rate monitoring scenario). Thus, it is convenient to select the most reasonable light leakage amount value as the current light leakage data threshold according to the current monitoring scenario. By dynamically and adaptively adjusting the current light leakage data threshold when the current monitoring scenario changes, no matter how the current monitoring scenario changes, the current light leakage data threshold can always dynamically and adaptively match the most accurate and appropriate light leakage amount value as the current light leakage data threshold based on the scenario type of the current monitoring scenario. This is convenient for subsequent comparison of the most accurate and appropriate current light leakage data threshold with the actually detected PPG light leakage data, thereby more accurately and sensitively determining whether there is light leakage in the PPG sensor of the wearable device, and effectively improving the accuracy of PPG light leakage detection in daily use after the strict control of the dark room environment is removed.

[0055] It should be noted that the execution subject of the embodiments of the present application is a wearable device, and the wearable device may include, but is not limited to, such as a smart watch, a smart bracelet, a smart helmet, smart glasses, a smart collar, or any electronic device capable of implementing the above functions. Hereinafter, taking the wearable device as the execution subject as an example, the following embodiments of the present application will be described.

[0056] To better understand the technical solution of the present application, the following will be described in detail in conjunction with the accompanying drawings of the specification and specific implementation manners.

[0057] The present application proposes a PPG light leakage self-checking method for the first embodiment.

[0058] Please refer to Figure 1 , Figure 1 which is a schematic flowchart provided for the first embodiment of the PPG light leakage self-checking method of the present application.

[0059] In this embodiment, the PPG light leakage self-checking method is applied to a wearable device, the wearable device is integrated with a PPG sensor, the PPG sensor includes a photodetector and a light source, and the method includes steps S100 to S400:

[0060] Step S100, receiving a PPG light leakage self-checking instruction;

[0061] As is known to those skilled in the art, a photodetector is a device that can convert optical signals into electrical signals. A PPG sensor is an optical sensor used to measure changes in blood volume, and is typically applied to monitor physiological parameters such as heart rate and blood oxygen saturation. The PPG sensor mainly includes a light source and a photodetector, and its working principle is as follows: the light source emits light of a specific wavelength (such as green light, red light, or infrared light) to human tissue. At the same time, the photodetector detects the change in light intensity after the light emitted by the light source is absorbed and scattered by the human tissue, and then measures various physiological indicators by analyzing the change in light intensity.

[0062] It should be noted that the PPG light leakage self-check instruction is an instruction triggered by the user or the system to activate the PPG light leakage self-check function of the wearable device. This PPG light leakage self-check instruction can be triggered manually or automatically under specific conditions, such as triggered automatically at a fixed time, triggered periodically, or triggered automatically after detecting that the wearable device has remained in a stationary state for a preset duration.

[0063] Step S200: Obtain the first optoelectronic data detected by the photodetector when the light source is on, and the second optoelectronic data detected when the light source is off, and determine the PPG light leakage data according to the first optoelectronic data and the second optoelectronic data;

[0064] As is known to those skilled in the art, when the light source is on, the signal received by the photodetector includes the light signal reflected or scattered by the human tissue after being emitted by the light source and the ambient light signal; when the light source is off, when the wearable device is not worn properly, or the optoelectronic detection system of the wearable device is not tightly encapsulated, etc., the optoelectronic signal is mainly composed of the ambient light signal.

[0065] It should be noted that the PPG light leakage data refers to the result calculated from the difference between the first optoelectronic data and the second optoelectronic data, which reflects whether there is unexpected light leakage into the photodetector in the current ambient light conditions. In this embodiment, by calculating the difference between the first optoelectronic data and the second optoelectronic data, the effective signal component caused by the internal light source of the PPG sensor can be effectively separated, thereby eliminating the interference of ambient light fluctuations on the light leakage detection.

[0066] In this embodiment, after receiving the PPG light leakage self-check instruction, there are various ways to obtain the first optoelectronic data and the second optoelectronic data required for the light leakage detection.

[0067] In one example, the data detected by the photodetector when the light source is on can be directly used as the first optoelectronic data, and the data detected by the photodetector when the light source is off can be used as the second optoelectronic data.

[0068] This example directly obtains the single measurement data of the photodetector when the light source is turned on and off as the first photoelectric data and the second photoelectric data, which has remarkable operational simplicity and efficiency. First, at the operational level, this example does not require additional data processing steps such as multiple samplings, removing extreme values, and calculating the average value, thus simplifying the algorithm design and reducing the requirements for the processor performance. Second, due to the reduction of the time for data acquisition and processing, this example can significantly improve the speed of the detection process, especially suitable for application scenarios that require quick feedback. Finally, for those situations where the external environmental conditions are extremely stable and the interference factors are few, single measurement can already provide sufficiently accurate results, enabling the device to achieve an efficient self-check process while ensuring a certain accuracy. Therefore, this example can demonstrate unique advantages in application scenarios with limited resources or high real-time requirements.

[0069] In another example, it is also possible to take multiple data detected by the photodetector when the light source is turned on, remove the maximum value and the minimum value, then calculate the average value, and use the average value as the first photoelectric data, and, take multiple data detected by the photodetector when the light source is turned off, remove the maximum value and the minimum value, then calculate the average value, and use the average value as the second photoelectric data.

[0070] This example obtains the first photoelectric data and the second photoelectric data by taking multiple measurements, removing the maximum value and the minimum value, and then calculating the average value, which can significantly improve the accuracy and stability of the detection results. First, through multiple samplings, this example effectively reduces the influence of accidental errors. Especially in the presence of short-term unpredictable interferences, it can more realistically reflect the changes of the actual photoelectric signals. Second, the process of removing extreme values and taking the average plays a simple filtering role, which helps to smooth data fluctuations, suppress random noise, thereby improving the signal-to-noise ratio and enhancing the stability of the output signal. Finally, this example is particularly suitable for application scenarios with high requirements for measurement accuracy, such as ensuring the accuracy of health monitoring data, or situations where various uncertain interference factors need to be excluded in complex and changeable environments. In summary, this example provides more reliable and accurate detection results through fine data processing, and is very suitable for application occasions with high-precision requirements.

[0071] Step S300, determine the current monitoring scenario that the wearable device selects to start from multiple health index monitoring scenarios, and dynamically determine the current light leakage data threshold according to the current monitoring scenario, where the multiple health index monitoring scenarios include at least three of a heart rate monitoring scenario, a blood oxygen saturation monitoring scenario, a blood pressure monitoring scenario, and a respiratory rate monitoring scenario, and the current light leakage data thresholds determined by different health index monitoring scenarios are different;

[0072] It should be noted that the health indicator monitoring scenario refers to various physiological parameter monitoring scenarios that a wearable device can perform through its integrated PPG sensor, including but not limited to heart rate monitoring, blood oxygen saturation monitoring, blood pressure monitoring, respiratory rate monitoring, etc. Among them, the heart rate monitoring scenario is a monitoring scenario specifically used to measure the number of heartbeats per minute, the blood oxygen saturation monitoring scenario is a monitoring scenario specifically used to measure the degree of oxygen saturation in the blood, the blood pressure monitoring scenario is a monitoring scenario specifically used to measure the blood pressure level, and the respiratory rate monitoring scenario is a monitoring scenario specifically used to measure the respiratory rate.

