Blood oxygen saturation detection method, device and equipment and readable storage medium

Abstract

The invention relates to an oxyhemoglobin saturation detection method, device and equipment and a readable storage medium, a light source and a light sensor of electronic equipment are utilized, spectral channel reading is performed in a mode that a user presses the light source, and a PPG signal and pressing force for a detected part of the user are determined based on the spectral channel reading; the blood oxygen saturation degree of the user is determined by adopting the blood oxygen saturation degree calculation model conforming to the pressing force of the user, non-invasive blood oxygen saturation degree measurement is achieved by combining configuration hardware and functions of the electronic equipment with proper algorithms and models, and convenience is brought to health management of the user.

Description

Technical Field

[0001] The present disclosure relates to the technical field of terminal devices, and in particular to a blood oxygen saturation detection method, device, equipment and readable storage medium. Background Art

[0002] Based on the different light absorption coefficients of human oxygenated hemoglobin and reduced hemoglobin in the red light spectral region and the infrared light spectral region, a sensor with dual light emitting diodes is used to emit red light and infrared light to illuminate the specific detection part of the user under test, and the absorbance changes of the two lights are detected respectively. The blood oxygen saturation of the user under test can be predicted through the ratio of the absorbance changes of the two lights and a specific blood oxygen saturation calculation model.

[0003] At present, blood oxygen saturation measurement usually requires the use of dedicated wearable devices, such as smart bracelets, smart watches, etc., which have high user costs and bring inconvenience to daily blood oxygen saturation detection. Summary of the invention

[0004] In view of this, in order to solve the above technical problems, the present disclosure provides a blood oxygen saturation detection method, device, equipment and storage medium.

[0005] According to a first aspect of an embodiment of the present disclosure, a method for detecting blood oxygen saturation is provided. The method is applied to an electronic device, the electronic device at least comprising a light source and a light sensor; the light source supports providing infrared light; the light sensor at least comprises a red light channel and an infrared light channel; the method comprises:

[0006] In response to the light source emitting light, obtaining a spectral channel reading generated by the light sensor when the measured part of the user presses the light source;

[0007] Determine the light intensity reading according to the spectral channel reading, and obtain the photoelectric pulse graph PPG signal corresponding to the red light and the infrared light;

[0008] According to a pre-established mapping relationship between the light intensity reading and the pressing force, a first pressing force generated when the measured part of the user corresponding to the light intensity reading presses the light source is obtained;

[0009] Determining a target calculation model corresponding to the first pressing intensity according to a pre-established correspondence between the pressing intensity and the blood oxygen saturation calculation model;

[0010] The target calculation model is used to obtain the blood oxygen saturation measurement result of the user according to the PPG signals corresponding to the red light and the infrared light.

[0011] According to a second aspect of an embodiment of the present disclosure, a blood oxygen saturation detection device is provided, which is applied to an electronic device, wherein the electronic device at least includes a light source and a light sensor; the light source supports providing infrared light; the light sensor includes at least a red light channel and an infrared light channel; the device includes:

[0012] A spectral channel reading acquisition module, configured to obtain, in response to the light source emitting light, a spectral channel reading generated by the light sensor when the user's measured part presses the light source;

[0013] A light intensity reading and signal component acquisition module, used to determine the light intensity reading according to the spectral channel reading, and obtain the photoelectric pulse graph PPG signal corresponding to the red light and the infrared light;

[0014] A pressing force determination module, configured to obtain, according to a pre-established mapping relationship between light intensity readings and pressing force, a first pressing force generated when a measured part of a user corresponding to the light intensity reading presses the light source;

[0015] a target calculation model determination module, configured to determine a target calculation model corresponding to the first pressing intensity according to a pre-established correspondence between the pressing intensity and the blood oxygen saturation calculation model;

[0016] The blood oxygen measurement result acquisition module is used to obtain the blood oxygen saturation measurement result of the user according to the PPG signal corresponding to the red light and the infrared light by using the target calculation model.

[0017] According to a third aspect of an embodiment of the present disclosure, there is provided an electronic device, including: a processor and a memory; the memory is used to store a computer program; the processor is used to call the computer program to implement the above-mentioned blood oxygen saturation detection method.

[0018] According to a fourth aspect of an embodiment of the present disclosure, a readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the above-mentioned blood oxygen saturation detection method is implemented.

[0019] The technical solution provided by the embodiments of the present disclosure may have the following beneficial effects:

[0020] The blood oxygen saturation detection method provided by the embodiment of the present disclosure utilizes the light source and light sensor of the electronic device itself, and obtains spectral channel readings by the user pressing the light source, determines the PPG signal and the pressing force for the measured part of the user based on the spectral channel readings, and adopts a blood oxygen saturation calculation model that conforms to the user's pressing force to determine the blood oxygen saturation of the user, thereby reducing the influence of external ambient light on the blood oxygen saturation measurement, and eliminating the need to wear a dedicated blood oxygen saturation measurement device. Instead, the configuration hardware and functions of the electronic device itself are combined with appropriate algorithms and models to achieve non-invasive blood oxygen saturation measurement, provide instant blood oxygen saturation monitoring results, save the cost of users to achieve health management, and bring convenience to users' health management.

[0021] It should be understood that the above general description and the following detailed description are only exemplary and explanatory and cannot limit the present disclosure. In addition, any embodiment of the present disclosure does not need to achieve all the above effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0023] Figure 1 is a flow chart of a method for detecting blood oxygen saturation according to an exemplary embodiment;

[0024] Figure 2 is a flow chart showing a method of obtaining PPG signals corresponding to red light and infrared light according to an exemplary embodiment;

[0025] Figure 3 is a flow chart showing a mapping relationship between a light intensity reading and a pressing force according to an exemplary embodiment;

[0026] Figure 4 is a flow chart showing another method of determining a mapping relationship between a light intensity reading and a pressing force according to an exemplary embodiment;

[0027] Figure 5 is a flow chart showing a corresponding relationship between a pressing force and a blood oxygen saturation calculation model according to an exemplary embodiment;

[0028] Figure 6 is a flow chart showing a method of determining the blood oxygen saturation of a user according to a blood oxygen calculation model according to an exemplary embodiment;

[0029] Figure 7 This is a flow chart of a blood oxygen saturation detection method using a mobile phone as an example of an electronic device;

[0030] Figure 8 The schematic diagram of a measurement posture of a user pressing a light source on a measured part is shown by taking a mobile phone as an example of an electronic device;

[0031] Fig. 9 is a structural schematic diagram of a blood oxygen saturation detection device according to an exemplary embodiment;

[0032] Fig.10 The present invention is a block diagram of a terminal device according to an exemplary embodiment. DETAILED DESCRIPTION

[0033] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0034] The terms used in this disclosure are for the purpose of describing specific embodiments only and are not intended to limit the disclosure. The singular forms of "a", "said" and "the" used in this disclosure and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0035] It should be understood that although the terms first, second, third, etc. may be used in the present disclosure to describe various information, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present disclosure, the first classification threshold may also be referred to as the second classification threshold, and similarly, the second classification threshold may also be referred to as the first classification threshold. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0036] The present disclosure provides a blood oxygen saturation detection method, which can be applied to electronic devices such as mobile phones, tablets, etc., and the electronic devices at least include a light source and a light sensor; wherein the light source is used to irradiate a measured part of a user, and supports providing red light and infrared light; the light sensor can include multiple different color channels, each color channel corresponds to a certain wavelength range or a specific color, and is used to record channel readings corresponding to light intensities or energies of different wavelengths in reflected light from the measured part of the user when the measured part of the user is placed on the light source, such as a red light channel, an infrared light channel, a green light channel, etc.

