Data processing method, data processing apparatus, electronic device and readable storage medium

Abstract

The application discloses a data processing method, a data processing device, an electronic equipment and a readable storage medium, and belongs to the technical field of blood oxygen detection. The data processing method comprises the following steps: acquiring a health parameter, wherein the health parameter comprises a photoelectric plethysmogram signal; determining a green light amplitude spectrum, a red light amplitude spectrum and an infrared light amplitude spectrum according to the photoelectric plethysmogram signal; determining a human pulse frequency according to the green light amplitude spectrum; determining a first parameter according to the red light amplitude spectrum and the human pulse frequency, and determining a second parameter according to the infrared light amplitude spectrum and the human pulse frequency; and determining a blood oxygen saturation degree according to the first parameter and the second parameter.

Description

Technical Field

[0001] This application belongs to the field of blood oxygen detection technology, specifically relating to a data processing method, a data processing device, an electronic device, and a readable storage medium. Background Technology

[0002] Blood oxygen saturation (SaO2) is the percentage of oxygen-bound oxyhemoglobin (HbO2) in the blood relative to the total available hemoglobin (Hb), essentially representing the concentration of oxygen in the blood. It is a crucial physiological parameter for respiratory and circulatory function. When deoxyhemoglobin in the blood combines with oxygen entering the body, it forms oxyhemoglobin. The two differ in their absorption rates of infrared and red light. Oxyhemoglobin absorbs less red light and more infrared light; deoxyhemoglobin absorbs more red light and less infrared light. Wearable devices with blood oxygen detection capabilities typically utilize this characteristic to calculate blood oxygen saturation.

[0003] In related technologies, wearable smart devices such as smartwatches determine the parameters used to calculate blood oxygen saturation solely through red and infrared light. However, in some applications, red and infrared light exhibit low perfusion indexes and weak signals, resulting in low accuracy in the calculated blood oxygen saturation. Summary of the Invention

[0004] The purpose of this application is to provide a data processing method, data processing device, electronic device, and readable storage medium that can solve the problem of low accuracy in determining blood oxygen saturation solely through red and infrared light.

[0005] In a first aspect, embodiments of this application provide a data processing method, which includes: acquiring health parameters, including photoplethysmography (PPG) signals; determining a green light amplitude spectrum, a red light amplitude spectrum, and an infrared light amplitude spectrum based on the PPG signals; determining a human pulse frequency based on the green light amplitude spectrum; determining a first parameter based on the red light amplitude spectrum and the human pulse frequency; determining a second parameter based on the infrared light amplitude spectrum and the human pulse frequency; and determining blood oxygen saturation based on the first and second parameters.

[0006] Secondly, embodiments of this application provide a data processing apparatus, which includes a processing unit for determining a first parameter and a second parameter, and determining blood oxygen saturation based on the first parameter and the second parameter.

[0007] Thirdly, embodiments of this application provide an electronic device including a processor and a memory. The memory stores programs or instructions that can run on the processor, and when the programs or instructions are executed by the processor, they implement the steps of the data processing method as described in the first aspect.

[0008] Fourthly, embodiments of this application provide a readable storage medium that stores a program or instructions executable on a processor, which, when executed by the processor, implement the steps of the data processing method as described in the first aspect.

[0009] Fifthly, embodiments of this application provide a chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the steps of the data processing method as described in the first aspect.

[0010] In a sixth aspect, embodiments of this application provide a computer program product stored in a storage medium, which is executed by at least one processor to implement the steps of the data processing method as described in the first aspect.