[0073] It should also be noted that the current monitoring scenario refers to the health indicator monitoring scenario that the user is currently using or the device automatically selects to perform. The current light leakage data threshold refers to the light leakage data threshold corresponding to the current monitoring scenario, which is used to determine whether there is a light leakage problem with the PPG sensor in the current monitoring scenario.

[0074] It can be understood that different monitoring scenarios have different tolerances for light leakage. For example, in the blood oxygen saturation monitoring scenario, since it relies on the change of light signals of specific wavelengths, the tolerance for light leakage is relatively low, and the corresponding current light leakage data threshold is also relatively small; while in the heart rate monitoring scenario, since the overall trend of light intensity change is mainly concerned, a relatively large amount of light leakage may be allowed without affecting the final measurement result. Therefore, the current light leakage data threshold will change with the change of the monitoring scenario to ensure that the most suitable light leakage standard can be adopted for detection in various application scenarios, so as to accurately detect potential light leakage problems and effectively improve the accuracy of light leakage detection.

[0075] After receiving the PPG light leakage self-check instruction in this embodiment, the current health indicator monitoring scenario being performed is first identified, and the best light leakage data threshold applicable to this scenario is selected as the current light leakage data threshold, so as to facilitate subsequent comparison of the PPG light leakage data calculated based on the difference between the first optoelectronic data and the second optoelectronic data with this current light leakage data threshold, thereby determining whether there is a light leakage problem with the PPG sensor in the current monitoring scenario.

[0076] Step S400, when the PPG light leakage data is greater than the current light leakage data threshold, it is determined that the PPG sensor has light leakage.

[0077] In this embodiment, when it is determined that the ambient light is in a stable state (i.e., the fluctuation degree of the ambient light data is the first fluctuation degree), the first optoelectronic data detected by the photodetector when the light source is turned on and the second optoelectronic data detected when the light source is turned off are respectively obtained, and the differential method is used to eliminate the influence of the ambient light, effectively separating the signal change caused by light leakage to obtain the PPG light leakage data. At the same time, according to the current monitoring scenario, the current light leakage data threshold is dynamically determined, so as to judge whether there is a light leakage risk of the PPG sensor in the current monitoring scenario through the current light leakage data threshold, ensuring that the most suitable light leakage standard can be adopted in various monitoring scenarios, accurately detecting potential light leakage problems, effectively improving the accuracy of light leakage detection, and then achieving accurate light leakage detection under natural light conditions, breaking through the dependence of traditional PPG light leakage detection on a dark room environment, and greatly improving the convenience and practicability of PPG light leakage detection.

[0078] In this embodiment, the physical light shielding for dark room detection is creatively transformed into a noise suppression model for optoelectronic signal differential calculation, breaking through the traditional dark room dependence, enabling end users to complete high-precision self-checks in daily environments, and solving the technical problems of traditional PPG light leakage detection relying on a strictly controlled dark room environment, with high equipment costs and complex operation processes, which is not conducive to light leakage detection in daily use, and significantly improving the convenience of PPG light leakage detection.

[0079] It is worth mentioning that this embodiment also determines the current monitoring scenario started by the wearable device selected from multiple health index monitoring scenarios, and according to this current monitoring scenario, dynamically determines the current light leakage data threshold technical solution, so that the wearable device in this embodiment can adaptively adjust the size of the current light leakage data threshold when facing different health index monitoring scenarios (such as heart rate monitoring scenario, blood oxygen saturation monitoring scenario, blood pressure monitoring scenario or respiratory rate monitoring scenario), so as to facilitate selecting the most reasonable light leakage value as the current light leakage data threshold according to the current monitoring scenario. By dynamically and adaptively adjusting the current light leakage data threshold when the current monitoring scenario changes, no matter how the current monitoring scenario changes, the current light leakage data threshold can always be dynamically and adaptively matched to the most accurate and appropriate light leakage value as the current light leakage data threshold based on the scenario type of the current monitoring scenario, facilitating subsequent comparison of the most accurate and appropriate current light leakage data threshold with the actually detected PPG light leakage data, thereby more accurately and sensitively determining whether there is light leakage in the PPG sensor of the wearable device, and then effectively improving the accuracy of light leakage detection in daily use after the PPG light leakage detection breaks away from the strictly controlled dark room environment.

[0080] In the first feasible implementation, the step of dynamically determining the current light leakage data threshold according to the current monitoring scenario in step S300 may include steps S310 to S320:

[0081] Step S310, query the light leakage data threshold mapped by the current monitoring scenario from a preset scenario mapping threshold table according to the current monitoring scenario;

[0082] It should be noted that in order to achieve the goal of adaptively adjusting the light leakage data threshold according to different health indicator monitoring scenarios, a scenario mapping threshold table is pre-constructed in this implementation. This table details the mapping relationships between each health indicator monitoring scenario (such as heart rate monitoring, blood oxygen saturation monitoring, blood pressure monitoring, and respiratory rate monitoring, etc.) and the corresponding light leakage data thresholds. For example, in the blood oxygen saturation monitoring scenario, since the accuracy requirement for the optical signal is relatively high, the corresponding light leakage data threshold is set relatively small; while in the heart rate monitoring scenario, considering that the overall trend of the light intensity change is mainly concerned, a larger light leakage amount is allowed without affecting the final heart rate measurement result, so the corresponding light leakage data threshold can be set larger.

[0083] The method of customizing the light leakage data threshold based on the specific application scenario requirements in this implementation not only takes into account the different requirements of different physiological parameter monitoring for the performance of the PPG sensor, but also ensures high precision and reliability in the light leakage detection process by finely managing the light leakage standards in each monitoring scenario. In addition, by organizing these mapping relationships into an easily accessible scenario mapping threshold table, the process of querying and applying the corresponding light leakage data threshold in the actual operation of the system is greatly simplified.

[0084] Step S320, use the mapped light leakage data threshold as the current light leakage data threshold.

[0085] By introducing the scenario mapping threshold table and querying and using the corresponding light leakage data threshold from it according to the current monitoring scenario, this implementation provides a simple and effective solution, enabling the wearable device to flexibly adjust the light leakage detection standard in different health indicator monitoring scenarios, significantly enhancing the applicability and accuracy of the PPG light leakage self-check method. It not only solves the problem of the high dependence of traditional PPG light leakage detection on a darkroom environment, but also realizes convenient and efficient light leakage detection in daily environments, providing a more reliable and user-friendly experience for users.

[0086] In the second feasible implementation, the step of dynamically determining the current light leakage data threshold according to the current monitoring scenario in step S300 may include steps S330 to S350:

[0087] Step S330, dynamically detect the current optical sensitivity CTR of the PPG sensor;

[0088] It should be noted that the optical sensitivity CTR (Current Transform Ratio) of a PPG sensor refers to the ability of the photodetector inside the PPG sensor to convert the optical signal emitted by the light source into an electrical signal. Specifically, it is a measure of the ratio of the light intensity received by the photodetector to the light intensity emitted by the light source.

[0089] Since the performance of a PPG sensor may be affected by various factors, such as the increase in usage time, changes in environmental conditions, etc., its actual optical sensitivity may vary. In this embodiment, by dynamically detecting the current optical sensitivity CTR of the PPG sensor, the sensitivity attenuation caused by sensor aging or environmental factors can be corrected in real time, avoiding misjudging normal signals as light leakage due to reduced sensitivity, and at the same time preventing the problem of missed detection of real light leakage due to abnormally increased sensitivity, significantly improving the detection reliability.

