Blood oxygen measurement method, device and electronic equipment

Abstract

Embodiments of the present application provide a blood oxygen measurement method and device and electronic equipment, and relate to the technical field of blood oxygen measurement. The method comprises the following steps: acquiring an infrared signal, a red light signal and a green light signal; determining a target key point in the green light signal, mapping position information of the target key point in the green light signal to the infrared signal and the red light signal respectively to obtain a target key point in the infrared signal and a target key point in the red light signal; determining target blood oxygen characteristic values corresponding to the infrared signal and the red light signal respectively according to signal values corresponding to the target key point in the green light signal, the target key point in the infrared signal and the target key point in the red light signal respectively; and obtaining a blood oxygen saturation degree according to the target blood oxygen characteristic values corresponding to the infrared signal and the red light signal respectively. The present application uses the green light signal as an auxiliary to position the key point, improves the accuracy of the target key point in the red light signal and the infrared signal respectively, and improves the detection accuracy of the blood oxygen saturation degree.

Description

Technical Field

[0001] This application relates to the field of blood oxygen measurement technology, specifically to a blood oxygen measurement method, device, and electronic equipment. Background Technology

[0002] Oxygen saturation (SpO2) is the concentration of oxygen in the blood. It is an important physiological parameter of the respiratory and circulatory systems, describing the blood's ability to carry and transport oxygen. Human metabolism is a biological oxidation process, and the oxygen needed for metabolism enters the bloodstream through the respiratory system. The oxygen entering the bloodstream combines with deoxyhemoglobin (Hb) in red blood cells to form oxyhemoglobin (HbO2), which is then transported to various tissues and cells throughout the body. SpO2 is the percentage of HbO2 in the total hemoglobin volume of the blood, i.e., SpO2 = HbO2 / (HbO2 + Hb) * 100%. Normally, this percentage is approximately 98%.

[0003] Wearable non-invasive pulse oximetry is now widely used, calculating blood oxygen saturation by collecting light signals from reflective devices. However, reflective pulse signals, being weak biological signals, are extremely susceptible to interference. Even though subjects are required to remain still during the test to reduce movement-related interference, individual differences and measurement-related interference are unavoidable. In particular, factors such as the subject's health status, skin color, hair density, vein location, and the tightness of the device can all lead to inconsistent quality of the acquired PPG (photoplethysmography) signals, thus reducing the accuracy of blood oxygen measurement. Summary of the Invention

[0004] In view of the above problems, this application provides a blood oxygen measurement method, device and electronic device to solve the above technical problems.

[0005] In a first aspect, embodiments of this application provide a blood oxygen measurement method, which involves acquiring infrared signals, red light signals, and green light signals; determining target key points in the green light signal; mapping the position information of the target key points in the green light signal to the infrared signal and the red light signal respectively, thereby obtaining the target key points in the infrared signal and the target key points in the red light signal; determining the target blood oxygen feature values ​​corresponding to the infrared signal and the red light signal respectively based on the signal values ​​corresponding to the target key points in the green light signal, the infrared signal, and the red light signal; and obtaining blood oxygen saturation based on the target blood oxygen feature values ​​corresponding to the infrared signal and the red light signal respectively. This application uses green light signals as an auxiliary for key point positioning, thereby improving the accuracy of the target key points corresponding to the red light signal and the infrared signal, reducing the signal key point positioning error caused by factors such as the user's health status, skin color, hair density, vein position, and tightness of the clothing during measurement, and improving the detection accuracy of blood oxygen saturation.

[0006] Secondly, embodiments of this application provide a blood oxygen measurement device, the device comprising:

[0007] The acquisition module is used to acquire infrared signals, red light signals, and green light signals;

[0008] The key point localization module is used to determine the target key points in the green light signal, and map the position information of the target key points in the green light signal to the infrared signal and the red light signal respectively, so as to obtain the target key points in the infrared signal and the target key points in the red light signal;

[0009] The feature value determination module is used to determine the target blood oxygen feature value corresponding to the infrared signal and the red light signal respectively based on the signal values ​​corresponding to the target key points in the green light signal, the target key points in the infrared signal and the target key points in the red light signal;

[0010] The blood oxygen determination module is used to obtain blood oxygen saturation based on the target blood oxygen feature values ​​corresponding to the infrared signal and the red light signal, respectively.

[0011] Thirdly, embodiments of this application provide an electronic device, including the above-described blood oxygen measurement method or the above-described blood oxygen measurement device.

[0012] The blood oxygen measurement method, device, and electronic equipment provided in this application can solve the problem of reduced accuracy of blood oxygen measurement caused by inconsistent quality of acquired PPG signals in existing blood oxygen measurement methods. By using green light signals as an aid for key point positioning, and by improving the accuracy of the target key points corresponding to red light signals and infrared signals, the error in signal key point positioning caused by factors such as the user's health status, skin color, hair density, vein position, and tightness of the device during measurement is reduced, thereby improving the detection accuracy of blood oxygen saturation.

[0013] These or other aspects of this application will become more apparent in the following description of the embodiments. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 A schematic flowchart of the blood oxygen measurement method provided in the embodiments of this application is shown.

[0016] Figure 2 A flowchart illustrating the signal acquisition method provided in an embodiment of this application is shown.

[0017] Figure 3 A flowchart illustrating the multi-channel signal acquisition method provided in an embodiment of this application is shown.

[0018] Figure 4 A schematic flowchart of the peak and valley detection method provided in the embodiments of this application is shown.

[0019] Figure 5 A schematic flowchart of the blood oxygen measurement method based on pseudo-oxygen identification provided in the embodiments of this application is shown.

[0020] Figure 6 A schematic flowchart of the pseudo-oxygen identification method provided in the embodiments of this application is shown.

[0021] Figure 7 This paper illustrates a flowchart of another blood oxygen measurement method based on pseudo-oxygen identification provided in an embodiment of this application.

[0022] Figure 8 A schematic flowchart of another blood oxygen measurement method provided in an embodiment of this application is shown.

[0023] Figure 9A schematic diagram of the blood oxygen measurement device provided in an embodiment of this application is shown. Detailed Implementation

[0024] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0025] To enable those skilled in the art to better understand the solutions of this application, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0026] In the embodiments of this application, it should be noted that, in this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0027] Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0028] In the description of the embodiments of this application, the words "example" or "for example" are used to indicate exemplification, illustration, or description. Any embodiment or design described as "example" or "for example" in the embodiments of this application is not to be construed as being more preferred or having more advantages than another embodiment or design. The use of the words "example" or "for example" is intended to present relative concepts in a clear manner.

[0029] Furthermore, in the embodiments of this application, "multiple" refers to two or more. Therefore, in the embodiments of this application, "multiple" can also be understood as "at least two". "At least one" can be understood as one or more, such as one, two, or more. For example, including at least one means including one, two, or more, and is not limited to which ones are included. For example, including at least one of A, B, and C, then it could include A, B, C, A and B, A and C, B and C, or A and B and C.

[0030] It should be noted that in the embodiments of this application, "and / or" describes the relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. In addition, the character " / ", unless otherwise specified, generally indicates that the associated objects before and after it are in an "or" relationship.

[0031] As described in the background section, the quality of the acquired PPG signals varies due to factors such as the subject's health status, skin color, hair density, vein location, and the tightness of the fitting. Although signal quality assessment can currently be used to filter out high-quality signals from the acquired PPG signals, the different absorption rates of hemoglobin for red and infrared light, coupled with the difficulty in guaranteeing signal quality, make it challenging to identify the peak and trough signal points of the acquired PPG signals, resulting in signal point identification errors. Since the determination of blood oxygen saturation depends on the identified signal points, this introduces errors into the final measured blood oxygen saturation, reducing the accuracy of blood oxygen measurement.

[0032] Based on this, in order to reduce signal point identification errors and improve blood oxygen measurement accuracy, this application provides a blood oxygen measurement method, device, and electronic device. By using green light signals as an aid for key point positioning, and by improving the accuracy of the target key points corresponding to red light signals and infrared signals, the error in signal key point positioning caused by factors such as the user's health status, skin color, hair density, vein position, and tightness of the clothing during measurement is reduced, thereby improving the detection accuracy of blood oxygen saturation.

[0033] The technical methods in the embodiments of this application will now be described with reference to the accompanying drawings.

[0034] Figure 1 This is a schematic flowchart of a blood oxygen measurement method provided in an embodiment of this application. The blood oxygen measurement method shown can be used in wrist-worn blood oxygen measurement devices, such as smartwatches, smart bracelets, and other smart wearable devices with blood oxygen measurement functions, and can also be used in fingertip blood oxygen measurement devices, such as finger clip-on blood oxygen meters. Figure 1As shown, this blood oxygen measurement method includes at least steps S110 to S140, which are described in detail below:

[0035] Step S110: Acquire infrared signal, red light signal and green light signal.