[0011] The data processing method provided in this application includes: acquiring health parameters, including photoplethysmography (PPG) signals; determining green light amplitude spectrum, red light amplitude spectrum, and infrared light amplitude spectrum based on the PPG signals; determining the human pulse frequency based on the green light amplitude spectrum; determining a first parameter based on the red light amplitude spectrum and the human pulse frequency; determining a second parameter based on the infrared light amplitude spectrum and the human pulse frequency; and determining blood oxygen saturation based on the first and second parameters. In this application's embodiments, the human pulse frequency is extracted using green light with a higher signal-to-noise ratio (determining the human pulse frequency based on the green light amplitude spectrum), and the first and second parameters are determined based on the human pulse frequency. This method of determining whether the conditions for calculating blood oxygen saturation are met, and the method of determining the parameters used to calculate blood oxygen saturation, makes it easier to extract signal features, and the acquired first and second parameters are more reliable, thus resulting in a more accurate calculated blood oxygen saturation. Attached Figure Description

[0012] Figure 1 One of the flowcharts for the data processing method provided in the embodiments of this application;

[0013] Figure 2 The second flowchart of the data processing method provided in the embodiments of this application;

[0014] Figure 3 The third flowchart of the data processing method provided in the embodiments of this application;

[0015] Figure 4 The fourth flowchart of the data processing method provided in the embodiments of this application;

[0016] Figure 5 This is a structural block diagram of the data processing apparatus provided in the embodiments of this application;

[0017] Figure 6A structural block diagram of the electronic device provided in the embodiments of this application;

[0018] Figure 7 A schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application;

[0019] Figure 8 A schematic diagram of the photoplethysmography signal after filtering out the DC component, provided in an embodiment of this application;

[0020] Figure 9 A schematic diagram of the green light amplitude spectrum, red light amplitude spectrum, and infrared light amplitude spectrum provided in the embodiments of this application;

[0021] Figure 10 A schematic diagram of the green light amplitude spectrum provided in an embodiment of this application;

[0022] Figure 11 A schematic diagram of the red light amplitude spectrum provided in an embodiment of this application;

[0023] Figure 12 One of the schematic diagrams of the infrared light amplitude spectrum provided in the embodiments of this application;

[0024] Figure 13 This is a second schematic diagram of the infrared light amplitude spectrum provided in the embodiments of this application.

[0025] in, Figure 5 The correspondence between the reference numerals and component names in the attached drawings is as follows:

[0026] 500: Data processing device; 510: Acquisition module; 520: First determining module; 530: Second determining module; 540: Third determining module; 550: Fourth determining module; 560: Fifth determining module. Detailed Implementation

[0027] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0028] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0029] The data processing method, data processing device, electronic device, and readable storage medium provided in this application will be described in detail below with reference to the accompanying drawings and through specific embodiments and application scenarios.

[0030] like Figure 1 , Figure 2 and Figure 3 As shown, this application provides a data processing method. It should be noted that the data processing method can be implemented using wearable devices, and of course, it can also be implemented using other types of devices, such as mobile phones. Wearable devices include smartwatches, smart bracelets, or other smart devices that can be worn by users.

[0031] In one embodiment according to this application, such as Figure 1 As shown, the specific steps of the data processing method include:

[0032] S102, acquire health parameters, including photoplethysmography (PPG) wave signals.

[0033] The photoplethysmography (PPG) signal includes not only red and infrared signals but also green signals. The presence of green, red, and infrared signals is used to determine whether the conditions for calculating blood oxygen saturation are met. If these conditions are met, the green, red, and infrared signals are used to determine the parameters required for calculating blood oxygen saturation.

[0034] S104 determines the green light amplitude spectrum, red light amplitude spectrum, and infrared light amplitude spectrum based on the photoplethysmography pulse wave signal.

[0035] Optionally, the photoplethysmography (PPG) signal is processed by a first filter to extract the red light DC amplitude and infrared light DC amplitude. This step aims to preprocess the PPG signal. The frequency of the human PPG signal is typically between 0.5Hz and 5Hz. Considering the presence of harmonics in the PPG signal, and the relatively minor presence of harmonics above the third harmonic, this step uses a first filter to process the PPG signal. Optionally, the first filter is a low-pass filter. A low-pass filter is an electronic filter that allows signals below the cutoff frequency to pass through, but blocks signals above the cutoff frequency. Optionally, the cutoff frequency of the low-pass filter is between 14Hz and 16Hz. Optionally, the cutoff frequency of the low-pass filter is 15Hz. This step is used to determine the red light DC amplitude (DC). red ) and infrared light DC amplitude (DC) ir This is used as a parameter for calculating blood oxygen saturation in subsequent steps.