[0090] Step S340, according to the current monitoring scenario, determine the current light source color of the light source corresponding to the current monitoring scenario;

[0091] It should be noted that the current light source color refers to the color of the light that the light source needs to emit under the current monitoring scenario.

[0092] As known to those skilled in the art, the light source color (such as green light, red light, or infrared light) used by a PPG sensor has a direct impact on its monitoring effect. Different physiological parameter monitoring scenarios have different preferences for the light source color: for example, blood oxygen saturation monitoring usually relies on red light and infrared light because these two kinds of light can better penetrate the skin and provide information about the oxygen content in the blood; while heart rate monitoring prefers to use green light because it can better match the small-amplitude blood volume changes caused by heartbeats.

[0093] Exemplarily, in a feasible implementation manner, step S340 may include steps S341 to S342:

[0094] Step S341, when the current monitoring scenario is a blood oxygen saturation monitoring scenario, determine that the current light source color of the light source corresponding to the current monitoring scenario is red;

[0095] It should be noted that the monitoring of blood oxygen saturation depends on the absorption characteristics of different wavelength lights (especially red light and infrared light) after penetrating human tissues. The oxygen content in the blood will affect the absorption rate of these lights. By analyzing the intensity difference of red light and infrared light after passing through the finger or other parts, the blood oxygen saturation can be calculated.

[0096] Therefore, when performing blood oxygen saturation monitoring, choosing red as the light source color is based on its physical characteristics that are particularly effective for detecting the oxygen level in the blood.

[0097] In addition, the red light source has a good effect on penetrating tissues such as the skin and muscles, and can provide stable and accurate measurement results.

[0098] Step S342, when the current monitoring scenario is a heart rate monitoring scenario, a blood pressure monitoring scenario, or a respiratory rate monitoring scenario, determine that the current light source color of the light source corresponding to the current monitoring scenario is green.

[0099] As is known to those skilled in the art, green light can well match the small blood volume changes caused by heartbeats and effectively reflect the information of blood flow. That is, the change in blood volume will cause a change in the absorption rate of green light. Therefore, this change can be captured by a photodetector and converted into an electrical signal to measure the heart rate and indirectly estimate the blood pressure level.

[0100] In addition, since the breathing process will cause changes in the distribution of blood in the body, which in turn affects the morphology of the PPG signal, green light is also applicable to the monitoring work in this scenario.

[0101] Since the optical sensitivity CTR of the photodetector to different color lights will be different. This means that even for the same PPG sensor, when using light sources of different colors, its ability to convert optical signals into electrical signals will also vary. In this embodiment, the setting of the light leakage data threshold is further optimized through the current light source color, so that the threshold setting is deeply coupled with the physical characteristics of the light wave, thereby obtaining a more accurate light leakage data threshold as the current light leakage data threshold, ensuring that a more accurate light leakage detection result can be finally obtained.

[0102] Step S350, dynamically determine the current light leakage data threshold according to the current light source color and the current CTR.

[0103] In this embodiment, by dynamically determining the current light leakage data threshold according to the current CTR and the current light source color, an adaptive light leakage threshold decision system is constructed, which solves the problem of threshold rigidity caused by sensor performance drift and fixed light wave parameters in the traditional scheme, ensures that the current light leakage data threshold is dynamically adjusted according to the sensor state and the current monitoring scenario, enables the light leakage detection to maintain high precision in monitoring scenarios with significant differences such as heart rate, blood oxygen, and blood pressure, and promotes the all-weather reliable self-check of wearable devices in natural light environments.

[0104] Furthermore, in a feasible embodiment, step S350 may include steps S351 to S352:

[0105] Step S351, when the current light source color is green, dynamically calculate the product of the current CTR and 3.7%, obtain a first product result, and based on the dynamically calculated first product result, dynamically determine the current light leakage data threshold;

[0106] Step S352, when the current light source color is red, dynamically calculate the product of the current CTR and 1.5%, obtain a second product result, and based on the dynamically calculated second product result, dynamically determine the current light leakage data threshold.

[0107] In this embodiment, through the dual mechanisms of light source color-specific correction and real-time determination of CTR, the light leakage detection threshold is deeply adapted to the true performance of the photodetector and the monitoring scenario, enabling the system to flexibly and accurately adjust the current light leakage data threshold according to the specific light source color and the actual working efficiency of the photodetector (i.e., the current CTR). Specifically, the light source color-specific correction is based on the physical property differences of lights with different wavelengths. For example, green light has a high correction coefficient to improve sensitivity because of its shallow tissue penetration and weak environmental interference, while red light has a low correction coefficient to enhance anti-interference ability because of its deep penetration and strong environmental noise, thus directly mapping the optical propagation law to the threshold decision logic to ensure the essential association between the light leakage determination standard and the light wave characteristics. At the same time, the dynamic detection of CTR provides real-time feedback on the change of the photoelectric conversion efficiency, avoiding misdetection of light leakage caused by sensor aging.

[0108] Under the synergistic effect of the two, this embodiment constructs a dynamic threshold model driven by "optical physical properties - sensor state" in two dimensions, achieving a balance between high-precision noise suppression and weak signal capture in scenarios such as blood oxygen and heart rate, breaking through the rigid limitations of traditional fixed thresholds, enabling light leakage detection to have environmental adaptability, sensor life perception ability, and scenario-based precision optimization, and providing a universal solution for the reliable self-check of wearable devices in complex lighting and long-term use scenarios.

[0109] It is worth mentioning that when dynamically determining the current light leakage data threshold based on the first product result or the second product result obtained by dynamic calculation, the product result can be directly used as the current light leakage data threshold, or on the basis of this product result, combined with other influencing factors, the product result can be adjusted to some extent and then used as the current light leakage data threshold. This embodiment does not make specific limitations on this.

[0110] Based on the above first embodiment, the second embodiment of the PPG light leakage self-check method of this application is proposed.

[0111] In the second embodiment of this application, for the content that is the same as or similar to the above embodiment, reference can be made to the above introduction and will not be elaborated hereinafter.

[0112] Please refer to Figure 2 ,Figure 2 This is a flow chart of the second embodiment of the PPG light leakage self-detection method of the present application.

[0113] In this embodiment, the wearable device is further integrated with an ambient light detection device. After step S100 receives the PPG light leakage self-detection instruction, the PPG light leakage self-detection method may further include steps S500 to S700:

[0114] Step S500, obtaining ambient light data detected by the ambient light detection device within a sliding time window, and determining a degree of fluctuation of the ambient light data;

[0115] It should be noted that the ambient light detection device is a device for detecting ambient light. The ambient light data refers to the ambient light data detected by the ambient light detection device within the sliding time window after the wearable device receives the PPG light leakage self-test instruction, mainly including the light intensity and frequency of the ambient light within the sliding time window.

[0116] It should also be noted that the degree of fluctuation refers to the discreteness of the ambient light data, which reflects the stability of the ambient light within the sliding time window.

[0117] In this embodiment, the degree of fluctuation can be determined by statistical quantities such as variance, standard deviation, and range.

[0118] For example, in a feasible implementation, the step of determining the degree of fluctuation of the ambient light data in step S500 may include steps S510 to S520:

[0119] Step S510, performing statistical analysis on the ambient light data to obtain statistics of the ambient light data, wherein the statistics include at least one of variance, standard deviation, and range;

[0120] Those skilled in the art will know that statistics refer to quantitative indicators used in statistics to describe or summarize the characteristics of a data set.