[0037] Figure 1is a flow chart of a method for detecting blood oxygen saturation according to an exemplary embodiment. Figure 1 As shown, the blood oxygen saturation detection method may include the following steps:

[0038] S101, in response to the electronic device being in a vital sign parameter monitoring state, obtaining a spectral channel reading generated by the light sensor when a measured part of a user presses the light source when the light source is emitting light;

[0039] The spectral channel readings indicate the intensity of light signals within different wavelength ranges, which may include different frequency bands such as visible light and infrared. Each spectral channel corresponds to a certain wavelength range, such as red, green, blue, etc. By simultaneously recording the readings of multiple channels, information corresponding to light within different wavelength ranges can be obtained.

[0040] The light source is used to illuminate the user's measured part. When the light source is turned on and the user's measured part covers the light source, the user's measured part will reflect and absorb the light emitted by the light source. At this time, different channels in the light sensor can capture the channel reading sequence of light intensity corresponding to different wavelengths of light in the reflected light from the measured part that changes with time; wherein, the light sensor can be a spectral sensor.

[0041] The user's measured parts may include but are not limited to fingers, wrists, arms, forehead, cheeks and other parts that can be placed on the light source.

[0042] For example, an electronic device is equipped with a health monitoring program or software. When the user enables the health monitoring program to measure blood oxygen saturation, the user can cover the light source with a finger when the light source is illuminated. At this time, the light sensor can collect the light intensity of different wavelengths provided by the light source and reflected by the user's finger, and convert it into corresponding spectral channel readings.

[0043] S102, determining the light intensity reading according to the spectral channel reading, and obtaining the PPG signals corresponding to the red light and the infrared light;

[0044] Light intensity readings refer to the energy or power density of light, the light energy transmitted per second over a specific area. Light of different wavelengths contribute differently to light intensity. According to the pre-set weight values ​​of different channel readings, the readings of each channel are weighted and combined to obtain a comprehensive overall light intensity reading, and the light intensity reading can be converted into corresponding units of lux or candela / square meter according to actual application requirements; among which, the weight values ​​of different channel readings are determined according to the wavelength range represented by the channel and the intensity response characteristics of light, and different channels usually have different weight values.

[0045] The PPG signal is a technical signal used for non-invasive blood flow and pulse waveform monitoring. It is based on the principle that light is transmitted and reflected in the skin when a light source irradiates the skin. It uses a light sensor to detect the intensity changes of light absorbed and reflected by the skin and converts it into an electrical signal, so that the PPG signal can be processed and analyzed to estimate physiological indicators such as blood oxygen saturation and heart rate. In the calculation of blood oxygen saturation, two wavelengths of light, red light and infrared light, are usually used for measurement.

[0046] Hemoglobin has different absorption characteristics under red light and infrared light wavelengths. Red light wavelengths are absorbed more by hemoglobin oxygenated hemoglobin (oxygenated hemoglobin), while infrared light wavelengths are absorbed more by deoxyhemoglobin (deoxygenated hemoglobin). When the oxygen saturation in the blood is high, red light is absorbed more by hemoglobin oxygenated hemoglobin, and infrared light is absorbed less by deoxyhemoglobin, so the red light signal is relatively strong and the infrared light signal is relatively weak. On the contrary, when the blood oxygen saturation is low, the red light signal is relatively weak and the infrared light signal is relatively strong. Therefore, based on the red light PPG signal and the infrared light PPG signal, the absorption characteristics of hemoglobin at different wavelengths can be used to infer the ratio of oxygenated hemoglobin and deoxygenated hemoglobin in the blood, thereby predicting the blood oxygen saturation.

[0047] Based on the above principle, since the spectral channel readings represent the intensity changes of light in different wavelength ranges after being reflected and absorbed by the user's measured part, based on the red light channel readings and the infrared light channel readings in the spectral channel readings, the first PPG signal corresponding to the red light and the second PPG signal corresponding to the infrared light can be obtained.

[0048] S103, according to a pre-established mapping relationship between the light intensity reading and the pressing force, obtaining a first pressing force generated when the measured part of the user corresponding to the light intensity reading presses the light source;

[0049] When the user presses the light source with different pressures on the measured part, the contact area between the measured part and the light source is different in size, and the absorption and reflection of light by the tissue of the measured part is affected accordingly, resulting in different light intensities entering the light sensor, and the generated spectral channel readings will change accordingly. Based on the correspondence between the spectral channel readings and the light intensity, the corresponding relationship between the light intensity readings and the pressing force can be determined by collecting the pressing force and the corresponding spectral channel readings as sample data, and performing data statistics and analysis on the sample data.

[0050] The mapping relationship between the light intensity reading and the pressing force is used to determine the first pressing force of the user's measured part pressing on the light source when the light intensity reading is determined based on the currently collected spectral channel reading. The mapping relationship can be determined by data fitting or machine learning based on the first sample data collected in advance, wherein the first sample data includes different pressing forces when the sample population presses the light source, and the light intensity reading determined based on the spectral channel reading under the pressing force; the electronic device that collects the first sample data and the electronic device currently detecting blood oxygen saturation are devices with the same configuration.

[0051] S104, determining a target calculation model corresponding to the first pressing intensity according to a pre-established correspondence relationship between the pressing intensity and the blood oxygen saturation calculation model;

[0052] When the user presses the light source at different pressures on the measured part, the different pressures will cause different degrees of tissue compression at the measured part, affecting the ability of light to penetrate the tissue and the degree of absorption. The obtained spectral channel readings are affected accordingly, thus affecting the blood oxygen saturation measurement. In order to more accurately predict the blood oxygen saturation, a blood oxygen saturation calculation model under different pressures is established to improve the accuracy of the calculation results.