[0036] Optionally, the DC component in the photoplethysmography (PPG) signal is removed by a second filter, and the amplitude spectra of the green light, red light, and infrared light are determined. Optionally, the second filter is a high-pass filter. A high-pass filter is an electronic filter that allows signals above its cutoff frequency to pass through, but blocks signals below its cutoff frequency. Optionally, the cutoff frequency of the high-pass filter is between 0.4 Hz and 0.6 Hz. Alternatively, the cutoff frequency of the high-pass filter may be 0.5 Hz. Figure 8 This is a schematic diagram of the photoplethysmography (PPG) signal after filtering out the DC component, provided in an embodiment of this application. After removing the DC component from the PPG signal using a second filter, the amplitude spectrum of the green light is determined by Fourier transform based on the green light signal; the amplitude spectrum of the red light is determined by Fourier transform based on the red light signal; and the amplitude spectrum of the infrared light is determined by Fourier transform based on the infrared light signal. Figure 9 This diagram illustrates the amplitude spectra of green light, red light, and infrared light provided in embodiments of this application. It should be noted that Fourier transform is a form of harmonic analysis. In signal processing, the purpose of Fourier transform is to decompose a signal into a frequency spectrum (amplitude spectrum). The frequency spectrum is used to display the magnitude of the amplitude corresponding to a frequency.

[0037] S106, determine the human pulse frequency based on the green light amplitude spectrum.

[0038] Compared to red and infrared light, green light is more readily absorbed by oxyhemoglobin and deoxyhemoglobin. Green light also penetrates skin tissue more easily than red and infrared light. Therefore, in reflective pulse oximetry devices, green light exhibits a larger signal variation amplitude and a higher signal-to-noise ratio (SNR). The SNR is the ratio of the intensity of the received useful signal to the intensity of the received interference signal (noise and interference). Although the SNR of photoplethysmography (PPG) signals collected from different wavelengths of light differs, the pulse frequency remains the same. This means that the high SNR of green light can be used to extract the pulse frequency (human pulse frequency), and the amplitude spectrum of green light makes it easier to determine the human pulse frequency, resulting in more accurate measurements. Optionally, such as... Figure 10 As shown, the frequency corresponding to the largest amplitude value in the green light amplitude spectrum is taken as the human pulse frequency F. pulse .

[0039] S108, determine the first parameter based on the red light amplitude spectrum and the human pulse frequency, and determine the second parameter based on the infrared light amplitude spectrum and the human pulse frequency.

[0040] Optionally, the first parameter includes the red light signal-to-noise ratio, the red light AC amplitude, and the red light second harmonic amplitude.

[0041] Optionally, the second parameter includes the infrared light signal-to-noise ratio, the infrared light AC amplitude, and the infrared light second harmonic amplitude.