[0036] Considering the absorption coefficient characteristics of the human body for different lights, the green PPG signal has a higher signal-to-noise ratio compared to the red and infrared PPG signals. The signal quality is less affected by factors such as the subject's health status, skin color, hair density, vein location, and tightness of the device, making it easier to identify signal points. Therefore, in this embodiment of the application, a green light sensor, a red light sensor, and an infrared sensor are set in the blood oxygen measurement device. The infrared sensor, red light sensor, and green light sensor are used to collect signals from the user being measured, obtaining infrared signals, red light signals, and green light signals. Optionally, a green light sensor, an infrared sensor, and a red light sensor can be separately installed in the blood oxygen measurement device; alternatively, an optical signal sensor can be installed in the blood oxygen measurement device, which integrates an infrared sensor, a green light sensor, and a red light sensor. The infrared sensor, red light sensor, and green light sensor in the optical signal sensor collect signals from the user being measured, obtaining infrared signals, red light signals, and green light signals; alternatively, an infrared-red light sensor and a green light sensor can be installed in the blood oxygen measurement device, wherein the infrared-red light sensor integrates an infrared sensor and a red light sensor. The infrared sensor, red light sensor, and green light sensor in the infrared-red light sensor collect signals from the user being measured, obtaining infrared signals, red light signals, and green light signals.

[0037] In some implementations, considering the different quality of PPG signals acquired at different measurement locations, at least two measurement points can be set to ensure the acquisition of better PPG signals. Each measurement point includes an infrared sensor, a red light sensor, and a green light sensor. Each measurement point acquires a candidate infrared signal, a candidate red light signal, and a candidate green light signal, respectively. The signal quality of the candidate infrared signal, candidate red light signal, and candidate green light signal acquired at each measurement point is evaluated to obtain the signal quality evaluation result of that measurement point. The candidate infrared signal, candidate red light signal, and candidate green light signal of the measurement point with the best signal quality evaluation result are determined as the infrared signal, red light signal, and green light signal, respectively.

[0038] Optionally, signal quality assessment can be performed using at least one of the following: signal variation characteristics, gravitational acceleration variation characteristics, and signal frequency domain characteristics, to obtain signal quality assessment results.

[0039] In some implementations, each measurement point may acquire an infrared signal, a red light signal, and a green light signal. Based on the infrared signal, red light signal, and green light signal acquired at the measurement point, steps S120 to S140 are executed to obtain the blood oxygen saturation at the measurement point.

[0040] In some implementations, considering that the signal quality of the green light signal is less affected by the measurement location, a green light sensor and at least two measurement points can be set up. Each measurement point includes an infrared sensor and a red light sensor. Each measurement point acquires a candidate infrared signal and a candidate red light signal, respectively. A green light signal is acquired through the green light sensor. The signal quality of the candidate infrared signal and the candidate red light signal acquired by each measurement point is evaluated to obtain the signal quality evaluation result of that measurement point. The candidate infrared signal and the candidate red light signal of the measurement point with the best signal quality evaluation result are determined as the infrared signal and the red light signal, respectively, thereby obtaining the infrared signal, the red light signal and the green light signal.

[0041] Step S120: Determine the target key points in the green light signal, and map the position information of the target key points in the green light signal to the infrared signal and the red light signal respectively, to obtain the target key points in the infrared signal and the target key points in the red light signal.

[0042] The target key points include peak signal points and trough signal points.

[0043] Considering that green light is absorbed by both oxyhemoglobin and deoxyhemoglobin compared to red light, green light provides a better signal and has a better signal-to-noise ratio than other light sources. Therefore, in this embodiment, green light is used as an auxiliary signal to locate key points in both infrared and red light signals. In some implementations, peak and trough detection is performed on the green light signal to determine the target key points within the green light signal.

[0044] In some implementations, red, infrared, and green light are shone into human tissues. Since the blood flow in veins and other body tissues is relatively constant, the absorption of light can be approximated as a constant. Arteries, however, expand periodically with the pulse, resulting in a periodic change in the total blood volume per unit volume. Consequently, the absorption of red, infrared, and green light by arteries varies periodically with the pulse, giving the red, infrared, and green light signals the same signal period but different signal amplitudes. This means that the positional information between the target key points in the red and infrared signals and the target key points in the green light signal is the same or satisfies a preset positional information mapping relationship. Therefore, the positional information of the target key points in the green light signal can be mapped onto the infrared and red light signals respectively, yielding the target key points in the infrared and red light signals.

[0045] Step S130: Determine the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red signal based on the signal values ​​corresponding to the target key points in the green light signal, the infrared signal, and the red light signal.

[0046] Among them, the blood oxygen characteristic value is used to characterize the blood perfusion index. In some implementations, it can be determined based on the ratio of the AC component to the DC component of the signal.

[0047] The signal value includes at least one of the signal amplitude and the signal width.

[0048] In some implementations, the AC and DC components of the signal values ​​corresponding to the target key points in the infrared signal and the target key points in the red light signal can be obtained based on the signal values ​​of the target key points in the infrared signal and the target key points in the red light signal, respectively. Based on the AC and DC components of the signal values ​​corresponding to the target key points in the infrared signal and the target key points in the red light signal, the blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal can be obtained. Based on the AC and DC components of the signal values ​​of the target key points in the green light signal, the blood oxygen characteristic value of the green light signal can be obtained. If the blood oxygen characteristic value of the green light signal meets the preset conditions, the blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal are determined as the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal, respectively. If the blood oxygen characteristic value of the green light signal does not meet the preset conditions, the blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal are corrected according to the blood oxygen characteristic value of the green light signal to obtain the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal, respectively.

[0049] The preset condition can be that the blood oxygen characteristic value of the green light signal is greater than or equal to a preset blood oxygen characteristic threshold, or the preset condition can be that the blood oxygen characteristic value of the green light signal is within a preset blood oxygen characteristic range.

[0050] Optionally, the blood oxygen feature value of the green light signal can be input into a preset correction model to obtain the target blood oxygen feature values ​​corresponding to the infrared and red light signals, respectively. The preset correction model can be a machine learning-based correction model or a neural network-based correction model.

[0051] Optionally, preset feature value mapping data can be queried based on the blood oxygen feature value of the green light signal to obtain the target blood oxygen feature values ​​corresponding to the infrared and red light signals respectively. The preset feature value mapping data includes the blood oxygen feature range values ​​of multiple green light signals, as well as the blood oxygen feature values ​​of the infrared and red light signals corresponding to the blood oxygen feature range values ​​of each green light signal.

[0052] Step S140: Obtain blood oxygen saturation based on the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal, respectively.

[0053] In some implementations, fitting parameters can be obtained based on the target blood oxygenation feature values ​​corresponding to the infrared and red light signals, and the fitting parameters.

[0054] For example, blood oxygen saturation can be obtained by A*(target blood oxygen characteristic value of red light signal / target blood oxygen characteristic value of infrared signal)^2 + B*(target blood oxygen characteristic value of red light signal / target blood oxygen characteristic value of infrared signal) + C. Here, A, B, and C are fitting parameters obtained beforehand through data fitting.

[0055] In some implementations, the optical density ratio can be obtained based on the target blood oxygen characteristic values ​​corresponding to the infrared and red light signals, and fitting parameters can be acquired. Blood oxygen saturation can then be obtained based on the fitting parameters and the optical density ratio. The optical density ratio characterizes the absorption ratio of hemoglobin to red and infrared signals. For example, blood oxygen saturation can be obtained by A*(optical density ratio)^2 + B*(optical density ratio) + C, where A, B, and C are fitting parameters obtained beforehand through data fitting.

[0056] In some embodiments, to improve the accuracy of blood oxygen measurement, the red light signal, infrared signal, and green light signal acquired at each sampling moment within a preset time period can be processed using steps S120 to S140 to obtain candidate blood oxygen saturation at each sampling moment, forming a set of candidate blood oxygen saturation within the preset time period. Outlier filtering is then performed on the candidate blood oxygen saturation in the set to filter out abnormal candidate blood oxygen saturation, resulting in the remaining candidate blood oxygen saturation. The final blood oxygen saturation is then determined based on the remaining candidate blood oxygen saturation. The preset time period can be 1 minute, 2 minutes, etc., and this embodiment does not specifically limit it.

[0057] Optionally, in blood oxygen measurement, the preset duration is divided according to a preset sampling period to form at least one sampling moment. At each sampling moment, red light, infrared light, and green light are emitted to the human skin, and the red light signal, infrared signal, and green light signal at that sampling moment are collected. For the red light signal, infrared signal, and green light signal at each sampling moment, the above steps S120 to S140 are performed to obtain the candidate blood oxygen saturation at that sampling moment. The candidate blood oxygen saturation at each sampling moment within the preset duration is summarized to obtain the set of candidate blood oxygen saturation within the preset duration.

[0058] Optionally, outlier filtering can be performed on the candidate blood oxygen saturation set using 3sigm to filter out abnormal candidate blood oxygen saturation values.