[0121] In this embodiment, statistics mainly refer to indicators used to quantify the degree of dispersion of data, that is, parameters such as variance, standard deviation, and range.

[0122] Step S520: determining the degree of fluctuation of the ambient light data based on the statistics.

[0123] In this embodiment, the degree of fluctuation can be divided into multiple levels in advance, where the lower the level, the smaller the fluctuation, and specific judgment criteria are set for the degree of fluctuation at each level, so as to compare the statistics with the judgment criteria corresponding to each level to determine which level the degree of fluctuation of the ambient light data belongs to.

[0124] Exemplarily, the degree of fluctuation can be divided into two levels, namely the first level and the second level, and the degree of fluctuation of the second level is higher than that of the first level. At this time, if the statistic is the range, the judgment criterion corresponding to the first level can be set as the statistic being less than a preset range threshold, and the judgment criterion corresponding to the second level can be set as the statistic being not less than the preset range threshold. If the statistic is the variance and the standard deviation, the judgment criterion corresponding to the first level can be set as the variance in the statistic being less than a preset variance threshold and the standard deviation in the statistic being less than a preset standard deviation threshold, and the judgment criterion corresponding to the second level can be set as the variance in the statistic being not less than the preset variance threshold or the standard deviation in the statistic being not less than the preset standard deviation threshold, and so on.

[0125] In this embodiment, by introducing statistics such as variance, standard deviation, and range to quantify the degree of fluctuation of the ambient light data, and dividing the degree of fluctuation into multiple levels, each level corresponding to different judgment criteria, the accuracy and adaptability of PPG light leakage self-check are significantly improved. Specifically, in this embodiment, first, through a detailed statistical analysis of the ambient light data within the sliding time window, key statistics reflecting the degree of data dispersion are calculated; then, based on the comparison of these statistics with the preset judgment criteria, it is determined which level the degree of fluctuation of the current ambient light belongs to. This hierarchical fluctuation evaluation mechanism can not only effectively identify the stable lighting conditions most suitable for light leakage detection, but also allow the system to flexibly adjust the judgment criteria according to the actual application scenario, greatly improving the reliability and efficiency of the detection.

[0126] It can be understood that when the degree of fluctuation is divided into the first level and the second level, the degree of fluctuation of the first level can be determined as the first degree of fluctuation, indicating that the fluctuation of the ambient light is relatively slight and in a relatively stable state, which can trigger the light leakage detection, while the degree of fluctuation of the second level can be determined as the second degree of fluctuation, indicating that the fluctuation of the ambient light is relatively obvious and in a state of frequent change, which is not suitable for triggering the light leakage detection.

[0127] Correspondingly, when the levels of the degree of fluctuation are divided more finely, it can be set that the degree of fluctuation lower than a certain level belongs to the first degree of fluctuation, and the degree of fluctuation of the remaining levels belongs to the second degree of fluctuation.

[0128] In addition, this embodiment can also directly set the corresponding judgment criteria for the first degree of fluctuation and the second degree of fluctuation, so as to directly determine whether the degree of fluctuation of the ambient light data is the first degree of fluctuation or the second degree of fluctuation based on the statistic, reducing the intermediate links.

[0129] In addition to the method of determining the degree of fluctuation through statistics, this embodiment can also calculate the change rate of the ambient light data at adjacent time points within the sliding time window, and then determine the degree of fluctuation through parameters such as the average value, maximum value, and minimum value of the change rate.

[0130] Exemplarily, when the maximum value of the change rate is less than 1, the minimum value is greater than -1, and the average value is between -0.3 and 0.3, it is determined that the fluctuation degree of the ambient light data is the first fluctuation degree; otherwise, it is determined that the fluctuation degree of the ambient light data is the second fluctuation degree.

[0131] It should be specifically noted that within this sliding time window, various light-emitting components of the wearable device (including but not limited to the display light-emitting module, indicator light, and light source in the PPG sensor) should remain in their original states. This is because if the states of various light-emitting components of the wearable device change continuously within the sliding time window, it may cause significant fluctuations in the ambient light data, making the system always consider the current ambient light unstable and not suitable for light leakage detection. This will not only reduce the success rate and efficiency of light leakage detection but also increase the algorithm complexity and energy consumption, affecting the user experience and device performance.

[0132] In this embodiment, after receiving the PPG light leakage self-check instruction and before starting the ambient light detection device to detect the ambient light, it is possible to control various light-emitting components inside the wearable device to remain in their original states, so as to avoid introducing additional light interference during the detection process of the ambient light data within the sliding time window, resulting in the inability of the ambient light data to accurately depict the changes in the external ambient light, thereby effectively avoiding misjudgment of the ambient light stability caused by changes in the internal light source, ensuring that the system accurately judges the stability of the ambient light, and further improving the reliability and efficiency of light leakage detection.

[0133] In this embodiment, after receiving the PPG light leakage self-check instruction, the ambient light detection device is started to detect the ambient light. Thus, by obtaining the ambient light data detected by the ambient light detection device within the sliding time window, the fluctuation of the ambient light is monitored in real time. Furthermore, according to the fluctuation of the ambient light, it is determined whether the current ambient light is stable and suitable for light leakage detection of the PPG sensor, so as to break the dependence on the darkroom environment in the traditional solution.

[0134] Step S600, in the case where the fluctuation degree is the first fluctuation degree, trigger the step of obtaining the first optoelectronic data detected by the photodetector when the light source is turned on;

[0135] It should be noted that the first fluctuation degree is a preset fluctuation degree, indicating that the fluctuation of the ambient light is small and in a relatively stable state, and light leakage detection can be triggered.

[0136] In this embodiment, when the fluctuation degree of the ambient light data is at the first fluctuation degree, indicating that the lighting environment is relatively stable in the current environment, it is determined that the light leakage detection can be triggered, and step S200 is executed to obtain the first optoelectronic data detected by the photodetector when the light source is turned on and the second optoelectronic data detected when the light source is turned off, and determine the PPG light leakage data based on the first optoelectronic data and the second optoelectronic data, so as to avoid misjudgment of light leakage caused by dynamic light interference through pre-screening of ambient light stability and improve the detection success rate.

[0137] It is worth mentioning that in this embodiment, when the fluctuation degree of the ambient light data is at the first fluctuation degree and it is determined that the light leakage detection can be triggered, the ambient light detection device can be turned off and no longer obtain ambient light data to reduce energy consumption and extend the battery life of the wearable device. It is also possible to continue to turn on the ambient light detection device and increase the judgment standard of the first fluctuation degree, so as to reduce the influence of the on / off of the light source in the PPG sensor on the judgment of ambient light stability during the light leakage detection process, ensure that the result of the light leakage detection is determined based on the data detected when the ambient light is in a stable state, and prevent inaccurate detection results caused by sudden changes in ambient light during the light leakage detection process, and ensure that the entire light leakage detection process is carried out when the ambient light is in a stable state.

[0138] Step S700, when the fluctuation degree is at the second fluctuation degree, output a preset ambient light fluctuation prompt, where the second fluctuation degree is higher than the first fluctuation degree.