[0053] The blood oxygen saturation calculation model is used to determine the user's blood oxygen saturation based on the PPG signal of the set wavelength determined in the aforementioned step S102. The calculation model can be established by analyzing a large amount of sample data collected in advance, using machine learning, data fitting, etc. The sample data includes relevant sample data collected when a sample population with different blood oxygen saturations presses the light source with different pressing strengths.

[0054] After determining the first pressing force of the measured part of the current user according to step S103, the first pressing force can be matched with the corresponding relationship between the pressing force and the blood oxygen saturation calculation model, and the blood oxygen saturation calculation model that meets the first pressing force can be used as the target calculation model.

[0055] S105, using the target calculation model, and obtaining a blood oxygen saturation measurement result of the user according to the PPG signals corresponding to the red light and the infrared light.

[0056] The target calculation model determines the blood oxygen saturation in a manner that depends on the light absorption characteristics and signal analysis technology, and may be a pre-established relationship model between blood oxygen saturation and R value, which is used to predict blood oxygen saturation according to the ratio R value of the red light PPG signal and the infrared light PPG signal. The R value is calculated based on the red light PPG signal and the infrared light PPG signal, and in the process of calculating the R value, the influence of environmental noise and light intensity can be reduced by dividing by the DC component of the PPC signal.

[0057] When the target calculation model is a relationship model between blood oxygen saturation and R value, the R value can be first calculated based on the AC component and DC component of the red light PPG signal and the infrared light PPG signal, and then the R value is input into the target calculation model to convert the R value into a corresponding blood oxygen saturation value; alternatively, when the target calculation model is a relationship model between blood oxygen saturation and the AC component and DC component of the red light and infrared light PPG signals, the acquired AC and DC components of the red light and infrared light PPG signals can be directly used as the input of the target model to obtain the output predicted blood oxygen saturation.

[0058] In the embodiments of the present disclosure, the light source and light sensor of the electronic device itself are utilized, and the spectral channel reading is obtained by the user pressing the light source. The PPG signal and the pressing force for the measured part of the user are determined based on the spectral channel reading, and the blood oxygen saturation calculation model that conforms to the user's pressing force is used to determine the blood oxygen saturation of the user, thereby reducing the influence of external ambient light on the blood oxygen saturation measurement. Without the need for additional hardware, the configuration hardware and functions of the electronic device itself are combined with appropriate algorithms and models to achieve non-invasive blood oxygen saturation measurement, provide instant blood oxygen saturation monitoring results, save the cost of users to achieve health management, and bring convenience to users' health management.

[0059] In some embodiments, the aforementioned electronic device may further include a light intensity sensor. When the light source of the electronic device is illuminated, a light intensity reading generated by the light intensity sensor is obtained when the user's measured part presses on the light source, and the above-mentioned blood oxygen saturation detection method is performed based on the light intensity reading.

[0060] In some embodiments, Figure 2 As shown, the acquisition of the photoelectric pulse graph PPG signal corresponding to the red light and the infrared light in the aforementioned step S102 may include the following implementation steps:

[0061] S201, obtaining a curve of a red light channel reading and an infrared light channel reading changing with time according to the spectral channel reading;

[0062] The spectral channel readings obtained based on the light sensor are the sequence of channel readings over a period of time when the user's measured part is pressed on the light source. Therefore, according to the reading sequence corresponding to the set wavelength of light, a curve of channel readings changing over time can be obtained. For blood oxygen saturation measurement, the set wavelength of light includes red light and infrared light, then curve 1 of the red light channel reading changing over time and curve 2 of the infrared light channel reading changing over time can be obtained.

[0063] S202, determining a first PPG signal corresponding to red light and a second PPG signal corresponding to infrared light according to a curve of the channel reading changing over time;

[0064] The AC component of the PPG signal corresponds to the change in blood flow caused by arterial pulsation, usually corresponding to the contraction and relaxation cycle of the heart. The DC component reflects the change in venous blood volume and other non-pulsating blood flow components, with a low frequency range, usually less than 0.5Hz. The spectral channel readings represent the absorption and reflection of light in different wavelength ranges at the user's measured part. The curve that changes with time can provide information related to blood absorption and scattering, reflecting the AC and DC components in the PPG signal.

[0065] Based on this, the curve of the spectral channel readings of the set wavelength changing with time can be directly determined as the PPG signal of the set wavelength; or, the curve of the spectral channel readings changing with time can be further processed to improve the signal quality, such as filtering, baseline drift correction, etc., and the processed curve is used as the PPG signal of the set wavelength. In the measurement of blood oxygen saturation, the set wavelength can usually be a combination of 660 nanometers and 940 nanometers, that is, the first PPG signal and the second PPG signal are determined based on the red light channel readings and the infrared light channel readings of the light sensor.

[0066] See also Figure 3 As shown, in some embodiments, the method may further include a step of pre-acquiring a mapping relationship between the light intensity reading and the pressing force. The mapping relationship between the light intensity reading and the pressing force described in the aforementioned step S103 may be obtained in the following manner:

[0067] S301, collecting spectral channel readings generated by the light sensor when a sample population presses the light source with different pressing intensities, counting pressing intensity samples of the sample population, and determining light intensity reading samples under different pressing intensities based on the spectral channel readings;

[0068] The sample population may include multiple groups of people of different ages and genders. When each sample population presses the light source of the electronic device with different pressing strengths, the spectral channel readings generated by the light sensor of the electronic device are counted respectively. A pressure sensor may also be used to collect the user's pressing strength, and the pressing strength and corresponding light intensity reading samples are counted to obtain a sample data set.

[0069] S302, performing data fitting according to the illumination intensity reading samples and the corresponding pressing forces, to obtain a mapping relationship between the illumination intensity readings and the pressing forces.

[0070] Data fitting refers to selecting an appropriate mathematical or statistical model, such as determining a function or curve, so that the model can describe the corresponding relationship of a set of data. Common data fitting methods include linear regression, polynomial fitting, nonlinear fitting, etc. By adjusting the model parameters, the gap between the model's predicted value and the actual observed value is minimized.

[0071] For example, polynomial fitting can be used to establish a polynomial function model according to the selected polynomial order, that is, f(x) = a0+a1x+a2x 2 +…+a n xn, where a0, a1, a2…a n are the polynomial coefficients to be estimated, x represents the light intensity reading, f(x) represents the corresponding pressing force, and the selected polynomial order can be determined by cross-validation and other methods; an error function for measuring the degree of model fit is defined, such as a residual sum of squares function, and based on the light intensity reading samples and the corresponding pressing force sample data set, a least squares method, gradient descent method, Newton method, etc. can be used for fitting, and the estimated value of the polynomial coefficients is determined by minimizing the error function.