[0059] Optionally, the mean, median, or mode of the remaining candidate oxygen saturation values ​​can be used to determine the oxygen saturation level.

[0060] The blood oxygen measurement method provided in this application uses green light signals as an aid for key point localization. By improving the accuracy of the target key points corresponding to red light signals and infrared signals, it reduces the signal key point localization error caused by factors such as the user's health status, skin color, hair density, vein position, and tightness of the clothing during measurement, thereby improving the detection accuracy of blood oxygen saturation.

[0061] Considering factors such as the subject's health status, skin color, hair density, vein location, and the tightness of the fitting, the quality of the acquired PPG signals can vary, leading to errors in the final calculated blood oxygen saturation and reducing the accuracy of blood oxygen calculation. Therefore, in some implementations, to reduce the error in blood oxygen saturation calculation and improve its accuracy, signal quality assessment can be performed on the acquired red, infrared, and green light signals during signal acquisition. Only red, infrared, and green light signals with better quality are processed using steps S120-S140. Thus, by detecting the signal quality, the error in blood oxygen saturation calculation is reduced, and the accuracy of blood oxygen calculation is improved.

[0062] like Figure 2 As shown, Figure 2 This is a schematic flowchart of a signal acquisition method provided in an embodiment of this application. The signal acquisition method shown includes steps S211A to S212A:

[0063] Step S211A: Evaluate the signal quality of the optical signal to obtain the signal quality of the optical signal.

[0064] The optical signals include red light signals, infrared signals, and green light signals.

[0065] In some implementations, at least one of the following can be obtained: the variation characteristics of the optical signal, the variation characteristics of gravitational acceleration, and the frequency domain characteristics of the optical signal. The signal quality of the optical signal can be determined based on at least one of the following: the variation characteristics of the optical signal, the variation characteristics of gravitational acceleration, and the frequency domain characteristics of the optical signal.

[0066] The characteristics of light signal changes include the variation in the signal value of the red light signal. The attenuation of light over time in pulsating arterial blood can exhibit a fluctuating curve. The AC and DC components of the light signal are determined based on the peaks and troughs of this curve. Generally, the peak and trough positions of this curve are within a certain normal range. If a user wears a wearable device while in motion, the contact position between the diode and the skin changes continuously with the user's movement, and may even detach from the skin. This means that the attenuation of the light signal also includes attenuation in the air between the diode and the skin, resulting in the peak and trough positions of the light attenuation over time potentially deviating significantly from the normal range. Therefore, the determined AC and DC components of the infrared signal, the AC and DC components of the red light signal, the AC and DC components of the green light signal may be inaccurate, leading to errors in the final obtained blood oxygen saturation reading. The light signal includes any one of the red, infrared, and green light signals.

[0067] Optionally, the signal quality of the optical signal can be obtained based on its variation characteristics. For example, after acquiring the peak and trough positions of multiple optical signals over a period of time as light attenuates, the proportion of these peak and trough positions within the normal range is determined to obtain the variation characteristics of the optical signal. Understandably, if the variation characteristics of the optical signal are less than a preset threshold, the signal quality of the optical signal during that time period is determined to be poor; if the variation characteristics are greater than or equal to the preset threshold, the signal quality of the optical signal during that time period is determined to be good.

[0068] Optionally, the characteristics of gravitational acceleration changes can be obtained using sensors such as three-axis gyroscopes or six-axis gyroscopes. For example, using a three-axis gyroscope, when a user is moving, their center of gravity may constantly shift up and down, causing the Z-axis acceleration measurement to change within a short period. Since users consume blood oxygen during exercise, a user with normal blood oxygen saturation might be measured as having low oxygen levels, leading to misjudgment. Therefore, if the Z-axis acceleration measurement changes multiple times within a short period, it can be determined that the optical signal quality is poor during that time, making it unsuitable for blood oxygen measurement. Measurement should be performed only after the Z-axis acceleration measurement stabilizes within a short timeframe.

[0069] Optionally, the frequency domain characteristics of the optical signal may specifically include the frequency domain characteristics of the red light signal, the infrared signal, and the green light signal. Both the red and infrared signals are located in the near-infrared region, and their frequency domains are within specific frequency ranges. If the proportion of light signals whose frequency domains are outside this specific frequency range in the optical signal received by the optical receiving sensor in the wearable device exceeds a set proportion, it indicates that the signal quality of the optical signal during that period is poor. Therefore, the wearable device can perform blood oxygen measurement if the proportion of light signals whose frequency domains are outside this specific frequency range in the optical signal received by the optical receiving sensor is less than or equal to a set proportion.

[0070] Step S212A: Based on the signal quality of the optical signal, filter out the effective optical signal from the optical signal and obtain the red light signal, infrared signal and green light signal from the effective optical signal.

[0071] In some implementations, based on the signal quality of the optical signal, optical signals with poor signal quality are filtered out, and the remaining optical signals are determined as valid optical signals, thereby acquiring the red light signal, infrared signal, and green light signal from the valid optical signals.

[0072] In some implementations, based on Figure 2 The provided signal acquisition method, in order to further improve signal quality and reduce blood oxygen saturation errors, can set at least two measurement points. Each measurement point includes an infrared sensor, a red light sensor, and a green light sensor. Signal acquisition is performed at each measurement point to obtain the infrared information, red light signal, and green light signal of that measurement point, forming candidate light signals for that point. The quality of each candidate light signal is evaluated to obtain the final light signal based on the signal quality of each candidate light signal, and then... Figure 2 The provided signal acquisition method performs quality assessment on the optical signal at each sampling time to obtain a valid optical signal, and acquires the red light signal, infrared signal, and green light signal from the valid optical signal. The candidate optical signal can be an optical signal containing red light, infrared signal, and green light signal collected from a measurement point in a blood oxygenation measuring device equipped with a green light sensor. For example, the blood oxygenation measuring device can be a wrist-worn blood oxygenation measuring device.

[0073] Understandably, at each sampling time, the infrared sensor, red light sensor, and green light sensor at each measurement point collect the light signal at that measurement point, forming candidate light signals for that measurement point. Each candidate photoelectric information is obtained through the infrared sensor, red light sensor, and green light sensor at that measurement point. Since the location of each measurement point is different, the quality of the collected candidate light signals varies. To reduce the probability of false oxygen generation, it is necessary to determine the candidate light signal with the best signal quality from the candidate light signals of multiple measurement points.

[0074] like Figure 3, Figure 3 This is a flowchart illustrating a multi-channel signal acquisition method provided in an embodiment of this application. The multi-channel signal acquisition method shown includes steps S211B to S215B:

[0075] Step S211B: Collect at least two candidate optical signals.

[0076] Step S212B: Evaluate the quality of each candidate optical signal to obtain the signal quality of each candidate optical signal.

[0077] In some implementations, the quality of each candidate optical signal can be evaluated according to the above step S211A to obtain the signal quality of each candidate optical signal.

[0078] In some implementations, the green light signal in each candidate optical signal can be obtained by following the above step S211A to obtain the signal quality of the green light signal in each candidate optical signal, and the signal quality of the green light signal in each candidate optical signal can be determined as the signal quality of the candidate optical signal.

[0079] Step S213B: Based on the signal quality of each candidate optical signal, determine the optical signal used for blood oxygen measurement from each candidate optical signal.

[0080] In some implementations, the candidate optical signal with better signal quality can be determined as the optical signal based on the signal quality of each candidate optical signal.

[0081] Step S214B: Evaluate the signal quality of the optical signal to obtain the signal quality of the optical signal.

[0082] In some embodiments, the optical signal can be evaluated according to the above step S211A to obtain the signal quality of the optical signal. The embodiments of this application will not be described in detail here.

[0083] Step S215B: Based on the signal quality of the optical signal, filter out the effective optical signal from the optical signal and obtain the red light signal, infrared signal and green light signal from the effective optical signal.

[0084] In some implementations, the red light signal, infrared signal and green light signal in the effective optical signal can be obtained by referring to the above step S212A. The embodiments of this application will not be described in detail here.

[0085] Considering that green light signals have a higher signal-to-noise ratio than red light and infrared PPG signals, making signal point identification easier, in some implementations, peak and trough detection is performed on the green light signal to determine the target key points in the green light signal. According to a preset position mapping relationship, the position information of the target key points in the green light signal is mapped to the infrared signal and red light signal respectively, thus obtaining the target key points in the infrared signal and the target key points in the red light signal. In this way, the key point positioning of the infrared signal and the red light signal is realized by using the green light signal as auxiliary information, improving the accuracy of key point positioning of the infrared signal and the red light signal, thereby reducing the error of blood oxygen saturation.