[0042] Optionally, the red light signal-to-noise ratio (SNR) is determined based on the red light amplitude spectrum and the human pulse frequency. red The infrared signal-to-noise ratio (SNR) is determined based on the infrared light amplitude spectrum and the human pulse frequency. ir Optionally, such as Figure 11 As shown, the AC amplitude of red light can also be determined based on the red light amplitude spectrum and the human pulse frequency. red The amplitude of red light AC is the amplitude corresponding to the human pulse frequency in the red light amplitude spectrum. Figure 11 The amplitude corresponding to P1 is the correct red light AC amplitude. red . Figure 11 The amplitudes corresponding to P2 and P3 are both greater than the amplitude corresponding to P1. Without using the human pulse frequency found through the green light amplitude spectrum, it's easy to mistakenly take the amplitudes corresponding to P2 and P3 as the red light AC amplitudes. Optionally, such as... Figure 12 As shown, the infrared light amplitude spectrum and the human pulse frequency can also be used to determine the infrared light AC amplitude. ir The amplitude of infrared light exchange is the amplitude corresponding to the human pulse frequency in the infrared light amplitude spectrum. Figure 12 The amplitude corresponding to P1 is the correct infrared AC amplitude.ir Optionally, the second harmonic frequency is determined based on the human pulse frequency. Twice the human pulse frequency is taken as the second harmonic frequency. Optionally, the second harmonic amplitude A of the red light is determined based on the red light amplitude spectrum and the second harmonic frequency. red2 The second harmonic amplitude of red light is the amplitude corresponding to the second harmonic frequency in the red light amplitude spectrum. Optionally, such as... Figure 13 As shown, the amplitude A of the second harmonic of infrared light is determined based on the infrared light amplitude spectrum and the second harmonic frequency. ir2 The amplitude of the second harmonic of infrared light is the amplitude corresponding to the second harmonic frequency in the infrared light amplitude spectrum. Figure 13 The amplitude corresponding to P1 is the correct infrared AC amplitude. ir . Figure 13 The amplitude corresponding to P2 is the correct second harmonic amplitude of infrared light, A. ir2 Optionally, the red light harmonic amplitude ratio (Harmonic_ratio) is determined based on the red light second harmonic amplitude and the red light AC amplitude. red Optionally, the infrared light harmonic amplitude ratio (Harmonic_ratio) is determined based on the second harmonic amplitude and the AC amplitude of the infrared light. ir Since the photoplethysmography (PPG) signal of the human body usually has a significant second harmonic, interference is generally difficult to generate a second harmonic. Therefore, the presence of a significant second harmonic in the signal spectrum can be used to determine whether the PPG signal is a physiological signal. However, considering that signal strength is affected by factors such as the sensor's luminous current, when the signal is weak due to a small luminous current, directly judging by the magnitude of the second harmonic amplitude can easily lead to misjudging the weak signal as a non-physiological signal. It is more reasonable to use the ratio of the second harmonic amplitude to the AC amplitude to determine whether it is a physiological signal. When the signal-to-noise ratio and harmonic amplitude simultaneously meet the conditions for blood oxygen detection, blood oxygen saturation can then be further calculated.

[0043] S110, determine blood oxygen saturation based on the first and second parameters.

[0044] The determination of whether to calculate blood oxygen saturation is based on the red light signal-to-noise ratio, infrared light signal-to-noise ratio, red light harmonic amplitude ratio, and infrared light harmonic amplitude ratio. If the photoplethysmography (PPG) signal is determined to be a physiological signal and suitable for calculating blood oxygen saturation, blood oxygen saturation is determined based on the red light AC amplitude, red light DC amplitude, infrared light AC amplitude, and infrared light DC amplitude. By combining the signal-to-noise ratio and harmonic amplitude ratios, this method of determining whether the PPG signal is a physiological signal and suitable for calculating blood oxygen saturation is less likely to misjudge non-physiological signals as physiological signals and less likely to misjudge weak signals as non-physiological signals, resulting in more accurate judgments compared to methods that rely on the correlation coefficients between the AC and green light signals, or between the AC and green light signals in the red light and infrared light signals.

[0045] In the embodiments of this application, the human pulse frequency is extracted using green light with a higher signal-to-noise ratio (the human pulse frequency is determined based on the amplitude spectrum of the green light), and a first parameter and a second parameter are determined based on the human pulse frequency. This method of determining whether the conditions for calculating blood oxygen saturation are met, and the method of determining the parameters used to calculate blood oxygen saturation, makes it easier to extract signal features, and the obtained first and second parameters are more reliable, thus the final calculated blood oxygen saturation can be more accurate.