[0072] In the disclosed embodiment, based on a large number of collected sample data sets, a mapping relationship between the light intensity reading and the actual pressure applied to the user's measured part is determined using data fitting, so that the model can adapt to new, unseen data and has a stronger predictive ability. When the light intensity reading is actually determined, the pressure applied to the user's measured part can be accurately obtained based on the mapping relationship, providing a data basis for subsequent blood oxygen saturation calculations.

[0073] In some embodiments, Figure 4 As shown, the mapping relationship between the light intensity reading and the pressing force described in the aforementioned step S103 can also be obtained in the following manner:

[0074] S401, collecting spectral channel readings generated by the light sensor when a sample population presses the light source with different pressing intensities, counting pressing intensity samples of the sample population, and determining light intensity reading samples under different pressing intensities based on the spectral channel readings;

[0075] S402, dividing the value of the pressing force into M discrete value intervals, establishing a mapping relationship between the light intensity reading and the discrete value intervals based on the light intensity reading samples, and determining the mapping relationship as a mapping relationship between the light intensity reading and the pressing force; M is greater than or equal to 2.

[0076] That is, the pressing force samples of the sample population when pressing the light source are divided into at least two value intervals, and a mapping relationship between the light intensity reading and the pressing force value interval is established based on the light intensity reading and the corresponding pressing force samples. Moreover, the pressing force value interval can be used as a division interval of different pressing forces corresponding to the blood oxygen saturation calculation model, and the number of pressing force value intervals is the same as the number of blood oxygen saturation calculation models.

[0077] For example, the pressure intensity P is divided into three value intervals: (0, N1], (N1, N2], and (N2, N3]. According to the light intensity reading and the corresponding pressure intensity sample, the mapping relationship between the light sensitivity reading and the three value intervals is determined, so that when determining the light sensitivity reading, the pressure intensity value interval to which it belongs can be determined based on the mapping relationship.

[0078] In the disclosed embodiment, the pressure force data is divided into discrete value intervals, which reduces the complexity of the problem, limits the change in light perception reading caused by the change in pressure force within the interval, reduces the propagation of errors, and makes it easier to process and implement the determination of the pressure force value based on the light perception reading.

[0079] In some embodiments, see Figure 5 As shown, the method may further include the step of pre-acquiring the corresponding relationship between the pressing force and the blood oxygen saturation calculation model. The corresponding relationship between the pressing force and the blood oxygen saturation calculation model described in the aforementioned step S103 may be acquired in the following manner:

[0080] S501, when the sample population presses the light source with different pressing forces, collecting spectral channel reading samples generated by the light sensor under the pressing forces, and recording the blood oxygen saturation of the sample population to obtain a sample data set;

[0081] The sample data set collected in this embodiment can be the same batch of data collected by the same device as the sample data required for determining the mapping relationship between the light intensity reading and the pressing force. When the sample population presses the light source with different pressing forces, the pressing force at this time, the spectral channel reading corresponding to the pressing force, and the blood oxygen saturation of the sample population are recorded, and the recorded data is used as the sample data set for determining the blood oxygen saturation calculation model. Among them, for the sample data set, the data can also be pre-processed, including data cleaning, removal of outliers, etc., to improve the quality of the sample data.

[0082] S502, performing data fitting according to the sample data set to obtain a blood oxygen saturation calculation model for a parameter R value under different pressure intensities; the R value is determined according to a spectral channel reading sample; the R value is used to represent the absorption ratio of red light and infrared light.

[0083] Classify according to the value range of the pressing intensity, and establish a calculation model of the blood oxygen saturation in the pressing intensity value range and the R value determined based on the spectral channel reading samples according to the spectral channel reading samples in different pressing intensity value ranges. The calculation model can be determined by data fitting such as linear regression, support vector regression, polynomial fitting, or machine learning, neural network, etc. In this embodiment, the calculation model can be determined by linear regression data fitting using the least squares method. The specific implementation can adopt the means in the relevant technology, which will not be elaborated in this disclosure.

[0084] In the disclosed embodiment, a blood oxygen saturation calculation model under different pressing pressures is determined based on a large number of collected sample data sets, and non-invasive and non-intrusive measurement is achieved by predicting blood oxygen saturation through spectral channel readings, thereby reducing the impact of pressing pressure on blood oxygen saturation measurement, reducing interference from ambient light, and improving measurement accuracy.

[0085] like Figure 6 As shown, in some embodiments, the aforementioned step S105 uses the target calculation model to obtain the blood oxygen saturation measurement result of the user according to the PPG signal corresponding to the red light and the infrared light, which can be achieved by the following method:

[0086] S601, obtaining an AC component and a DC component of the PPG signal corresponding to the red light and the infrared light;

[0087] Since the PPG signal is a composite signal of a DC component and an AC component, the two components can be separated from the PPG signal by utilizing the spectral characteristics of the signal or the overall waveform characteristics of the signal, such as the time domain waveform method, the frequency domain waveform method, the machine learning method, the wavelet transform method, etc. The specific component extraction method can be determined according to the signal characteristics of the PPG signal, such as the signal-to-noise ratio, signal characteristics, real-time requirements, etc. of the PPG signal.

[0088] S602, determining a parameter R value according to the AC component and the DC component; the R value is used to represent the absorption ratio of red light and infrared light;

[0089] The R value, as an evaluation index of blood oxygen saturation, can reflect the difference between the red light and infrared light channel readings, and is further used to estimate the level of blood oxygen saturation. The R value can be calculated as follows: the ratio of the AC component to the DC component of the red light is determined as the first component ratio; the ratio of the AC component to the DC component of the infrared light is determined as the second component ratio; and the ratio R value is determined based on the first component ratio and the second component ratio.

[0090] S603: Determine a blood oxygen saturation measurement result of the user according to the R value and a target calculation model related to the R value.

[0091] In this embodiment, the target calculation model is a relationship model between blood oxygen saturation and R value, and the corresponding blood oxygen saturation can be obtained by inputting the R value.

[0092] In the embodiment of the present disclosure, the R value, an evaluation index of blood oxygen saturation, is determined by acquiring the AC component and DC component of red light and infrared light, thereby reducing the influence of environmental noise and light intensity. Based on the established relationship model between blood oxygen saturation and R value, the user's blood oxygen saturation measurement is determined, thereby meeting the real-time requirements of blood oxygen saturation monitoring and providing convenience for the user's health monitoring.

[0093] In some embodiments, the acquisition of the AC component and the DC component of the PPG signal corresponding to the red light and the infrared light in step S601 may be implemented in the following manner:

[0094] Resampling each of the PPG signals; wherein the resampling of each signal uses the same sampling frequency;

[0095] According to the component extraction method of the resampled PPG signal, the AC component and the DC component of the resampled PPG signal are obtained.