[0086] The preset position mapping relationships include a preset position mapping relationship between green light signals and infrared signals, and a preset position mapping relationship between green light signals and red light signals. Specifically, the position mapping relationship between green light signals and infrared signals indicates the mapping relationship between the position information of the signal points of the green light signals and the signal points of the infrared signals, while the position mapping relationship between green light signals and red light signals indicates the mapping relationship between the position information of the signal points of the green light signals and the signal points of the red light signals.

[0087] In some implementations, a large number of sample infrared signals, sample red light signals, and sample green light signals can be collected in advance. By obtaining the position information of the signal points at the same sampling time in the sample infrared signals, sample red light signals, and sample green light signals, a positional mapping relationship between the green light signal and the infrared signal, and a positional mapping relationship between the green light signal and the red light signal can be established.

[0088] In an optional implementation, the position information of the target key point in the green light signal can be mapped to the infrared signal according to the preset position mapping relationship between the green light signal and the infrared signal to obtain the target key point in the infrared signal; the position information of the target key point in the green light signal can be mapped to the red light signal according to the preset position mapping relationship between the green light signal and the red light signal to obtain the target key point in the red light signal.

[0089] The target key points include peak signal points and trough signal points. Taking infrared signals as an example, the position information of the peak signal points in the green light signal can be mapped to the infrared signal according to the preset position mapping relationship between the green light signal and the infrared signal to obtain the peak signal points in the infrared signal. Similarly, the position information of the trough signal points in the green light signal can be mapped to the infrared signal to obtain the trough signal points in the infrared signal. The method for determining the target key points in the red light signal is similar to that for the infrared signal, and will not be described in detail here.

[0090] In an optional implementation, peak and trough detection can be performed on the green light signal based on its amplitude and width using a preset signal threshold. This yields peak and trough signal points in the green light signal, which are then identified as key target points within the green light signal. The signal threshold includes an amplitude threshold and a width threshold.

[0091] In some implementations, considering that the amplitude and width of the green light signal collected by different users vary during peak and trough detection, and that the amplitude and width of the green light signal collected by the same user vary in different seasons and wearing conditions, using the same bandwidth and amplitude signal threshold for peak and trough detection for all green light signals may cause errors in the location information of the detected peak and trough signal points, thereby increasing the measurement error of blood oxygen saturation. Therefore, based on the statistical characteristics of the green light signal value, a signal threshold for the green light signal can be determined. Peak and trough detection is then performed based on the signal value of each sampling point in the green light signal and the signal threshold to obtain the peak and trough signal points in the green light signal. These peak and trough signal points are then identified as key target points in the green light signal.

[0092] like Figure 4 As shown, Figure 4 This is a schematic flowchart of the peak and trough detection method provided in the embodiments of this application. The peak and trough detection method shown includes steps S221 to S224:

[0093] Step S221: Statistical analysis is performed on the signal values ​​of each sampling point in the green light signal to obtain the statistical characteristics of the green light signal.

[0094] Among them, the statistical characteristics of the signal value include any one of the signal value mean, signal value mode, and signal value median.

[0095] The signal value includes amplitude and width.

[0096] Step S222: Determine the signal threshold of the green light signal based on the statistical characteristics of the signal value.

[0097] Among them, the signal thresholds include the trough signal threshold and the peak signal threshold.

[0098] In some implementations, the signal threshold of the green light signal can be obtained based on the statistical characteristics of the signal value and preset threshold data. The preset threshold data includes multiple signal value ranges and the signal threshold corresponding to each signal value range.

[0099] For example, taking the signal value as amplitude and the statistical feature as average value, the preset threshold data can be queried based on the average amplitude value to obtain the target amplitude range where the average amplitude value is located, and the signal threshold corresponding to the target amplitude range can be determined as the signal threshold of the green light signal.

[0100] In some implementations, the signal threshold of the green light signal can be obtained based on the statistical characteristics of the signal value and a preset threshold prediction model. The preset threshold prediction model can be a mathematical prediction model, a machine learning prediction model, or a neural network prediction model.

[0101] Step S223: Combine the signal values ​​of each sampling point in the green light signal with the signal threshold to determine the peak signal point and the trough signal point of the green light signal.

[0102] In some implementations, the signal value of each sampling point in the green light signal can be compared with a signal threshold. If the signal value of the sampling point meets the peak signal threshold in the signal threshold, the sampling point is determined as a peak signal point. If the signal value of the sampling point meets the trough signal threshold in the signal threshold, the sampling point is determined as a trough signal point. If the signal value of the sampling point does not meet either the peak signal threshold or the trough signal threshold in the signal threshold, the signal value of the next sampling point is compared with the signal threshold. This process continues until every sampling point of the green light signal in the current time range has been traversed, thus obtaining the peak signal point and trough signal point of the green light signal in the current time range.

[0103] Step S224: The peak and trough signal points of the green light signal are identified as key target points in the green light signal.

[0104] This application embodiment uses green light signal as auxiliary information to realize key point positioning of infrared and red light signals, improve the accuracy of key point positioning of infrared and red light signals, and thus reduce the error of blood oxygen saturation.

[0105] When blood oxygen measurement methods are used in wrist-based blood oxygen measurement devices, the presence of both veins and arteries in the wrist means that during data acquisition, both arterial and venous hemoglobin are detected by the red and infrared signals. This results in a large difference in the blood oxygen characteristic values ​​of the red and infrared signals, leading to an error between the calculated and actual blood oxygen saturation. This is known as pseudo-oxygenation, which includes pseudo-hypoxia and pseudo-normoxia. Pseudo-hypoxia is characterized by a gold standard value that is actually within the normal oxygen range (95-100), but the measured value is a deoxygenated value (below 95). Similarly, pseudo-normoxia is characterized by a gold standard value that is actually within the normal deoxygenated range (75-95), but the measured value is a normal oxygen range (above 95). Therefore, to improve the accuracy of blood oxygen saturation measurement, in some implementations, false oxygen identification can be performed based on the blood oxygen characteristic values ​​of the green light signal, the infrared signal, and the red light signal. If false oxygen exists, the blood oxygen characteristic values ​​of the red light signal and the infrared signal are corrected to obtain the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal, respectively. Based on the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal, the blood oxygen saturation is obtained. If false oxygen does not exist, the blood oxygen saturation is obtained based on the blood oxygen characteristic values ​​of the red light signal and the infrared signal.

[0106] like Figure 5 As shown, Figure 5 This is a schematic flowchart of the blood oxygen measurement method based on spurious oxygen identification provided in the embodiments of this application. The blood oxygen measurement method based on spurious oxygen identification shown includes steps S510 to S570:

[0107] Step S510: Acquire infrared signal, red light signal and green light signal, perform peak and trough detection on green light signal, and determine key target points in green light signal.

[0108] In some implementations, infrared signals, red light signals, and green light signals can be obtained according to the above step S110, which will not be described in detail in the embodiments of this application.

[0109] In some implementation methods, reference may be made to Figure 2 The provided signal acquisition method acquires infrared signals, red light signals, and green light signals, which will not be described in detail in the embodiments of this application.

[0110] In some implementation methods, reference may be made to Figure 3 The provided multi-channel signal acquisition method acquires infrared signals, red light signals, and green light signals, which will not be described in detail in the embodiments of this application.

[0111] In some implementations, the peak and trough detection of the green light signal can be performed with reference to the above step S120 to determine the target key points in the green light signal. The embodiments of this application will not be described in detail here.

[0112] In some implementation methods, reference may be made to Figure 4 The provided peak and valley detection method performs peak and valley detection on the green light signal to determine the target key points in the green light signal. The embodiments of this application will not be described in detail here.

[0113] Step S520: Map the location information of the target key points in the green light signal to the infrared signal and the red light signal respectively to obtain the target key points in the infrared signal and the target key points in the red light signal.

[0114] In some implementations, the target key points in the infrared signal and the target key points in the red light signal can be obtained according to the above step S120. The embodiments of this application will not be described in detail here.

[0115] Step S530: Determine the blood oxygen characteristic value of the green light signal, the blood oxygen characteristic value of the infrared signal, and the blood oxygen characteristic value of the red light signal based on the signal values ​​corresponding to the target key points in the green light signal, the target key points in the infrared signal, and the target key points in the red light signal.

[0116] In some implementations, the blood oxygen characteristic value can be obtained based on the ratio between the DC and AC components of the optical signal.

[0117] In some implementations, based on the signal values ​​corresponding to the target key points in the green light signal, the target key points in the infrared signal, and the target key points in the red light signal, the DC and AC components corresponding to the green light signal, the infrared signal, and the red light signal are obtained. Based on the DC and AC components corresponding to the green light signal, the infrared signal, and the red light signal, the blood oxygen characteristic values ​​are obtained.

[0118] Optionally, the DC and AC components of the optical signal can be determined based on the signal values ​​at the peak and trough points of the optical signal, and the blood oxygen characteristic value of the optical signal can be obtained through the AC / DC component.