[0046] In another embodiment of this application, such as Figure 2 As shown, step S108 specifically includes:

[0047] S1081, based on the human pulse frequency, determine the red light signal-to-noise ratio, red light AC amplitude, and red light second harmonic amplitude in the red light amplitude spectrum; based on the human pulse frequency, determine the infrared light signal-to-noise ratio, infrared light AC amplitude, and infrared light second harmonic amplitude in the infrared light amplitude spectrum.

[0048] Optionally, the red light signal-to-noise ratio (SNR) is determined based on the red light amplitude spectrum and the human pulse frequency. red The infrared signal-to-noise ratio (SNR) is determined based on the infrared light amplitude spectrum and the human pulse frequency. ir Optionally, the amplitudes of red light AC, red light second harmonic, infrared light AC, and infrared light second harmonic can be determined based on the human pulse frequency. For example... Figure 11 As shown, the AC amplitude of red light can also be determined based on the red light amplitude spectrum and the human pulse frequency. red The amplitude of red light AC is the amplitude corresponding to the human pulse frequency in the red light amplitude spectrum. Figure 11 The amplitude corresponding to P1 is the correct red light AC amplitude. red . Figure 11The amplitudes corresponding to P2 and P3 are both greater than the amplitude corresponding to P1. Without using the human pulse frequency found through the green light amplitude spectrum, it's easy to mistakenly take the amplitudes corresponding to P2 and P3 as the red light AC amplitudes. Optionally, such as... Figure 12 As shown, the infrared light amplitude spectrum and the human pulse frequency can also be used to determine the infrared light AC amplitude. ir The amplitude of infrared light exchange is the amplitude corresponding to the human pulse frequency in the infrared light amplitude spectrum. Figure 12 The amplitude corresponding to P1 is the correct infrared AC amplitude. ir Optionally, the second harmonic frequency is determined based on the human pulse frequency. Twice the human pulse frequency is taken as the second harmonic frequency. Optionally, the second harmonic amplitude A of the red light is determined based on the red light amplitude spectrum and the second harmonic frequency. red2 The second harmonic amplitude of red light is the amplitude corresponding to the second harmonic frequency in the red light amplitude spectrum. Optionally, such as... Figure 13 As shown, the amplitude A of the second harmonic of infrared light is determined based on the infrared light amplitude spectrum and the second harmonic frequency. ir2 The amplitude of the second harmonic of infrared light is the amplitude corresponding to the second harmonic frequency in the infrared light amplitude spectrum. Figure 13 The amplitude corresponding to P1 is the correct infrared AC amplitude. ir . Figure 13 The amplitude corresponding to P2 is the correct second harmonic amplitude of infrared light, A. ir2 .

[0049] In another embodiment of this application, such as Figure 2 As shown, step S110 includes:

[0050] S1101, determine the red light harmonic amplitude ratio based on the red light second harmonic amplitude and the red light AC amplitude, and determine the infrared light harmonic amplitude ratio based on the infrared light second harmonic amplitude and the infrared light AC amplitude.

[0051] Optionally, the second harmonic amplitude A of the infrared light is determined based on the infrared light amplitude spectrum and the second harmonic frequency. ir2 The second harmonic amplitude of infrared light is the amplitude corresponding to the second harmonic frequency in the infrared light amplitude spectrum. The red light harmonic amplitude ratio (Harmonic_ratio) is also relevant. red It is the ratio of the second harmonic amplitude of red light to the AC amplitude of red light. Harmonic ratio (infrared light harmonic amplitude ratio) ir It is the ratio of the second harmonic amplitude of infrared light to the AC amplitude of infrared light.

[0052] S1102, determine whether the photoplethysmography (PPG) signal is a physiological signal based on the red light signal-to-noise ratio, the infrared light signal-to-noise ratio, the red light harmonic amplitude ratio, and the infrared light harmonic amplitude ratio.