[0139] It should be noted that the ambient light fluctuation prompt is a notice or warning message sent by the wearable device to the user when it detects that the current ambient light conditions are not suitable for self-checking the light leakage of the PPG sensor. This prompt is intended to inform the user that the current ambient light changes too frequently or the intensity difference is too large, resulting in the photodetector being unable to accurately detect light leakage. Specifically, when the system analyzes the ambient light data within the sliding time window and finds that its fluctuation degree reaches the preset second fluctuation degree (i.e., large fluctuation, indicating unstable ambient light), this prompt will be triggered. The ambient light fluctuation prompt can be conveyed to the user in various forms such as displaying text information on the device's display screen, emitting a sound alarm, or vibrating notification, guiding the user to select a more stable lighting environment to retry the light leakage detection. This not only helps to avoid misjudgment or inaccurate detection results caused by ambient light interference, but also improves the user's experience and understanding of device operation. In this way, it is ensured that the light leakage detection is only performed under ideal environmental conditions, thus guaranteeing the accuracy and reliability of the detection process.

[0140] In this embodiment, when the detected environmental light data fluctuation degree is the second fluctuation degree (i.e., the environmental light is unstable and the fluctuation is obvious), a preset environmental light fluctuation prompt is output. This step aims to enhance the user experience and improve the reliability of the detection process. By timely feedback to the user that the current environment is not suitable for accurate light leakage detection, it avoids misjudgment or inaccurate results caused by unstable external light conditions. Specifically, when the system determines that the environmental light is in a relatively fluctuating state, it will automatically pause the light leakage detection process and display corresponding prompt information through the user interface of the wearable device, informing the user to try again in a more stable lighting environment. This not only improves the user's trust and satisfaction but also ensures that the light leakage detection is only performed under ideal conditions, thus guaranteeing the accuracy and reliability of the detection results.

[0141] In a feasible implementation manner, the PPG light leakage self-check method may further include step S800:

[0142] When the PPG light leakage data is less than or equal to the current light leakage data threshold and the PPG light leakage data is not zero, PPG calibration data is generated according to the PPG light leakage data, where the PPG calibration data is used to calibrate the PPG sensor.

[0143] To further improve the accuracy and reliability of the PPG sensor, in this implementation manner, when it is determined that the PPG light leakage data is less than or equal to the current light leakage data threshold, that is, on the basis of confirming that there is no obvious light leakage problem in the current PPG sensor, an additional calibration step is introduced. By using the obtained PPG light leakage data to generate specific PPG calibration data, during the subsequent use of the wearable device, the PPG sensor is accurately calibrated through the PPG calibration data to compensate for the small performance drift or error caused by long-term use or other factors.

[0144] Exemplarily, when the PPG light leakage data is greater than the current light leakage data threshold, an alarm message indicating that the detection of the human health monitoring data by the wearable device is inaccurate is output.

[0145] Among them, the human health monitoring data can be physiological parameters such as heart rate, blood oxygen saturation, or sleep, which are not specifically limited in this embodiment.

[0146] When the PPG light leakage data is greater than the current light leakage data threshold, it is determined that the PPG sensor has light leakage, or more specifically, the PPG sensor has light leakage that cannot be calibrated. That is, it is determined that the monitoring function of the wearable device for human health indicators is no longer qualified. At this time, even if the PPG sensor is compensated based on the PPG light leakage data, accurate calibration cannot be achieved because too much PPG optoelectronic data is lost due to a large amount of light leakage data, and a large amount of lost PPG optoelectronic data often contains a lot of detection information for relevant health indicators such as heart rate, blood oxygen, or sleep. Therefore, when the PPG light leakage data is greater than the current light leakage data threshold, even if PPG calibration data is generated based on the PPG light leakage data to compensate the PPG sensor, effective calibration cannot be achieved, and thus physiological parameters such as heart rate, blood oxygen saturation, or sleep cannot be accurately monitored anymore. The unqualified product needs to be reworked and repaired.

[0147] In a feasible implementation manner, the wearable device is also integrated with an inertial sensor. Before the step of obtaining the ambient light data detected by the ambient light detection device within the sliding time window in step S500, the PPG light leakage self-check method may further include steps A10 to A20:

[0148] Step A10, determine the motion state of the wearable device according to the data detected by the inertial sensor;

[0149] Step A20, when the motion state is stationary, execute the step of obtaining the ambient light data detected by the ambient light detection device within the sliding time window.

[0150] As known to those skilled in the art, an inertial sensor is a device that can sense changes in the acceleration and angular velocity of an object and usually includes components such as an accelerometer and a gyroscope. By analyzing these data, the current motion state of the wearable device, whether it is stationary or moving, can be accurately determined.

[0151] This embodiment uses the data provided by the inertial sensor to evaluate whether the wearable device is in a stationary state, thereby ensuring that the device has stopped moving stably before ambient light data is collected. Once it is confirmed that the wearable device is in a stationary state (i.e., there is no obvious displacement or rotation), the system will trigger the execution of the step of obtaining the ambient light data detected by the ambient light detection device within the sliding time window and start collecting ambient light data. This is because when the wearable device is in a motion state, its relative position to the ambient light source may change rapidly, resulting in the data collected by the ambient light detection device containing dynamic interference components, such as high-frequency fluctuations in ambient light intensity caused by arm swinging. Such dynamic interference will significantly increase the fluctuation degree of the ambient light data within the sliding time window, causing the system to misjudge the ambient light as unstable and frequently abort the light leakage detection process, ultimately leading to an increase in the detection failure rate and energy consumption waste.

[0152] In this embodiment, by strongly associating the trigger condition for ambient light stability judgment with the stationary state of the device, the transient ambient light noise caused by movement is effectively filtered out, enabling the fluctuation degree of the ambient light data to truly reflect the stability of the ambient light.

[0153] Based on the above second embodiment, a PPG light leakage self-check method according to a third embodiment of the present application is proposed.

[0154] In the third embodiment of the present application, for the content that is the same as or similar to the above embodiments, reference may be made to the above introduction and will not be repeated hereinafter.

[0155] In this embodiment, the photodetector includes a first photodetector and a second photodetector with different positions. The first photoelectric data includes the third photoelectric data detected by the first photodetector when the light source is turned on, and the fourth photoelectric data detected by the second photodetector when the light source is turned on. The second photoelectric data includes the fifth photoelectric data detected by the first photodetector when the light source is turned off, and the sixth photoelectric data detected by the second photodetector when the light source is turned off. The current light leakage data threshold includes a first light leakage data threshold dynamically determined based on the current monitoring scenario of the first photodetector, and a second light leakage data threshold dynamically determined based on the current monitoring scenario of the second photodetector;

[0156] The step of determining the PPG light leakage data according to the first photoelectric data and the second photoelectric data in step S200 may include steps S210 to S220:

[0157] Step S210, determining the PPG light leakage data corresponding to the first photodetector according to the third photoelectric data and the fifth photoelectric data;

[0158] Step S220, determining the PPG light leakage data corresponding to the second photodetector according to the fourth photoelectric data and the sixth photoelectric data;

[0159] When the PPG light leakage data is greater than the current light leakage data threshold in step S400, determining that the PPG sensor has light leakage may include step S410:

[0160] Step S410, determining that the PPG sensor has light leakage when the PPG light leakage data corresponding to the first photodetector is greater than the first light leakage data threshold, or the PPG light leakage data corresponding to the second photodetector is greater than the second light leakage data threshold.