[0096] Resampling refers to the process of converting a signal at one sampling rate into a signal at another sampling rate in digital signal processing. The sampling rate indicates the number of times a signal is sampled per second, also known as the sampling frequency. The basic principle of resampling is to change the sampling rate of a signal by methods such as interpolation or downsampling. Interpolation is a method of estimating new sampling points by linear or nonlinear interpolation between known sampling points, while downsampling is a method of deleting some sampling points according to a certain rule.

[0097] In this embodiment, the first PPG signal and the second PPG signal of red light are resampled at the same sampling rate to obtain a signal with uniform time intervals. The PPG signal can be resampled using a difference method according to the timestamp information of the PPG signal, so that the resampled first PPG signal and the second PPG signal have the same sampling frequency, and the time intervals between the sampling points are consistent. For example, the sampling rate is set to 150 Hz, and the first PPG signal and the second PPG signal are resampled in a linear interpolation method according to the timestamp information of the existing sampling points.

[0098] The signal component extraction method refers to a method for extracting the DC component and AC component of the signal from the PPG signal, which may include but is not limited to time domain waveform extraction, frequency domain waveform extraction, and wavelet transform extraction. For example, the signal-to-noise ratio of the resampled PPG signal is used as the basis for determination. For a PPG signal with a signal-to-noise ratio higher than a set threshold, the time domain waveform method may be used to extract the signal component, while for a PPG signal with a signal-to-noise ratio lower than the set threshold, the frequency waveform method may be used to extract the signal component.

[0099] The first PPG signal and the second PPG signal can select a suitable signal component extraction method according to the characteristics of the signal, and the signal component extraction methods can be different. For example, if the signal-to-noise ratio of the first PPG signal is higher than the set threshold and the signal-to-noise ratio of the second PPG signal is lower than the set threshold, the first PPG signal is extracted using the time domain waveform method and the second PPG signal is extracted using the frequency domain waveform method.

[0100] In the disclosed embodiment, a red light PPG signal and an infrared light PPG signal are determined by using the red light channel and infrared light channel reading sequences of the light sensor, and the two sets of signals are resampled using the same sampling rate, thereby improving signal quality and data processing efficiency. A signal component extraction method is determined based on the signal characteristics of the resampled PPG signal, thereby improving the signal's anti-noise performance and making the extracted signal components more accurate.

[0101] In some embodiments, in response to the component extraction method of the resampled PPG signal being a time domain waveform method extraction, the AC component and the DC component of the resampled PPG signal are obtained according to the component extraction method of the resampled PPG signal described in the above embodiment, which can be implemented in the following manner:

[0102] Detecting the peak and peak of the PPG signal to obtain a peak set and a peak valley set;

[0103] The DC component and the AC component are determined by using mean value calculation according to the peak-valley set and the peak value set.

[0104] Among them, the peak refers to the maximum point of the PPG signal. In a complete heartbeat cycle, the peak generally corresponds to the heart contraction period. By detecting and extracting the peak points in the PPG signal, the peak points are grouped into a set, and the set can include multiple peaks in a complete heartbeat cycle; the peak and valley represent the minimum point of the PPG signal, which usually corresponds to the heart diastole period. By detecting and extracting the peak and valley points in the PPG signal, the peak and valley points are grouped into a set, and the set can include multiple peaks and valleys in a complete heartbeat cycle.

[0105] Taking the resampled first PPG signal of red light as an example, after obtaining the peak set and the peak valley set of the PPG signal, the first average value of each peak valley value in the peak valley set can be determined as the DC component of the first PPG signal, and the difference between the second average value of each peak value in the peak set and the first average value can be determined as the AC component.

[0106] Alternatively, the average values ​​of corresponding points in the peak set and the peak-valley set can be calculated as the estimated value of the DC component, that is, each peak and the nearest peak-valley are taken as corresponding points, and the third average value obtained by adding the values ​​of the paired points and dividing by the number of paired points is used as the DC component of the PPG signal, and the fourth average value obtained by adding the difference between the peak value and the peak-valley of the paired points and dividing by the number of paired points is used as the AC component of the PPG signal.

[0107] The AC component and DC component of the PPG signal are determined according to the peak-valley set and the peak-valley set. The baseline drift can also be eliminated by using a detrending method, and then the average value of the remaining signal is extracted as the estimated value of the DC component. The average value of the signal after removing the DC component from the signal can be used as the AC component. It can be understood that the present disclosure does not limit the method of extracting PPG signal components according to the peak set and the peak-valley set, and a calculation method that is more in line with the signal characteristics can be selected according to actual conditions.

[0108] In the embodiment of the present disclosure, the mean calculation method is used to determine the AC component and DC component of the PPG signal, which meets the real-time requirements of data processing. The mean calculation removes noise and interference and improves the accuracy and stability of the extracted signal components.

[0109] In some embodiments, in response to the component extraction method of the resampled PPG signal being a time domain waveform method extraction, the method of extracting the component of the resampled PPG signal described in the above embodiment to obtain the AC component and the DC component of the resampled PPG signal may include the following steps:

[0110] Performing fast Fourier transform (FFT) processing on the resampled PPG signal to obtain frequency spectrum information of the resampled PPG signal;

[0111] According to the spectrum information, the energy value corresponding to the DC frequency is determined as the DC component, and the energy value corresponding to the set AC frequency range is determined as the AC component.

[0112] Fourier transform is an analysis tool that decomposes time domain signals into frequency domain signals. It is often used to perform spectrum analysis, filtering, noise reduction and other operations on signals. After converting the resampled PPG signal into a frequency domain signal, a spectrum diagram of the PPG signal can be obtained. The horizontal axis represents the frequency, and the vertical axis represents the amplitude or power spectral density of the signal. Based on the spectrum diagram, the intensity and relative proportion of different frequency components in the signal can be determined.

[0113] The DC component refers to the constant offset of the signal, which is usually located at the far left of the frequency axis, and the corresponding frequency is 0Hz, that is, the DC frequency can be taken as 0Hz, and the energy value corresponding to 0Hz in the spectrum diagram is determined as the DC component. The AC component refers to the changing part of the remaining signal after the DC component is removed from the signal. It is the alternating change of the signal in the frequency domain, which is usually caused by periodic fluctuations. In the process of measuring blood oxygen saturation, the AC frequency range is usually set to 0.5Hz-10Hz. For example, 0.5Hz-3Hz can be used as the set AC frequency range. The AC component within the set AC frequency range can be extracted by filtering, energy value averaging, etc.