[0053] When both the red light signal-to-noise ratio (SNR) and the infrared light SNR meet the threshold requirements, the signal indicates that it meets the conditions for blood oxygen detection. If either the red light SNR or the infrared light SNR does not meet the threshold requirements, the signal is considered not to meet the conditions for blood oxygen detection. Furthermore, since the photoplethysmography (PPG) signal of the human body usually has a significant second harmonic, interference is generally difficult to generate a second harmonic. Therefore, the presence of a significant second harmonic in the signal spectrum can be used to determine whether the PPG signal is a physiological signal. Considering that signal strength is affected by factors such as the sensor's luminous current, when the signal is weak due to a small luminous current, directly judging by the magnitude of the second harmonic amplitude may easily misjudge the weak signal as a non-physiological signal. It is more reasonable to use the ratio of the second harmonic amplitude to the AC amplitude to determine whether it is a physiological signal. When both the SNR and harmonic amplitude simultaneously meet the conditions for blood oxygen detection, blood oxygen saturation is then calculated.

[0054] S1103, determine blood oxygen saturation after confirming that the photoplethysmography signal is a physiological signal.

[0055] Optionally, blood oxygen saturation can be determined based on the red light AC amplitude, red light DC amplitude, infrared light AC amplitude, and infrared light DC amplitude.

[0056] Optionally, a first ratio is determined based on the red light AC amplitude, red light DC amplitude, infrared light AC amplitude, and infrared light DC amplitude; and blood oxygen saturation is determined based on the first ratio.

[0057] In some embodiments, optionally, the first ratio is the ratio of the third ratio to the fourth ratio. The third ratio is the ratio of the red light AC amplitude to the red light DC amplitude (AC...). red / DC red The fourth ratio is the ratio of the AC amplitude of infrared light to the DC amplitude of infrared light (AC). ir / DC ir The first ratio R = (AC) red / DC red ) / (AC ir / DC ir ).

[0058] In some embodiments, optionally, the blood oxygen saturation and the first ratio satisfy a first formula. The first formula is: S p O2=A+B×R+C×R 2 Among them, S p O2 is blood oxygen saturation, R is the first ratio, and A, B, and C are constants.

[0059] It should be noted that the first formula was determined through an oxygen-lowering experiment. During the experiment, data was collected to calculate the ratio R (the first ratio), and the blood oxygen saturation at the corresponding time point was obtained using a blood gas analyzer as the gold standard blood oxygen saturation result. The first formula was obtained by fitting several R values ​​and the gold standard blood oxygen saturation result to determine the functional relationship.

[0060] In another embodiment of this application, such as Figure 3 As shown, before step S106, the data processing method further includes:

[0061] The DC amplitude of red light and the DC amplitude of infrared light are determined based on the photoplethysmography (PPG) signal.

[0062] Optionally, this step is the same as step S104 above. This step is used to determine the DC amplitude of the red light. red ) and infrared light DC amplitude (DC) ir This is used as a parameter for calculating blood oxygen saturation in subsequent steps. Optionally, a second filter is used to remove the DC component from the photoplethysmography (PPG) signal and to determine the green, red, and infrared amplitude spectra.

[0063] Optionally, the second filter is a high-pass filter. A high-pass filter is an electronic filter that allows signals above the cutoff frequency to pass through, but blocks signals below the cutoff frequency. Optionally, the cutoff frequency of the high-pass filter is between 0.4 Hz and 0.6 Hz. Alternatively, the cutoff frequency of the high-pass filter is 0.5 Hz. Figure 8 This is a schematic diagram of the photoplethysmography (PPG) signal after filtering out the DC component, provided in an embodiment of this application. After removing the DC component from the PPG signal using a second filter, the amplitude spectrum of the green light is determined by Fourier transform based on the green light signal; the amplitude spectrum of the red light is determined by Fourier transform based on the red light signal; and the amplitude spectrum of the infrared light is determined by Fourier transform based on the infrared light signal. Figure 9 This diagram illustrates the amplitude spectra of green light, red light, and infrared light provided in embodiments of this application. It should be noted that Fourier transform is a form of harmonic analysis. In signal processing, the purpose of Fourier transform is to decompose a signal into a frequency spectrum (amplitude spectrum). The frequency spectrum is used to display the magnitude of the amplitude corresponding to a frequency.