[0161] In this embodiment, when there is more than one photoelectric sensor in the PPG sensor, the data detected by each photoelectric sensor when the light source is turned on and off can be obtained respectively, and the influence of ambient light can be excluded through differential calculation. Then, combined with the current light leakage data threshold set separately for each photodetector, the light leakage situation at each photodetector can be accurately quantified, so as to realize the independent light leakage detection of different photodetectors and improve the sensitivity and adaptability of PPG light leakage detection.

[0162] It is worth mentioning that after realizing the independent light leakage detection based on the photodetector, it is possible to further determine which photodetector in the PPG sensor has a light leakage phenomenon, which is convenient for targeted repair during subsequent maintenance.

[0163] In addition, when the PPG light leakage data corresponding to each photodetector is less than or equal to its respective current light leakage data threshold and is not zero, the PPG calibration data corresponding to each photodetector can be generated correspondingly, so as to achieve the calibration accuracy at the photodetector level when calibrating the PPG sensor.

[0164] Based on the above second embodiment, the PPG light leakage self-check method of the fourth embodiment of the present application is proposed.

[0165] In the fourth embodiment of the present application, the content that is the same as or similar to the above embodiment can be referred to the above introduction and will not be repeated hereinafter.

[0166] In this embodiment, the light source includes a first light source and a second light source with different positions. The first photoelectric data includes the seventh photoelectric data detected by the photodetector when the first light source is turned on and the second light source is turned off, and the eighth photoelectric data detected by the photodetector when the second light source is turned on and the first light source is turned off;

[0167] The step of determining the PPG light leakage data according to the first photoelectric data and the second photoelectric data in step S200 may further include steps S230 to S240:

[0168] Step S230, determining the PPG light leakage data corresponding to the first light source according to the seventh photoelectric data and the second photoelectric data;

[0169] Step S240, determining the PPG light leakage data corresponding to the second light source according to the eighth photoelectric data and the second photoelectric data;

[0170] When the PPG light leakage data is greater than the current light leakage data threshold in step S400, determining that the PPG sensor has a light leakage may further include step S420:

[0171] Step S420: Determine that there is PPG sensor light leakage when the PPG light leakage data corresponding to the first light source is greater than the current light leakage data threshold, or the PPG light leakage data corresponding to the second light source is greater than the current light leakage data threshold.

[0172] In this embodiment, when there is more than one light source in the PPG sensor, the data detected by the photoelectric sensor when different light sources are turned on alone can be obtained respectively, and the influence of ambient light can be excluded through differential calculation, so as to accurately quantify the light leakage situation of each light source in the PPG sensor, thereby realizing independent light leakage detection of different light sources and improving the sensitivity and adaptability of PPG light leakage detection.

[0173] It is worth mentioning that after realizing independent light leakage detection based on the light source, it is possible to further determine which light source in the PPG sensor has a light leakage phenomenon, which is convenient for targeted repair during subsequent maintenance.

[0174] In addition, when the PPG light leakage data corresponding to each light source is less than or equal to the current light leakage data threshold and is not zero, PPG calibration data corresponding to each light source can be generated accordingly, so as to achieve calibration accuracy at the light source level when calibrating the PPG sensor.

[0175] To facilitate understanding of the PPG light leakage self-check method provided in the above embodiments of the present application, a specific embodiment is specifically listed:

[0176] As Figure 3 shown, in this specific embodiment, the PPG light leakage self-check mainly involves a wearable device integrated with a PPG sensor, control software (host computer software, mobile phone APP or internal program of the wearable device), and a cloud device.

[0177] In this specific embodiment, a tester or user can issue a PPG light leakage self-check instruction through the control software to trigger the wearable device to perform PPG light leakage detection and display the data and results of the PPG light leakage detection. At the same time, the wearable device will also transmit the data and results of the PPG light leakage detection to the cloud device for storage and recording, so as to facilitate real-time monitoring of the defect rate of the PPG sensor.

[0178] As Figure 4As shown, in this specific embodiment, the PPG sensor mainly includes 3 LEDs (Light Emitting Diode, also known as light source) and 4 PDs (Photo Diode, also known as photodetector), and there is a light-shielding structure such as foam between the LED and the PD to block light and prevent the light of the LED from directly entering the corresponding PD. Among them, the 3 LEDs are LED1, LED2, and LED3 respectively, and the 4 PDs are PD1, PD2, PD3, and PD4 respectively. When LED1 emits light, it corresponds to PD1, PD2, PD3, and PD4. When LED2 emits light, it corresponds to PD3 and PD4. When LED3 emits light, it corresponds to PD1 and PD2.

[0179] In this specific embodiment, after the wearable device receives the PPG self-check instruction, it first determines whether the wearable device is stationary and horizontal by reading the data collected by the inertial sensor built in the wearable device. That is to say, the wearable device is also integrated with an inertial sensor. Before the step of obtaining the ambient light data detected by the photodetector within the sliding time window, the method further includes: determining the motion state of the wearable device according to the data detected by the inertial sensor; in the case where the motion state is stationary, executing the step of obtaining the ambient light data detected by the ambient light detection device within the sliding time window.

[0180] When the wearable device is stationary and horizontal, in this specific embodiment, it first determines the current ambient light stability through the ambient light detection device. After determining that the current ambient light is stable, it sequentially controls LED1 to turn on for one second - LED1 to turn off for one second - LED2 to turn on for one second - LED2 to turn off for one second - LED3 to turn on for one second - LED3 to turn off for one second (initially, all LEDs are in the off state), and within the time when the LED is on and off, it reads the data detected by the PD corresponding to the LED respectively, so as to determine the PD data when each LED is on and off. That is to say, it determines the fluctuation degree of the ambient light data, and in the case where the fluctuation degree is the first fluctuation degree, it obtains the first optoelectronic data detected by the photodetector when the light source is on, and the second optoelectronic data detected when the light source is off.

[0181] Exemplarily, when LED1 is on, the data detected by PD1, PD2, PD3, and PD4 can be read respectively and averaged, that is, PD(LED1 on) = (PD1 + PD2 + PD3 + PD4) / 4, as the PD data when LED1 is on. To avoid accidental interference, multiple operations can be performed within a specified time to obtain multiple PD(LED1 on), then the highest and lowest values can be removed, and the remaining data can be averaged again as the final PD(LED1 on). By analogy, the PD data PD(LED1 off) when LED1 is off, the PD data PD(LED2 on) when LED2 is on, the PD data PD(LED2 off) when LED2 is off, the PD data PD(LED3 on) when LED3 is on, and the PD data PD(LED3 off) when LED3 is off can be obtained.

[0182] Next, calculate the PPG light leakage data corresponding to each LED, and the formula is as follows:

[0183] PD(LED1 light leakage) = PD(LED1 on) - PD(LED1 off);

[0184] PD(LED2 light leakage) = PD(LED2 on) - PD(LED2 off);

[0185] PD(LED3 light leakage) = PD(LED3 on) - PD(LED3 off);

[0186] Among them, PD(LED1 light leakage) is the PPG light leakage data corresponding to LED1, PD(LED2 light leakage) is the PPG light leakage data corresponding to LED2, and PD(LED3 light leakage) is the PPG light leakage data corresponding to LED3.

[0187] That is, according to the first optoelectronic data and the second optoelectronic data, the PPG light leakage data is determined.