[0119] For example, taking the green light signal as an example, the signal values ​​of the peak signal points and the trough signal points in the green light signal are determined based on the signal values ​​of the target key points in the green light signal. The DC component and AC component of the green light signal are determined based on the signal values ​​of the peak signal points and the trough signal points in the green light signal. The blood oxygen characteristic value of the green light signal is obtained through the AC component / DC component.

[0120] Step S540: Based on the blood oxygen characteristic values ​​of the green light signal, the infrared signal, and the red light signal, false oxygen is identified to determine whether false oxygen exists.

[0121] In some implementations, a first optical density ratio between the infrared signal and the red signal can be calculated based on the blood oxygen characteristic values ​​of the green signal, the infrared signal, and the red signal; a second optical density ratio between the green signal and the infrared signal can be calculated; and a third optical density ratio between the green signal and the red signal can be calculated. False oxygen can then be identified based on the first, second, and third optical density ratios to determine whether false oxygen exists.

[0122] like Figure 6 As shown, Figure 6 This is a flowchart illustrating the false oxygen identification method provided in this application embodiment. The false oxygen identification method shown includes steps S541 to S543:

[0123] Step S541: Based on the blood oxygen characteristic values ​​of the green light signal, the infrared signal, and the red light signal, the second optical density ratio and the third optical density ratio are obtained.

[0124] In some implementations, a first optical density ratio between the infrared and red light signals can be obtained by dividing the blood oxygen characteristic value of the red light signal by the blood oxygen characteristic value of the infrared signal. A second optical density ratio between the infrared and green light signals can be obtained by dividing the blood oxygen characteristic value of the green light signal by the blood oxygen characteristic value of the infrared signal. Finally, a third optical density ratio between the green and red light signals can be obtained by dividing the blood oxygen characteristic value of the green light signal by the blood oxygen characteristic value of the red light signal.

[0125] Step S542: If both the second and third optical density ratios meet the preset optical density ratio thresholds, then it is determined that pseudo-oxygen exists.

[0126] In some implementations, if both the second and third optical density ratios are less than or equal to a preset optical density ratio threshold, then pseudo-oxygen is determined to be present.

[0127] Step S543: If the second optical density ratio and / or the third optical density ratio do not meet the preset optical density ratio threshold, then it is determined that there is no pseudo-oxygen.

[0128] In some implementations, if the second optical density ratio and / or the third optical density ratio are greater than a preset optical density ratio threshold, then it is determined that there is no pseudo-oxygen.

[0129] In step S550, if false oxygen exists, the blood oxygen characteristic values ​​of the infrared signal and the red signal are corrected based on the blood oxygen characteristic value of the green light signal to obtain the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal, respectively.

[0130] In some implementations, if pseudo-oxygen is present, the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red signal can be obtained according to the blood oxygen characteristic value of the green light signal, following the above step S130.

[0131] In some implementations, the blood oxygenation feature value of the green light signal can be input into a preset feature mapping model to obtain the target blood oxygenation feature values ​​corresponding to the infrared and red light signals, respectively. The preset feature mapping model can be a neural network-based feature mapping model or a machine learning-based feature mapping model.

[0132] In step S560, if there is no false oxygen, the blood oxygen characteristic value of the infrared signal is determined as the target blood oxygen characteristic value of the infrared signal, and the blood oxygen characteristic value of the red light signal is determined as the blood oxygen characteristic value of the red light signal.

[0133] Step S570: Obtain blood oxygen saturation based on the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal, respectively.

[0134] In some implementations, after determining the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal, the blood oxygen saturation can be obtained by referring to the above step S140. The embodiments of this application will not be described in detail here.

[0135] Considering that factors such as the subject's health status, skin color, hair density, vein location, and the tightness of the fitting can all lead to inconsistent PPG signal quality, resulting in errors in the measured blood oxygen saturation. Although the measurement error can be reduced through optical signal quality assessment, the computational load of signal quality assessment is large, which may reduce the real-time performance of blood oxygen measurement. Furthermore, if the filtering conditions are not set appropriately when performing signal filtering based on signal quality assessment, the validity of the optical signal cannot be guaranteed, which will also increase the measurement error of blood oxygen saturation. Therefore, to reduce the measurement error of blood oxygen saturation, in some implementations, after determining the first, second, and third initial optical density ratios, outlier screening is performed based on these ratios. The resulting second and third initial optical density ratios after outlier removal are then used for pseudo-oxygen identification. Based on the pseudo-oxygen identification results, the target blood oxygen characteristic values ​​corresponding to the infrared and red light signals are determined.

[0136] like Figure 7 As shown, Figure 7 This is a schematic flowchart of another blood oxygen measurement method based on spurious oxygen identification provided in this application embodiment. The blood oxygen measurement method based on spurious oxygen identification shown includes steps S710 to S790:

[0137] Step S710: Acquire infrared signal, red light signal and green light signal, perform peak and trough detection on green light signal, and determine key target points in green light signal.

[0138] In some implementations, infrared signals, red light signals, and green light signals can be obtained according to the above step S110, which will not be described in detail in the embodiments of this application.

[0139] In some implementation methods, reference may be made to Figure 2 The provided signal acquisition method acquires infrared signals, red light signals, and green light signals, which will not be described in detail in the embodiments of this application.

[0140] In some implementation methods, reference may be made to Figure 3 The provided multi-channel signal acquisition method acquires infrared signals, red light signals, and green light signals, which will not be described in detail in the embodiments of this application.

[0141] In some implementations, the peak and trough detection of the green light signal can be performed with reference to the above step S120 to determine the target key points in the green light signal. The embodiments of this application will not be described in detail here.

[0142] In some implementation methods, reference may be made to Figure 4 The provided peak and valley detection method performs peak and valley detection on the green light signal to determine the target key points in the green light signal. The embodiments of this application will not be described in detail here.

[0143] Step S720: Map the location information of the target key points in the green light signal to the infrared signal and the red light signal respectively to obtain the target key points in the infrared signal and the target key points in the red light signal.

[0144] In some implementations, the target key points in the infrared signal and the target key points in the red light signal can be obtained according to the above step S120. The embodiments of this application will not be described in detail here.

[0145] Step S730: Determine the blood oxygen characteristic value of the green light signal, the blood oxygen characteristic value of the infrared signal, and the blood oxygen characteristic value of the red light signal based on the signal values ​​corresponding to the target key points in the green light signal, the target key points in the infrared signal, and the target key points in the red light signal.

[0146] In some implementations, the blood oxygen characteristic values ​​of the green light signal, the infrared signal, and the red light signal can be determined with reference to the above step S530. The embodiments of this application will not be described in detail here.

[0147] Step S740: Based on the blood oxygen characteristic values ​​of the green light signal, the infrared signal, and the red light signal, the second initial optical density ratio and the third initial optical density ratio are obtained.

[0148] In some implementations, the first initial optical density ratio, the second initial optical density ratio, and the third initial optical density ratio can be obtained by referring to step S541 above. The embodiments of this application will not be described in detail here.

[0149] Step S750: Outlier filtering is performed on the second initial optical density ratio and the third initial optical density ratio respectively to obtain the remaining second initial optical density ratio and the remaining third initial optical density ratio after filtering.

[0150] In some implementations, outlier screening can be performed on the first initial optical density ratio, the second initial optical density ratio, and the third initial optical density ratio using 3 Sigma.

[0151] Optionally, the first initial optical density ratio, the second initial optical density ratio, and the third initial optical density ratio can be compared with preset optical density conditions to identify abnormal first initial optical density ratios that do not meet the preset optical density conditions, abnormal second initial optical density ratios that do not meet the preset optical density conditions, and abnormal third initial optical density ratios that do not meet the preset optical density conditions. Abnormal first initial optical density ratios, abnormal second initial optical density ratios, and abnormal third initial optical density ratios are sampled by 3 sigm and removed to obtain the remaining first initial optical density ratio, the remaining second initial optical density ratio, and the remaining third initial optical density ratio. The preset optical density condition can be that the initial optical density ratio is within a preset optical density ratio threshold range; the preset optical density condition can also be that the initial optical density ratio meets a preset optical density threshold; the preset optical density condition can also be that the difference between the initial optical density ratio and the average initial optical density ratio is less than or equal to a preset difference threshold. For example, when the difference between the first initial optical density ratio and the average first initial optical density ratio is less than or equal to the preset difference threshold, the first initial optical density ratio meets the preset optical density condition; when the difference between the first initial optical density ratio and the average first initial optical density ratio is greater than the preset difference threshold, the first initial optical density ratio does not meet the preset optical density condition.

[0152] Step S760: Based on the remaining second initial optical density ratio and the remaining third initial optical density ratio, perform pseudo-oxygen identification to determine whether pseudo-oxygen exists.

[0153] In some implementations, the presence of pseudo-oxygen can be determined by referring to the above steps S542 to S543, which will not be elaborated here in the embodiments of this application.