[0114] In the disclosed embodiment, the frequency spectrum information of the signal is obtained by performing FFT processing on the PPG signal, and the AC component and DC component of the signal are extracted at different frequencies based on the frequency spectrum information, the energy within the noise frequency range is filtered out, and efficient calculation is achieved using a fast algorithm, which saves computing resources, meets the real-time requirements of signal processing, and suppresses noise interference.

[0115] In order to enable those skilled in the art to better understand the blood oxygen saturation measurement method provided by the present disclosure, the following describes the technical solution of the present disclosure by taking a mobile phone as an example of an electronic device. The mobile phone has a light source and a built-in light sensor, supports the provision of red light and infrared light sources, and the channels of the light sensor may include channels within the visible light wavelength range such as red light, green light, blue light, and infrared light channels.

[0116] When using the blood oxygen saturation measurement method to predict the user's blood oxygen saturation, the mobile phone or an electronic device with the same configuration as the mobile phone can be used to collect sample data, and the force model and blood oxygen saturation calculation model required by the measurement method can be established based on the sample data. Figure 7 As shown, the steps may include:

[0117] S701, when different people press the light source at different pressures on the measured part, the pressing pressure, blood oxygen saturation, spectral channel reading sequence generated by the light sensor, and light intensity determined based on the spectral channel reading sequence are collected as sample data;

[0118] The pressing force can be collected by a pressure sensor. For example, a pressure sensor can be set on the electronic device that collects sample data, so that the pressing force of the user can be measured when the user's finger presses the light source; or, a suitable force sensor can be selected and fixed on the user's measured part such as a finger, and the pressure value applied by the user's finger on the light source of the electronic device can be obtained based on the sensor and the supporting collection equipment. According to the preset weight values ​​of the different channel readings, the corresponding light intensity readings are determined based on the collected spectral channel readings.

[0119] like Figure 8 As shown, the user can place the measured part such as a finger on the rear light source of the mobile phone, covering the light source, and when different forces are applied to the light source, the spectral channel readings under the force and the user's blood oxygen saturation are recorded.

[0120] S702, establishing a corresponding relationship between the light intensity reading and the pressing force based on the sample data of the light intensity reading and the corresponding pressing force;

[0121] S703, based on the pressing intensity, the blood oxygen saturation and the spectral channel readings under the pressing intensity, establishing a blood oxygen saturation calculation model under different pressing intensity, wherein the blood oxygen saturation calculation model is a relationship model between the blood oxygen saturation and the R value, and the R value is determined according to the spectral channel readings;

[0122] Determine the AC component of the red light PPG signal based on the spectral channel reading sequence red With DC component red , and the AC component AC of the infrared light PPG signal Ir With DC component Ir , then the R value can be determined as follows:

[0123]

[0124] According to the blood oxygen saturation under different pressing intensities and the R value determined based on the spectral channel readings, the relationship model between the blood oxygen saturation and the R value under different pressing intensities is determined by data fitting.

[0125] For example, the pressing force P is divided into three discrete intervals: (0, n1], (n1, n2], (n2, n3), and different pressing force value intervals correspond to different relationship model parameters. An exemplary blood oxygen saturation calculation model under different pressing forces is:

[0126]

[0127] After the corresponding relationship between the light intensity reading and the pressing force, and the blood oxygen saturation calculation model under different pressing forces are established in advance, the blood oxygen saturation of the user to be tested can be predicted by using the above blood oxygen saturation detection method based on the corresponding relationship and the blood oxygen saturation calculation model under different pressing forces, such as Figure 7 The following detection steps may be included:

[0128] S704, in response to the mobile phone being in a blood oxygen saturation monitoring state, when the light source is turned on, obtaining a spectrum channel reading sequence generated when a finger of the user to be tested presses on the light source, and a light intensity reading determined according to the spectrum channel reading sequence;

[0129] S705, determining a second pressing force of the finger of the user to be tested pressing on the light source according to the corresponding relationship between the light intensity reading and the pressing force determined in step S702;

[0130] S706, determining a red light PPG signal and an infrared light PPG signal 2 according to the red light and infrared light channel reading sequences in the spectral channel readings;

[0131] For example, the red light channel reading changing over time curve, that is, the PPG signal 1 at a wavelength of 660 nanometers: PPG1 = {R1, R2, R3...Rn}, and the infrared light channel reading changing over time curve, that is, the PPG signal 2 at a wavelength of 9400 nanometers: PPG2 = {IR1, IR2, IR3...IRn}.

[0132] S707, resample PPG signal 1 and PPG signal 2 in an interpolation manner according to the timestamp information of the channel readings, and determine a signal component extraction method according to the signal-to-noise ratio of the two resampled PPG signals;

[0133] In this embodiment, the two PPG signals can be resampled by interpolation according to the timestamp to obtain a signal with a uniform time interval, such as a sampling rate of 150 Hz; according to the signal characteristics of the resampled PPG signal, a method for extracting the AC component and the DC component of the PPG signal at different wavelengths is selected.

[0134] The time domain waveform method is used for the PPG signal with a high signal-to-noise ratio. For example, the peak detection and the peak-to-valley detection can be performed on the PPG signal to obtain the peak set and the peak-to-valley set, and the AC component and the DC component can be calculated respectively according to the following method:

[0135] DC=mean{foot1,foot2,foot3,…,footn};

[0136] AC=mean{peak1,peak2,peak3,…,peakn}-mean{foot1,foot2,foot3,…,footn};

[0137] Among them, DC represents the direct current component, AC represents the alternating current component, {foot1, foot2, foot3, …, footn} represents the peak and valley set, {peak1, peak2, peak3, …, peakn} represents the peak set, and mean{} represents the average value.

[0138] The frequency domain waveform method can be used for PPG signals with a low signal-to-noise ratio. By performing FFT on the PPG signal, the energy value corresponding to a frequency of 0 Hz can be determined as the DC component, and the maximum value of the energy value corresponding to a frequency range of 0.5-3 Hz can be determined as the AC component.

[0139] S708 , extracting the AC component and the DC component of the resampled PPG signal 1 and PPG signal 2 respectively, and calculating the R value corresponding to the user to be tested.

[0140] S709, determining a blood oxygen saturation calculation model that satisfies the second pressing force determined in step S705, and determining the blood oxygen saturation of the user to be measured according to the R value corresponding to the user to be measured and the blood oxygen saturation calculation model.

[0141] In the disclosed embodiment, the light source and light sensor of the mobile phone are utilized, the light source is used as the detection light source and the user's finger is pressed on the light source, thereby reducing the influence of external ambient light on the measurement result, and determining the light intensity reading according to the obtained spectral channel reading to obtain the user's pressing force, and adopting a blood oxygen saturation calculation model that matches the user's pressing force, and obtaining the user's blood oxygen saturation based on the measured PPG signal of the user's measured part, and realizing non-invasive blood oxygen saturation measurement by utilizing the configuration hardware and functions of the mobile phone itself in combination with a suitable blood oxygen saturation calculation model without the need for additional hardware, providing instant blood oxygen saturation monitoring results, reducing interference factors on the measurement results, improving the measurement accuracy of blood oxygen saturation, and bringing convenience to the user's health management.