[0188] After calculating the PPG light leakage data corresponding to each LED in this specific embodiment, the PPG light leakage data corresponding to each LED is sequentially compared with the current light leakage data threshold PD (light leakage threshold). If any PD (LED light leakage) > PD (light leakage threshold), it is considered that there is light leakage in the PPG sensor, and the product is determined to be unqualified. At this time, even if the PPG sensor is compensated based on the PPG light leakage data, accurate calibration cannot be achieved because too much PPG optoelectronic data is lost due to excessive light leakage data, and a large amount of the lost PPG optoelectronic data often contains a lot of detection information for relevant health indicators such as heart rate, blood oxygen, or sleep. Therefore, when the PPG light leakage data is greater than the current light leakage data threshold, even if PPG calibration data is generated based on the PPG light leakage data to compensate the PPG sensor, effective calibration cannot be achieved, and thus physiological parameters such as heart rate, blood oxygen saturation, or sleep cannot be accurately monitored anymore, and the unqualified product needs to be reworked and repaired; if all PD (LED light leakage) ≤ PD (light leakage threshold), it is considered that the light leakage of the PPG sensor is within an acceptable error range, and it is determined that the product does not need to be reworked and repaired. If the light leakage of the PPG sensor is within an acceptable error range but the light leakage is not 0, only the PPG sensor needs to be calibrated according to the light leakage data of the PPG sensor (that is, when the PPG light leakage data is less than or equal to the current light leakage data threshold and the PPG light leakage data is not zero, PPG calibration data is generated based on the PPG light leakage data, where the PPG calibration data is used to optimize and calibrate the PPG sensor, which is okay). That is, when the PPG light leakage data corresponding to the first light source is greater than the current light leakage data threshold, or the PPG light leakage data corresponding to the second light source is greater than the current light leakage data threshold, it is determined that there is light leakage in the PPG sensor.

[0189] Among them, the setting of PD (light leakage threshold) can refer to the optical sensitivity of the PPG sensor (i.e., the current CTR). According to the differences in the absorption and reflection of red light and green light by the human skin, and the actual requirements of the algorithm, when the light emitted by the LED is green, the corresponding PD (light leakage threshold) can be set as: PD (light leakage threshold - green light) = 3.7% * CTR, and when the light emitted by the LED is red, the corresponding PD (light leakage threshold) can be set as: PD (light leakage threshold - red light) = 1.5% * CTR. That is, when the current light source color is green, the product of the current CTR and 3.7% is dynamically calculated to obtain the first product result, and based on the dynamically calculated first product result, the current light leakage data threshold is dynamically determined; when the current light source color is red, the product of the current CTR and 1.5% is dynamically calculated to obtain the second product result, and based on the dynamically calculated second product result, the current light leakage data threshold is dynamically determined.

[0190] After determining that the light leakage of the PPG sensor is within an acceptable error range in this specific embodiment, it is determined that the PPG sensor has no light leakage, or it can also be said that the PPG sensor has a weak light leakage that can be calibrated (when the PPG light leakage data is not zero). At this time, when the PPG light leakage data is not zero, it is also necessary to further calibrate the PPG sensor based on this PPG light leakage data to eliminate the existing slight light leakage situation, without the need for rework and repair.

[0191] In one example, the calibration method is as follows: Save the PPG light leakage data corresponding to each LED in the memory. Each time the PPG sensor data is acquired subsequently, extract the corresponding PPG light leakage data from the memory according to the currently applied LED and PD. Subtract the corresponding PPG light leakage data from the measured PD data to obtain the calibrated PD data. That is, when the PPG light leakage data is less than or equal to the current light leakage data threshold and the PPG light leakage data is not zero, generate PPG calibration data based on the PPG light leakage data, where the PPG calibration data is used to calibrate the PPG sensor.

[0192] Exemplarily, PD(LED1 calibration) = PD(LED1 measured) - PD(LED1 light leakage), where PD(LED1 calibration) is the PD data when LED1 is lit after calibration, and PD(LED1 measured) is the PD data when LED1 is lit measured.

[0193] Finally, after completing the light leakage detection or calibration, the wearable device or the control software can push the corresponding data to the cloud device for storage to facilitate real-time monitoring of the defective rate of the PPG sensor.

[0194] It should be noted that the above specific embodiments are only used to assist in understanding the present application and do not constitute a limitation on the PPG light leakage self-checking method of the present application. Based on this technical concept, more forms of simple transformations are within the protection scope of the present application.

[0195] In addition, please refer to Figure 5 , Figure 5 which is a schematic diagram of the device structure of the hardware operating environment involved in the PPG light leakage self-checking method in the embodiments of the present application.

[0196] The present application also provides a wearable device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the steps of the PPG light leakage self-checking method in the above embodiments.

[0197] Next, refer to Figure 5, which shows a schematic structural diagram of a wearable device suitable for implementing the embodiments of the present application. The wearable device in the embodiments of the present application may include, but is not limited to, such as smart watches, smart bracelets, smart helmets, smart glasses, smart collars, or any electronic device capable of implementing the above functions. Figure 5 The wearable device shown is merely an example and should not impose any limitations on the functions and usage scope of the embodiments of the present application.

[0198] As Figure 5 shown, the wearable device may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to the program stored in the read-only memory 1002 or the program loaded from the storage device 1003 into the random access memory 1004. In the random access memory 1004, various programs and data required for the operation of the wearable device are also stored. The processing device 1001, the read-only memory 1002, and the random access memory 1004 are connected to each other through a bus 1005. The input / output interface 1006 is also connected to the bus. Generally, the following systems may be connected to the input / output interface 1006: an input device 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD, Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the wearable device to communicate with other devices wirelessly or wiredly to exchange data. Although the figure shows a wearable device with various systems, it should be understood that it is not required to implement or have all the shown systems. More or fewer systems may be alternatively implemented or had.

[0199] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program codes for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device, or installed from the storage device 1003, or installed from the read-only memory 1002. When the computer program is executed by the processing device 1001, the above functions defined in the method of the embodiments disclosed in the present application are executed.

[0200] The wearable device provided by the present application adopts the PPG light leakage self-checking method in the above-mentioned embodiment, which can solve the technical problem that the traditional PPG light leakage detection depends on a strictly controlled darkroom environment and has low convenience. Compared with the prior art, the beneficial effects of the wearable device provided by the present application are the same as those of the PPG light leakage self-checking method provided by the above-mentioned embodiment, and other technical features in the wearable device are the same as those disclosed in the above-mentioned embodiment method, which will not be elaborated here.

[0201] It should be understood that each part disclosed in the present application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in a suitable manner in any one or more embodiments or examples.

[0202] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in the present application, and all should be covered by the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the above-mentioned claims.

[0203] In addition, the present application also provides a computer-readable storage medium having computer-readable program instructions (i.e., computer programs) stored thereon, and the computer-readable program instructions are used to execute the steps of the PPG light leakage self-checking method in the above-mentioned embodiment.

[0204] The computer-readable storage medium provided by the present application can be, for example, a USB flash drive, but is not limited to an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, system, or device, or any combination of the above. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical fiber, a portable compact disk read-only memory, an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium can be transmitted by any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0205] The above computer-readable storage medium can be included in the wearable device; or it can exist separately and not be assembled into the wearable device.