[0154] In step S770, if false oxygen exists, the remaining blood oxygen characteristic value in the green light signal is determined based on the remaining second initial optical density ratio and the remaining third initial optical density ratio. The blood oxygen characteristic value of the infrared signal and the blood oxygen characteristic value of the red light signal are corrected based on the remaining blood oxygen characteristic value in the green light signal to obtain the target blood oxygen characteristic value corresponding to the infrared signal and the red light signal, respectively.

[0155] In some implementations, if pseudo-oxygen is present, the remaining blood oxygen characteristic value in the green light signal is determined based on the remaining second initial optical density ratio and the remaining third initial optical density ratio. The blood oxygen characteristic value of the infrared signal and the blood oxygen characteristic value of the red light signal are then corrected according to the above step S550 to obtain the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal, respectively.

[0156] In step S780, if there is no false oxygen, the residual blood oxygen characteristic value of the infrared signal and the residual blood oxygen characteristic value of the red light signal are determined. The residual blood oxygen characteristic value of the infrared signal is determined as the target blood oxygen characteristic value of the infrared signal, and the residual blood oxygen characteristic value of the red light signal is determined as the blood oxygen characteristic value of the red light signal.

[0157] In some implementations, if no false oxygen is present, the residual blood oxygen characteristic values ​​of the infrared signal and the red light signal are determined based on the remaining first initial optical density ratio, the remaining second initial optical density ratio, and the remaining third initial optical density ratio. The residual blood oxygen characteristic value of the infrared signal is then determined as the target blood oxygen characteristic value of the infrared signal, and the residual blood oxygen characteristic value of the red light signal is then determined as the blood oxygen characteristic value of the red light signal.

[0158] Step S790: Obtain blood oxygen saturation based on the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal, respectively.

[0159] In some implementations, after determining the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal, the blood oxygen saturation can be obtained by referring to the above step S140. The embodiments of this application will not be described in detail here.

[0160] The blood oxygen measurement method based on pseudo-oxygen identification provided in this application can still guarantee the accuracy of the final measured blood oxygen saturation even without signal quality evaluation of the light signal by adding an outlier screening step of optical density ratio.

[0161] Considering that the light signal quality of fingertip oximeters and wrist oximeters is relatively good when the measurement point is less affected by veins, spurious oxygen detection and key point localization would increase computational complexity and affect the real-time performance of oximetry. Therefore, to reduce computational complexity while ensuring real-time oximetry, some implementations can acquire an initial light signal containing only infrared and red light signals from the measurement point. The quality of this initial light signal is then evaluated to determine whether to acquire a green light signal and to perform spurious oxygen detection and key point localization. The initial light signal, acquired from the measurement point of either the wrist or fingertip oximeter, contains only red and infrared signals, and its signal quality needs to be evaluated.

[0162] like Figure 8 As shown, Figure 8 This is a schematic flowchart of another blood oxygen measurement method provided in an embodiment of this application, which includes steps S810 to S880:

[0163] Step S810: Acquire the initial optical signal.

[0164] The initial light signal includes infrared and red light signals.

[0165] Step S820: Evaluate the quality of the initial optical signal to obtain the signal quality of the initial optical signal.

[0166] In some embodiments, the initial optical signal can be evaluated according to the above steps S211A to obtain the signal quality of the initial optical signal, or the initial optical signal can be evaluated according to the above steps S211B to S214B to obtain the signal quality of the initial optical signal. The embodiments of this application will not be described in detail here.

[0167] Step S830: If the signal quality of the initial optical signal does not match the preset signal quality conditions, then acquire the green light signal.

[0168] In some implementations, the preset signal quality condition may be that there is no initial optical signal with poor signal quality, or that the number of initial optical signals with poor signal quality is less than or equal to a preset number threshold.

[0169] In some implementations, if the signal quality of the initial optical signal does not match the preset signal quality conditions, then the infrared signal, red light signal, and green light signal are acquired according to step S110 above, or referenced. Figure 2 The provided signal acquisition method acquires infrared, red, and green light signals, or refer to [the relevant documentation]. Figure 3The provided multi-channel signal acquisition method acquires infrared signals, red light signals, and green light signals, which will not be described in detail in the embodiments of this application.

[0170] Step S840: Detect peaks and troughs in the green light signal to determine key target points in the green light signal.

[0171] In some implementations, the peak and trough detection of the green light signal can be performed with reference to the above step S120 to determine the target key points in the green light signal. The embodiments of this application will not be described in detail here.

[0172] In some implementation methods, reference may be made to Figure 4 The provided peak and valley detection method performs peak and valley detection on the green light signal to determine the target key points in the green light signal. The embodiments of this application will not be described in detail here.

[0173] Step S850: Map the location information of the target key points in the green light signal to the infrared signal and the red light signal respectively to obtain the target key points in the infrared signal and the target key points in the red light signal.

[0174] In some implementations, the target key points in the infrared signal and the target key points in the red light signal can be obtained according to the above step S120. The embodiments of this application will not be described in detail here.

[0175] Step S860: Determine the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red signal based on the signal values ​​corresponding to the target key points in the green light signal, the infrared signal, and the red light signal.

[0176] In some embodiments, the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal can be determined according to the above step S130, or the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal can be determined with reference to the above steps S530 to S560, or the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal can be determined with reference to the above steps S730 to S780. The embodiments of this application will not be described in detail here.

[0177] After steps S870 and S820, if the signal quality of the initial optical signal matches the preset signal quality conditions, then the target blood oxygen characteristic values ​​corresponding to the red light signal and the infrared signal are obtained according to their respective DC and AC components.

[0178] In some implementations, if the signal quality of the initial optical signal matches the preset signal quality conditions, the target blood oxygen characteristic value of the red light signal is obtained by the ratio between the DC and AC components of the red light signal and the infrared signal, respectively, based on the DC and AC components of the red light signal and the infrared signal, respectively.

[0179] Optionally, peak and trough detection can be performed on the infrared signal and the red light signal respectively to obtain the target key points in the infrared signal and the target key points in the red light signal. Based on the signal values ​​corresponding to the target key points in the infrared signal and the target key points in the red light signal, the DC component and AC component corresponding to the red light signal and the infrared signal respectively can be determined.

[0180] Step S880: Obtain blood oxygen saturation based on the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal, respectively.

[0181] In some implementations, blood oxygen saturation can be obtained with reference to S140, which will not be described in detail in the embodiments of this application.

[0182] In some implementations, considering that the electronic device used for blood oxygen measurement does not have a green light sensor and cannot acquire green light signals, in step S830, if the signal quality of the initial light signal does not match the preset signal quality conditions, it is detected whether a green light sensor is installed in the electronic device. If a green light sensor is installed, the green light signal is acquired through the green light sensor, and the red light signal and the target blood oxygen characteristic value corresponding to the red light signal are obtained through the above steps S840 to S860. If the electronic device does not have a green light sensor, the target blood oxygen characteristic value corresponding to the red light signal is obtained according to the DC component and AC component corresponding to the red light signal and the infrared signal, respectively.

[0183] The blood oxygen measurement method provided in this application uses green light signal as an aid for key point localization. By improving the accuracy of the target key points corresponding to red light signal and infrared signal, it reduces the signal key point localization error caused by factors such as the user's health status, skin color, hair density, vein position and tightness of the clothing during measurement, thereby improving the detection accuracy of blood oxygen saturation.

[0184] To better implement the blood oxygen measurement method provided in the embodiments of this application, a blood oxygen measurement device is provided based on the embodiments of the blood oxygen measurement method, such as... Figure 9 As shown, Figure 9 This is a schematic diagram of the blood oxygen measurement device provided in the embodiments of this application. The blood oxygen measurement device shown includes:

[0185] The acquisition module is used to acquire infrared signals, red light signals, and green light signals;

[0186] The key point localization module is used to determine the target key points in the green light signal, and to map the position information of the target key points in the green light signal to the infrared signal and the red light signal respectively, so as to obtain the target key points in the infrared signal and the target key points in the red light signal.

[0187] The feature value determination module is used to determine the target blood oxygen feature value corresponding to the infrared signal and the red signal based on the signal values ​​corresponding to the target key points in the green light signal, the infrared signal and the red light signal respectively.

[0188] The blood oxygen determination module is used to obtain blood oxygen saturation based on the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal, respectively.

[0189] In some implementations, the key point localization module is used for:

[0190] Based on the preset position mapping relationship between the green light signal and the infrared signal, the position information of the target key points in the green light signal is mapped to the infrared signal to obtain the target key points in the infrared signal;

[0191] Based on the preset position mapping relationship between the green light signal and the red light signal, the position information of the target key point in the green light signal is mapped to the red light signal to obtain the target key point in the red light signal.

[0192] In some implementations, the feature value determination module includes:

[0193] The feature value calculation unit is used to determine the blood oxygen feature value of the green light signal, the blood oxygen feature value of the infrared signal, and the blood oxygen feature value of the red light signal based on the signal values ​​corresponding to the target key points in the green light signal, the infrared signal, and the red light signal, respectively.