[0142] Corresponding to the above-mentioned embodiment of the blood oxygen saturation detection method, Fig. 9 is a schematic diagram of the structure of a blood oxygen saturation detection device according to an exemplary embodiment. Fig. 9 As shown, the device is applied to an electronic device, and the electronic device at least includes a light source and a light sensor; the light source supports providing infrared light; the light sensor at least includes a red light channel and an infrared light channel; the device includes: a spectral channel reading acquisition module 901, a light intensity reading and signal component acquisition module 902, a pressing force determination module 903, a target calculation model determination module 904 and a blood oxygen measurement result acquisition module 905;

[0143] A spectral channel reading acquisition module 901 is used to obtain a spectral channel reading generated by the light sensor when the user's measured part presses the light source in response to the light source emitting light;

[0144] The light intensity reading and signal component acquisition module 902 is used to determine the light intensity reading according to the spectral channel reading, and obtain the photoelectric pulse graph PPG signal corresponding to the red light and the infrared light;

[0145] A pressing force determination module 903, configured to obtain, according to a pre-established mapping relationship between light intensity readings and pressing force, a first pressing force generated when a user's measured part corresponding to the light intensity reading presses the light source;

[0146] A target calculation model determination module 904 is used to determine the target calculation model corresponding to the first pressing force according to a pre-established correspondence between the pressing force and the blood oxygen saturation calculation model;

[0147] The blood oxygen measurement result acquisition module 905 is used to obtain the blood oxygen saturation measurement result of the user according to the PPG signal corresponding to the red light and the infrared light by using the target calculation model.

[0148] In some embodiments, the light intensity reading and signal component acquisition module is specifically used to:

[0149] According to the spectral channel readings, obtaining a curve of the red light channel reading and the infrared light channel reading changing with time;

[0150] According to the curve of the channel reading changing with time, a first PPG signal corresponding to the red light and a second PPG signal corresponding to the infrared light are determined.

[0151] In some embodiments, the blood oxygen measurement result acquisition module is specifically used to:

[0152] Acquire an AC component and a DC component of the PPG signal corresponding to the red light and the infrared light;

[0153] Determining a parameter R value according to the AC component and the DC component; the R value is used to represent the absorption ratio of red light and infrared light;

[0154] The blood oxygen saturation measurement result of the user is determined according to the R value and a target calculation model related to the R value.

[0155] In some embodiments, the blood oxygen measurement result acquisition module, when used to acquire the AC component and the DC component of the PPG signal corresponding to the red light and the infrared light, includes:

[0156] Resampling each of the PPG signals; wherein the resampling of each signal uses the same sampling frequency;

[0157] According to the signal characteristics of the resampled PPG signal, a signal component extraction method is determined, and the AC component and the DC component are obtained based on the signal component extraction method.

[0158] In some embodiments, the blood oxygen measurement result acquisition module is used to determine the parameter R value according to the AC component and the DC component, including:

[0159] Determining a ratio of the AC component to the DC component of the red light as a first component ratio;

[0160] Determining a ratio of the AC component to the DC component of the infrared light as a second component ratio;

[0161] A ratio R value is determined based on the first component ratio and the second component ratio.

[0162] In some embodiments, the apparatus further comprises:

[0163] Collecting spectral channel readings generated by the light sensor when a sample group presses the light source with different pressing forces, and determining light intensity reading samples under different pressing forces;

[0164] Performing data fitting according to the light intensity reading samples and the corresponding pressing force to obtain a mapping relationship between the light intensity reading and the pressing force; or,

[0165] The value of the pressing force is divided into M discrete value intervals, and a mapping relationship between the light intensity reading and the discrete value intervals is established according to the light intensity reading sample, and the mapping relationship is determined as a mapping relationship between the light intensity reading and the pressing force; M is greater than or equal to 2.

[0166] In some embodiments, the apparatus further comprises:

[0167] When the sample population presses the light source with different pressing forces, spectral channel reading samples generated by the light sensor under the pressing forces are collected, and the blood oxygen saturation of the sample population is recorded to obtain a sample data set;

[0168] Data fitting is performed according to the sample data set to obtain a blood oxygen saturation calculation model for a parameter R value under different pressure intensities; the R value is determined according to a spectral channel reading sample; the R value is used to represent the absorption ratio of red light and infrared light.

[0169] The implementation process of the functions and effects of each unit in the above-mentioned device is specifically described in the implementation process of the corresponding steps in the above-mentioned method, and will not be repeated here.

[0170] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can refer to the partial description of the method embodiments. The device embodiments described above are only schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the disclosed solution. A person of ordinary skill in the art may understand and implement it without creative work.

[0171] The embodiment of the present disclosure also provides a terminal device. The terminal device includes: a memory and a processor. The memory stores processor executable instructions, and the processor is configured to execute the executable instructions in the memory to implement the steps of the blood oxygen saturation detection method provided above. In the embodiment of the present disclosure, the terminal device can be a display device such as a mobile phone, a tablet, etc. having a light source and a light sensor.

[0172] Fig.10 is a block diagram of a terminal device provided according to an exemplary embodiment. Fig.10 As shown, the terminal device 1000 may include one or more of the following components: a processing component 1002, a memory 1004, a power component 1006, a multimedia component 1008, an audio component 1010, an input / output (I / O) interface 1012, a sensor component 1014, a communication component 1016, and an image acquisition component.

[0173] The processing component 1002 generally controls the overall operation of the terminal device 1000, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 1002 may include one or more processors 1020 to execute instructions. In addition, the processing component 1002 may include one or more units to facilitate interaction between the processing component 1002 and other components. For example, the processing component 1002 may include a multimedia unit to facilitate interaction between the multimedia component 1008 and the processing component 1002.

[0174] The memory 1004 is configured to store various types of data to support operations on the terminal device 1000. Examples of such data include instructions for any application or method operating on the terminal device 1000, contact data, phone book data, messages, pictures, videos, etc. The memory 1004 may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as a static random access memory (SRAM), an electrically erasable programmable read-only memory (EEPROM), an erasable programmable read-only memory (EPROM), a programmable read-only memory (PROM), a read-only memory (ROM), a magnetic memory, a flash memory, a magnetic disk, or an optical disk.

[0175] The power supply component 1006 provides power to various components of the terminal device 1000. The power supply component 1006 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the terminal device 1000.