[0206] The above computer-readable storage medium carries one or more programs, which, when executed by a wearable device, cause the wearable device to: receive a PPG light leakage self-check instruction; obtain first optoelectronic data detected by an optoelectronic detector when a light source is turned on and second optoelectronic data detected when the light source is turned off, and determine PPG light leakage data based on the first optoelectronic data and the second optoelectronic data; determine a current monitoring scenario that the wearable device selects to start from multiple health index monitoring scenarios, and dynamically determine a current light leakage data threshold according to the current monitoring scenario, where the multiple health index monitoring scenarios include at least three of a heart rate monitoring scenario, a blood oxygen saturation monitoring scenario, a blood pressure monitoring scenario, and a respiratory rate monitoring scenario, and the current light leakage data thresholds determined for different health index monitoring scenarios are different; and determine that the PPG sensor has light leakage when the PPG light leakage data is greater than the current light leakage data threshold.

[0207] Computer program code for performing the operations of this application can be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, executed as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, by using an Internet service provider to connect through the Internet).

[0208] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a part of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, as well as combinations of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0209] The modules described in the embodiments of the present application can be implemented in software or in hardware. In some cases, the name of the module does not constitute a limitation on the unit itself.

[0210] The computer-readable storage medium provided by the present application stores computer-readable program instructions (i.e., computer programs) for performing the steps of the above-mentioned PPG light leakage self-check method, which can solve the technical problem that traditional PPG light leakage detection depends on a strictly controlled darkroom environment and has low convenience. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as those of the PPG light leakage self-check method provided by the above embodiment, and will not be elaborated here.

[0211] In addition, the embodiments of the present application further provide a computer program product, including a computer program, which when executed by a processor, implements the steps of the PPG light leakage self-check method in the above embodiment.

[0212] The computer program product provided by the present application can solve the technical problem that traditional PPG light leakage detection depends on a strictly controlled darkroom environment and has low convenience. Compared with the prior art, the beneficial effects of the computer program product provided by the embodiments of the present application are the same as those of the PPG light leakage self-check method provided by the above embodiment, and will not be elaborated here.

[0213] The above are only some embodiments of the present application, and thus do not limit the patent scope of the present application. Any equivalent structural transformation made under the technical concept of the present application by using the content of the specification and drawings of the present application, or any direct / indirect application in other related technical fields, is included in the patent protection scope of the present application.

Claims

1. A method for self-checking PPG light leakage, characterized in that, The PPG light leakage self-check method is applied to a wearable device. The wearable device is integrated with a PPG sensor, and the PPG sensor includes a photodetector and a light source. The method includes: Receiving a PPG light leakage self-check instruction; Obtaining first optoelectronic data detected by the photodetector when the light source is on and second optoelectronic data detected by the photodetector when the light source is off, and determining PPG light leakage data based on the first optoelectronic data and the second optoelectronic data; Determining a current monitoring scenario started by the wearable device selected from multiple health index monitoring scenarios. According to the current monitoring scenario, dynamically determine a current light leakage data threshold. Among them, multiple health index monitoring scenarios include at least three of a heart rate monitoring scenario, a blood oxygen saturation monitoring scenario, a blood pressure monitoring scenario, and a respiratory rate monitoring scenario. The current light leakage data thresholds determined for different health index monitoring scenarios are different; When the PPG light leakage data is greater than the current light leakage data threshold, it is determined that the PPG sensor leaks light.

2. The PPG light leakage self-checking method according to claim 1, characterized in that The step of dynamically determining the current light leakage data threshold according to the current monitoring scenario includes: Querying from a preset scenario mapping threshold table according to the current monitoring scenario to obtain the light leakage data threshold mapped by the current monitoring scenario; Taking the mapped light leakage data threshold as the current light leakage data threshold.

3. The PPG light leakage self-checking method according to claim 1, wherein The step of dynamically determining the current light leakage data threshold according to the current monitoring scenario includes: Dynamically detecting the current optical sensitivity CTR of the PPG sensor; Determining the current light source color of the light source corresponding to the current monitoring scenario according to the current monitoring scenario; Dynamically determining the current light leakage data threshold according to the current light source color and the current CTR.

4. The PPG light leakage self-checking method according to claim 3, characterized in that, The step of dynamically determining the current light leakage data threshold according to the current light source color and the current CTR includes: When the current light source color is green, dynamically calculate the product of the current CTR and 3.7%, calculate a first product result, and dynamically determine the current light leakage data threshold based on the dynamically calculated first product result; When the current light source color is red, dynamically calculate the product of the current CTR and 1.5%, calculate a second product result, and dynamically determine the current light leakage data threshold based on the dynamically calculated second product result.

5. The PPG light leakage self-inspection method according to claim 3 or 4, characterized in that, The step of determining the current light source color of the light source corresponding to the current monitoring scenario according to the current monitoring scenario includes: When the current monitoring scenario is a blood oxygen saturation monitoring scenario, determining that the current light source color of the light source corresponding to the current monitoring scenario is red; When the current monitoring scenario is a heart rate monitoring scenario, a blood pressure monitoring scenario, or a respiratory rate monitoring scenario, determining that the current light source color of the light source corresponding to the current monitoring scenario is green.

6. The PPG light leakage self-checking method according to any one of claims 1 to 4, characterized in that The wearable device is also integrated with an ambient light detection device. After the step of receiving the PPG light leakage self-check instruction, the method further includes: Obtain the ambient light data detected by the ambient light detection device within a sliding time window, and determine the degree of fluctuation of the ambient light data; In the case where the degree of fluctuation is the first degree of fluctuation, trigger the step of obtaining the first optoelectronic data detected by the photodetector when the light source is turned on; In the case where the degree of fluctuation is the second degree of fluctuation, output a preset ambient light fluctuation prompt, where the second degree of fluctuation is higher than the first degree of fluctuation.

7. The PPG light leakage self-checking method according to claim 6, wherein, The method further includes: In the case where the PPG light leakage data is less than or equal to the current light leakage data threshold and the PPG light leakage data is not zero, generate PPG calibration data according to the PPG light leakage data, where the PPG calibration data is used to calibrate the PPG sensor.

8. The PPG light leakage self-checking method according to claim 6, characterized in that, The photodetector includes a first photodetector and a second photodetector with different positions. The first optoelectronic data includes the third optoelectronic data detected by the first photodetector when the light source is turned on, and the fourth optoelectronic data detected by the second photodetector when the light source is turned on. The second optoelectronic data includes the fifth optoelectronic data detected by the first photodetector when the light source is turned off, and the sixth optoelectronic data detected by the second photodetector when the light source is turned off. The current light leakage data threshold includes a first light leakage data threshold dynamically determined based on the current monitoring scenario of the first photodetector, and a second light leakage data threshold dynamically determined based on the current monitoring scenario of the second photodetector; The step of determining the PPG light leakage data according to the first optoelectronic data and the second optoelectronic data includes: Determine the PPG light leakage data corresponding to the first photodetector according to the third optoelectronic data and the fifth optoelectronic data; Determine the PPG light leakage data corresponding to the second photodetector according to the fourth optoelectronic data and the sixth optoelectronic data; The step of determining that the PPG sensor leaks light in the case where the PPG light leakage data is greater than the current light leakage data threshold includes: In the case where the PPG light leakage data corresponding to the first photodetector is greater than the first light leakage data threshold, or the PPG light leakage data corresponding to the second photodetector is greater than the second light leakage data threshold, determine that the PPG sensor leaks light.

9. A wearable device, characterized in that, Includes: A memory, a processor, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, it implements the PPG light leakage self-checking method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium. When the computer program is executed by the processor, it implements the PPG light leakage self-checking method according to any one of claims 1 to 8.

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