[0194] The false oxygen detection unit is used to identify false oxygen based on the blood oxygen characteristic values ​​of the green light signal, the infrared signal, and the red light signal, and to determine whether false oxygen exists.

[0195] The correction unit is used to correct the blood oxygen characteristic values ​​of the infrared signal and the red signal based on the blood oxygen characteristic value of the green light signal if false oxygen is present, so as to obtain the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal respectively.

[0196] In some implementations, the correction unit is used to input the blood oxygen feature value of the green light signal into a preset feature mapping model to obtain the target blood oxygen feature values ​​corresponding to the infrared signal and the red light signal, respectively.

[0197] In some implementations, the pseudo-oxygen identification unit is used for:

[0198] Based on the blood oxygen characteristic values ​​of the green light signal, the infrared signal, and the red light signal, the first optical density ratio, the second optical density ratio, and the third optical density ratio are obtained.

[0199] If both the second and third optical density ratios meet the preset optical density ratio thresholds, then it is determined that pseudo-oxygen exists.

[0200] If the second and / or third optical density ratios do not meet the preset optical density ratio threshold, then it is determined that there is no pseudo-oxygen.

[0201] In some implementations, the pseudo-oxygen identification unit is used for:

[0202] The first optical density ratio is obtained based on the blood oxygen characteristic values ​​of the infrared signal and the blood oxygen characteristic values ​​of the red light signal.

[0203] The second optical density ratio is obtained based on the blood oxygen characteristic values ​​of the green light signal and the infrared signal.

[0204] The third optical density ratio is obtained based on the blood oxygen characteristic values ​​of the green light signal and the red light signal.

[0205] In some implementations, the eigenvalue calculation unit is used for:

[0206] Based on the signal values ​​corresponding to the target key points in the green light signal, the target key points in the infrared signal, and the target key points in the red light signal, the DC and AC components of the green light signal, infrared signal, and red light signal are obtained respectively.

[0207] Based on the DC and AC components corresponding to the green, infrared, and red light signals, the blood oxygen characteristic values ​​of the green light signal, the infrared light signal, and the red light signal are obtained.

[0208] In some implementations, the acquisition module is used for:

[0209] The signal quality of the optical signal is evaluated to obtain the signal quality of the optical signal; the optical signal includes red light signal, infrared signal and green light signal;

[0210] Based on the signal quality of the optical signal, the effective optical signal is filtered out from the optical signal, and the red light signal, infrared signal and green light signal in the effective optical signal are obtained.

[0211] In some implementations, the acquisition module is used for:

[0212] Acquire at least one of the following: the variation characteristics of the optical signal, the variation characteristics of gravitational acceleration, and the frequency domain characteristics of the optical signal;

[0213] The signal quality of an optical signal is determined based on at least one of the following: the variation characteristics of the optical signal, the variation characteristics of gravitational acceleration, and the frequency domain characteristics of the optical signal.

[0214] In some implementations, the acquisition module is used for:

[0215] Collect at least two candidate optical signals;

[0216] The quality of each candidate optical signal is evaluated to obtain the signal quality of each candidate optical signal;

[0217] Based on the signal quality of each candidate optical signal, the optical signal used for blood oxygen measurement is determined from the candidate optical signals, and the signal quality of the optical signal is evaluated to obtain the signal quality of the optical signal.

[0218] In some implementations, the feature value determination module is used for:

[0219] Based on the signal values ​​corresponding to the target key points in the green light signal, the target key points in the infrared signal, and the target key points in the red light signal, determine the blood oxygen characteristic values ​​of the green light signal, the infrared signal, and the red light signal.

[0220] Based on the blood oxygen characteristic values ​​of the green light signal, the infrared signal, and the red light signal, the second initial optical density ratio and the third initial optical density ratio are obtained.

[0221] Outlier screening was performed on the second and third initial optical density ratios respectively to obtain the remaining second and third initial optical density ratios after screening.

[0222] False oxygen is identified based on the remaining second and third initial optical density ratios to determine whether false oxygen exists.

[0223] If false oxygen exists, the remaining blood oxygen characteristic value in the green light signal is determined based on the remaining second initial optical density ratio and the remaining third initial optical density ratio. The blood oxygen characteristic value of the infrared signal and the blood oxygen characteristic value of the red light signal are then corrected based on the remaining blood oxygen characteristic value in the green light signal to obtain the target blood oxygen characteristic value corresponding to the infrared signal and the red light signal, respectively.

[0224] In some implementations, the acquisition module is used for:

[0225] Acquire initial light signals, which include infrared and red light signals;

[0226] The quality of the initial optical signal is assessed to obtain the signal quality of the initial optical signal;

[0227] If the signal quality of the initial optical signal does not match the preset signal quality conditions, then a green light signal is acquired, and peak and trough detection is performed on the green light signal to determine the target key points in the green light signal.

[0228] In some implementations, the feature value determination module is used to obtain the target blood oxygen feature value corresponding to the red light signal and the infrared signal respectively, based on the DC component and AC component corresponding to the red light signal and the infrared signal respectively, if the signal quality of the initial light signal matches the preset signal quality conditions.

[0229] The blood oxygen determination module is used to obtain blood oxygen saturation based on the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal, respectively.

[0230] In some implementations, the blood oxygen determination module is used for:

[0231] The target optical density ratio is obtained based on the target blood oxygen characteristic values ​​corresponding to the infrared and red light signals, respectively.

[0232] Obtain the fitting parameters, and calculate the blood oxygen saturation based on the target optical density ratio and the fitting parameters.

[0233] In some implementations, the key point localization module is used for:

[0234] Statistical analysis is performed on the signal values ​​of each sampling point in the green light signal to obtain the statistical characteristics of the green light signal; the statistical characteristics of the signal values ​​include any one of the signal value mean, signal value mode, and signal value median.

[0235] The signal threshold of the green light signal is determined based on the statistical characteristics of the signal value.

[0236] By comparing the signal values ​​at each sampling point in the green light signal with the signal threshold, the peak and trough signal points of the green light signal are determined.

[0237] The peak and trough signal points of the green light signal are identified as key target points in the green light signal.

[0238] The blood oxygen measurement device provided in this application uses green light signal as an aid for key point positioning. By improving the accuracy of the target key points corresponding to the red light signal and infrared signal, it reduces the signal key point positioning error caused by factors such as the user's health status, skin color, hair density, vein position and tightness of the device during measurement, thereby improving the detection accuracy of blood oxygen saturation.

[0239] This application also provides an electronic device, which includes a main body and a blood oxygen measurement device or the aforementioned blood oxygen measurement method deployed therein. The electronic device may be, but is not limited to, a pulse oximeter, a body composition analyzer, or a smart wearable device. Smart wearable devices include, but are not limited to, smartwatches and smart bracelets. This electronic device acquires infrared signals, red light signals, and green light signals; determines target key points in the green light signal; maps the position information of the target key points in the green light signal to the infrared and red light signals respectively, obtaining the target key points in the infrared and red light signals; determines the target blood oxygen feature values ​​corresponding to the infrared and red light signals respectively based on the signal values ​​corresponding to the target key points in the green, infrared, and red light signals; and obtains the blood oxygen saturation based on the target blood oxygen feature values ​​corresponding to the infrared and red light signals. This addresses the technical problem of reduced accuracy in existing blood oxygen measurement methods due to inconsistent quality of acquired PPG signals.

[0240] The above are merely preferred embodiments of this application and are not intended to limit this application in any way. Although this application has disclosed preferred embodiments as above, it is not intended to limit this application. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the technical solution of this application. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of this application without departing from the scope of the technical solution of this application shall still fall within the scope of the technical solution of this application.