[0176] The multimedia component 1008 includes a screen that provides an output interface between the terminal device 1000 and the target object. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the target object. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.

[0177] The audio component 1010 is configured to output and / or input audio signals. For example, the audio component 1010 includes a microphone (MIC), and when the terminal device 1000 is in an operation mode, such as a call mode, a recording mode, and a speech recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 1004 or sent via the communication component 1016. In some embodiments, the audio component 1010 also includes a speaker for outputting audio signals.

[0178] The I / O interface 1012 provides an interface between the processing component 1002 and a peripheral interface unit, such as a keyboard, a click wheel, a button, etc.

[0179] The sensor component 1014 includes one or more sensors for providing various aspects of status evaluation for the terminal device 1000. For example, the sensor component 1014 can detect the open / closed state of the terminal device 1000, the relative positioning of components, such as the display screen and keypad of the terminal device 1000, and the sensor component 1014 can also detect the position change of the terminal device 1000 or a component, the presence or absence of contact between the target object and the terminal device 1000, the orientation or acceleration / deceleration of the terminal device 1000, and the temperature change of the terminal device 1000. For another example, the sensor component 1014 also includes a light sensor, which is arranged below the OLED display screen.

[0180] The communication component 1016 is configured to facilitate wired or wireless communication between the terminal device 1000 and other devices. The terminal device 1000 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 1016 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 1016 also includes a near field communication (NFC) unit to facilitate short-range communication. For example, the NFC unit can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0181] In an exemplary embodiment, the terminal device 1000 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components.

[0182] In an exemplary embodiment, the present disclosure also provides a readable storage medium, which stores executable instructions. The executable instructions can be executed by a processor of a terminal device to implement the steps of the blood oxygen saturation detection method provided above. The readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0183] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the disclosure disclosed herein. The present disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are to be considered exemplary only, and the true scope and spirit of the present disclosure are indicated by the above claims.

[0184] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for detecting blood oxygen saturation, characterized in that: Applied to electronic equipment, the electronic equipment at least includes a light source and a light sensor; the light source supports providing infrared light; the method includes: In response to the light source emitting light, obtaining a spectral channel reading generated by the light sensor when the measured part of the user presses the light source; Determine the light intensity reading according to the spectral channel reading, and obtain the photoelectric pulse graph PPG signal corresponding to the red light and the infrared light; According to a pre-established mapping relationship between the light intensity reading and the pressing force, a first pressing force generated when the measured part of the user corresponding to the light intensity reading presses the light source is obtained; Determining a target calculation model corresponding to the first pressing intensity according to a pre-established correspondence between the pressing intensity and the blood oxygen saturation calculation model; The target calculation model is used to obtain the blood oxygen saturation measurement result of the user according to the PPG signals corresponding to the red light and the infrared light.

2. The method according to claim 1, characterized in that The obtaining of PPG signals corresponding to red light and infrared light comprises: According to the spectral channel readings, obtaining a curve of the red light channel reading and the infrared light channel reading changing with time; According to the curve of the channel reading changing with time, a first PPG signal corresponding to the red light and a second PPG signal corresponding to the infrared light are determined.

3. The method according to claim 1, characterized in that: The using the target calculation model to obtain the blood oxygen saturation measurement result of the user according to the PPG signals corresponding to the red light and the infrared light includes: Acquire an AC component and a DC component of the PPG signal corresponding to the red light and the infrared light; Determining a parameter R value according to the AC component and the DC component; the R value is used to represent the absorption ratio of red light and infrared light; The blood oxygen saturation measurement result of the user is determined according to the R value and a target calculation model related to the R value.

4. The method according to claim 3, characterized in that The obtaining of the AC component and the DC component of the PPG signal corresponding to the red light and the infrared light includes: Resampling each of the PPG signals; wherein the resampling of each signal uses the same sampling frequency; According to the signal characteristics of the resampled PPG signal, a signal component extraction method is determined, and the AC component and the DC component are obtained based on the signal component extraction method.

5. The method according to claim 3, characterized in that: Determining the parameter R value according to the AC component and the DC component includes: Determining a ratio of the AC component to the DC component of the red light as a first component ratio; Determining a ratio of the AC component to the DC component of the infrared light as a second component ratio; A ratio R value is determined based on the first component ratio and the second component ratio.

6. The method according to claim 1, characterized in that The method further comprises: Collecting spectral channel readings generated by the light sensor when a sample group presses the light source with different pressing forces, and determining light intensity reading samples under different pressing forces; Performing data fitting according to the light intensity reading samples and the corresponding pressing force to obtain a mapping relationship between the light intensity reading and the pressing force; or, The value of the pressing force is divided into M discrete value intervals, and a mapping relationship between the light intensity reading and the discrete value intervals is established according to the light intensity reading sample, and the mapping relationship is determined as a mapping relationship between the light intensity reading and the pressing force; M is greater than or equal to 2.

7. The method according to claim 1, characterized in that The method further comprises: When the sample population presses the light source with different pressing forces, spectral channel reading samples generated by the light sensor under the pressing forces are collected, and the blood oxygen saturation of the sample population is recorded to obtain a sample data set; Data fitting is performed according to the sample data set to obtain a blood oxygen saturation calculation model for a parameter R value under different pressure intensities; the R value is determined according to a spectral channel reading sample; the R value is used to represent the absorption ratio of red light and infrared light.

8. A blood oxygen saturation detection device, characterized in that: Applied to electronic equipment, the electronic equipment at least includes a light source and a light sensor; the light source supports providing infrared light; the device includes: A spectral channel reading acquisition module, configured to obtain, in response to the light source emitting light, a spectral channel reading generated by the light sensor when the user's measured part presses the light source; A light intensity reading and signal component acquisition module, used to determine the light intensity reading according to the spectral channel reading, and obtain the photoelectric pulse graph PPG signal corresponding to the red light and the infrared light; A pressing force determination module, configured to obtain, according to a pre-established mapping relationship between light intensity readings and pressing force, a first pressing force generated when a measured part of a user corresponding to the light intensity reading presses the light source; a target calculation model determination module, configured to determine a target calculation model corresponding to the first pressing intensity according to a pre-established correspondence between the pressing intensity and the blood oxygen saturation calculation model; The blood oxygen measurement result acquisition module is used to obtain the blood oxygen saturation measurement result of the user according to the PPG signal corresponding to the red light and the infrared light by using the target calculation model.

9. An electronic device, characterized in that: include: Processor, memory; The memory is used to store computer programs; The processor is used to call the computer program to implement the blood oxygen saturation detection method according to any one of claims 1 to 7.

10. A readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the blood oxygen saturation detection method according to any one of claims 1 to 7 is implemented.

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