Claims

1. A method of oximetry, characterized by, The methods shown include: Acquire infrared signals, red light signals, and green light signals; Determine the target key points in the green light signal, and map the position information of the target key points in the green light signal to the infrared signal and the red light signal respectively to obtain the target key points in the infrared signal and the target key points in the red light signal; Based on the signal values ​​corresponding to the target key points in the green light signal, the target key points in the infrared signal, and the target key points in the red light signal, the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal are determined respectively. Blood oxygen saturation is obtained based on the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal, respectively. The step of determining the target blood oxygen feature value corresponding to the infrared signal and the red light signal based on the signal values ​​corresponding to the target key points in the green light signal, the infrared signal, and the red light signal respectively includes: Based on the signal values ​​corresponding to the target key points in the green light signal, the target key points in the infrared signal, and the target key points in the red light signal, the blood oxygen characteristic values ​​of the green light signal, the infrared signal, and the red light signal are determined. The second optical density ratio is obtained based on the blood oxygen characteristic values ​​of the green light signal and the infrared signal. The third optical density ratio is obtained based on the blood oxygen characteristic values ​​of the green light signal and the red light signal. If both the second optical density ratio and the third optical density ratio meet the preset optical density ratio threshold, then it is determined that pseudo-oxygen exists; If the second optical density ratio and / or the third optical density ratio do not meet the preset optical density ratio threshold, then it is determined that there is no pseudo-oxygen. If false oxygen exists, the blood oxygen feature value of the green light signal is input into a preset feature mapping model to obtain the target blood oxygen feature values ​​corresponding to the infrared signal and the red light signal respectively. or, Based on the signal values ​​corresponding to the target key points in the green light signal, the target key points in the infrared signal, and the target key points in the red light signal, the blood oxygen characteristic values ​​of the green light signal, the infrared signal, and the red light signal are determined. Based on the blood oxygen characteristic values ​​of the green light signal, the infrared signal, and the red light signal, a second initial optical density ratio and a third initial optical density ratio are obtained. Outlier filtering is performed on the second initial optical density ratio and the third initial optical density ratio respectively to obtain the remaining second initial optical density ratio and the remaining third initial optical density ratio after filtering. False oxygen is identified based on the remaining second initial optical density ratio and the remaining third initial optical density ratio to determine whether false oxygen exists. If false oxygen exists, the remaining blood oxygen feature value in the green light signal is determined based on the remaining second initial optical density ratio and the remaining third initial optical density ratio. The blood oxygen feature value of the infrared signal and the blood oxygen feature value of the red light signal are then corrected based on the remaining blood oxygen feature value in the green light signal to obtain the target blood oxygen feature value corresponding to the infrared signal and the red light signal, respectively.

2. The method according to claim 1, characterized in that, The step of mapping the location information of the target key points in the green light signal to the infrared signal and the red light signal respectively to obtain the target key points in the infrared signal and the target key points in the red light signal includes: Based on the preset position mapping relationship between the green light signal and the infrared signal, the position information of the target key point in the green light signal is mapped to the infrared signal to obtain the target key point in the infrared signal; Based on the preset position mapping relationship between the green light signal and the red light signal, the position information of the target key point in the green light signal is mapped to the red light signal to obtain the target key point in the red light signal.

3. The method according to claim 1, characterized in that, The step of determining the blood oxygen characteristic value of the green light signal, the blood oxygen characteristic value of the infrared signal, and the blood oxygen characteristic value of the red light signal based on the signal values ​​corresponding to the target key points in the green light signal, the target key points in the infrared signal, and the target key points in the red light signal, includes: Based on the signal values ​​corresponding to the target key points in the green light signal, the target key points in the infrared signal, and the target key points in the red light signal, the DC component and AC component corresponding to each of the green light signal, the infrared signal, and the red light signal are obtained; Based on the DC and AC components corresponding to the green light signal, the infrared signal, and the red light signal, the blood oxygen characteristic values ​​of the green light signal, the infrared signal, and the red light signal are obtained.

4. The method according to claim 1, characterized in that, The acquisition of infrared signals, red light signals, and green light signals includes: The signal quality of the optical signal is evaluated to obtain the signal quality of the optical signal; the optical signal includes red light signal, infrared signal and green light signal; Based on the signal quality of the optical signal, the effective optical signal is filtered out from the optical signal, and the red light signal, infrared signal and green light signal in the effective optical signal are obtained.

5. The method according to claim 4, characterized in that, The process of evaluating the signal quality of the optical signal to obtain the signal quality of the optical signal includes: Acquire at least one of the following: the variation characteristics of the optical signal, the variation characteristics of gravitational acceleration, and the frequency domain characteristics of the optical signal; The signal quality of the optical signal is determined based on at least one of the following: the variation characteristics of the optical signal, the variation characteristics of gravitational acceleration, and the frequency domain characteristics of the optical signal.

6. The method according to claim 5, characterized in that, Before performing signal quality assessment on the optical signal to obtain the signal quality of the optical signal, the method includes: Collect at least two candidate optical signals; The quality of each candidate optical signal is evaluated to obtain the signal quality of each candidate optical signal. Based on the signal quality of each candidate optical signal, an optical signal for blood oxygen measurement is determined from each candidate optical signal, and the signal quality evaluation of the optical signal is performed to obtain the signal quality of the optical signal.

7. The method according to claim 1, characterized in that, The method further includes: Acquire an initial light signal, which includes an infrared signal and a red light signal; The initial optical signal is evaluated to obtain its signal quality. If the signal quality of the initial optical signal does not match the preset signal quality conditions, then a green light signal is acquired, and peak and trough detection is performed on the green light signal to determine the target key points in the green light signal.

8. The method according to claim 7, characterized in that, After assessing the quality of the initial optical signal to obtain its signal quality, the method further includes: If the signal quality of the initial optical signal matches the preset signal quality conditions, then the target blood oxygen characteristic value corresponding to the red light signal and the infrared signal is obtained according to the DC component and AC component corresponding to the red light signal and the infrared signal, respectively. Blood oxygen saturation is obtained based on the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal, respectively.

9. The method according to any one of claims 1 to 8, characterized in that, The step of obtaining blood oxygen saturation based on the target blood oxygen feature values ​​corresponding to the infrared signal and the red light signal respectively includes: The target optical density ratio is obtained based on the target blood oxygen characteristic values ​​corresponding to the infrared signal and the red light signal, respectively. Obtain the fitting parameters, and based on the target optical density ratio and the fitting parameters, obtain the blood oxygen saturation.

10. The method according to claim 1, characterized in that, Determining key target points in the green light signal includes: Statistical analysis is performed on the signal values ​​of each sampling point in the green light signal to obtain the signal value statistical characteristics of the green light signal; the signal value statistical characteristics include any one of the signal value average, signal value mode, and signal value median. Based on the statistical characteristics of the signal values, the signal threshold of the green light signal is determined; By comparing the signal values ​​of each sampling point in the green light signal with the signal threshold, the peak signal point and the trough signal point of the green light signal are determined. The peak and trough signal points of the green light signal are identified as key target points in the green light signal.

11. A blood oxygen measuring device, characterized in that, The device includes: The acquisition module is used to acquire infrared signals, red light signals, and green light signals; The key point localization module is used to determine the target key points in the green light signal, and map the position information of the target key points in the green light signal to the infrared signal and the red light signal respectively, so as to obtain the target key points in the infrared signal and the target key points in the red light signal; The feature value determination module is used to determine the target blood oxygen feature value corresponding to the infrared signal and the red light signal respectively based on the signal values ​​corresponding to the target key points in the green light signal, the target key points in the infrared signal and the target key points in the red light signal; The blood oxygen determination module is used to obtain blood oxygen saturation based on the target blood oxygen feature values ​​corresponding to the infrared signal and the red light signal, respectively. The feature value determination module includes: The feature value calculation unit is used to determine the blood oxygen feature value of the green light signal, the blood oxygen feature value of the infrared signal, and the blood oxygen feature value of the red light signal based on the signal values ​​corresponding to the target key points in the green light signal, the target key points in the infrared signal, and the target key points in the red light signal, respectively. The false oxygen detection unit is configured to obtain a second optical density ratio based on the blood oxygen characteristic values ​​of the green light signal and the infrared signal; and to obtain a third optical density ratio based on the blood oxygen characteristic values ​​of the green light signal and the red light signal; if both the second optical density ratio and the third optical density ratio meet a preset optical density ratio threshold, then it is determined that false oxygen exists; and if the second optical density ratio and / or the third optical density ratio do not meet the preset optical density ratio threshold, then it is determined that false oxygen does not exist. The correction unit is used to input the blood oxygen feature value of the green light signal into a preset feature mapping model if false oxygen exists, so as to obtain the target blood oxygen feature values ​​corresponding to the infrared signal and the red light signal respectively. or, The feature value determination module is used for: Based on the signal values ​​corresponding to the target key points in the green light signal, the target key points in the infrared signal, and the target key points in the red light signal, the blood oxygen characteristic values ​​of the green light signal, the infrared signal, and the red light signal are determined. Based on the blood oxygen characteristic values ​​of the green light signal, the infrared signal, and the red light signal, a second initial optical density ratio and a third initial optical density ratio are obtained. Outlier filtering is performed on the second initial optical density ratio and the third initial optical density ratio respectively to obtain the remaining second initial optical density ratio and the remaining third initial optical density ratio after filtering. False oxygen is identified based on the remaining second initial optical density ratio and the remaining third initial optical density ratio to determine whether false oxygen exists. If false oxygen exists, the remaining blood oxygen feature value in the green light signal is determined based on the remaining second initial optical density ratio and the remaining third initial optical density ratio. The blood oxygen feature value of the infrared signal and the blood oxygen feature value of the red light signal are then corrected based on the remaining blood oxygen feature value in the green light signal to obtain the target blood oxygen feature value corresponding to the infrared signal and the red light signal, respectively.

12. An electronic device, characterized in that, It includes a processor and a memory, the memory storing a computer program that can be executed by the processor, the computer program implementing the method as described in any one of claims 1-10 when executed by the processor.

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