[0064] S1103 specifically includes:

[0065] Given that the photoplethysmography (PPG) signal is a physiological signal, blood oxygen saturation is determined based on the red light AC amplitude, red light DC amplitude, infrared light AC amplitude, and infrared light DC amplitude. Optionally, a first ratio is determined based on the red light AC amplitude, red light DC amplitude, infrared light AC amplitude, and infrared light DC amplitude; blood oxygen saturation is then determined based on this first ratio.

[0066] In another embodiment of this application, such as Figure 3 As shown, step S106 includes:

[0067] S1061 uses the frequency corresponding to the largest amplitude value in the green light amplitude spectrum as the human pulse frequency.

[0068] like Figure 13 As shown, the frequency corresponding to the maximum peak value is found in the green light amplitude spectrum and taken as the human pulse frequency. The maximum peak value is the maximum amplitude value.

[0069] In the embodiments of this application, the human pulse frequency is extracted by green light with a higher signal-to-noise ratio, and the signal-to-noise ratio of red light and infrared light is determined based on the human pulse frequency. This method makes it easier to extract signal features, and the blood oxygen saturation calculated in the end can be more accurate.

[0070] In one embodiment according to this application, such as Figure 4 As shown, the specific steps of the data processing method include:

[0071] S402, acquire health parameters, including photoplethysmography (PPG) signals.

[0072] S404 processes the photoplethysmography (PPG) signal through the first filter, and extracts the DC amplitude of red light and the DC amplitude of infrared light from the PPG signal.

[0073] S406 removes the DC component from the photoplethysmography signal using the second filter and determines the green light amplitude spectrum, red light amplitude spectrum, and infrared light amplitude spectrum.

[0074] S408 determines the human pulse frequency based on the green light amplitude spectrum, and determines the red light signal-to-noise ratio and infrared light signal-to-noise ratio based on the human pulse frequency.

[0075] S410 determines the amplitude of red light AC, the amplitude of red light second harmonic, the amplitude of infrared light AC, and the amplitude of infrared light second harmonic based on the human pulse frequency.

[0076] S412, determine the red light harmonic amplitude ratio based on the red light second harmonic amplitude and the red light AC amplitude, and determine the infrared light harmonic amplitude ratio based on the infrared light second harmonic amplitude and the infrared light AC amplitude.

[0077] S414, determine whether the red light signal-to-noise ratio is greater than the first threshold, the infrared light signal-to-noise ratio is greater than the second threshold, the red light harmonic amplitude ratio is greater than the third threshold, and the infrared light harmonic amplitude ratio is greater than the fourth threshold, and generate the first judgment result.

[0078] To determine whether a photoplethysmography (PPG) signal is a physiological signal suitable for calculating blood oxygen saturation, four conditions must be met. The first condition is that the red light signal-to-noise ratio (SNR) is greater than a first threshold; the second condition is that the infrared light SNR is greater than a second threshold; the third condition is that the red light harmonic amplitude ratio (HHAM) is greater than a third threshold; and the fourth condition is that the HHAM is greater than a fourth threshold. When both the red and infrared SNRs meet the threshold requirements, the signal meets the conditions for blood oxygen detection; when either the red or infrared SNR does not meet the threshold requirements, the signal is considered not to meet the conditions for blood oxygen detection. Furthermore, since human PPG signals typically have a significant second harmonic, interference is usually difficult to generate a second harmonic. Therefore, the presence of a significant second harmonic in the signal spectrum can be used to determine whether the PPG signal is a physiological signal. Considering that signal strength is affected by factors such as the sensor's luminous current, when the signal is weak due to a small luminous current, directly judging by the magnitude of the second harmonic amplitude may easily lead to misjudging the weak signal as a non-physiological signal. It is more reasonable to use the ratio of the second harmonic amplitude to the AC amplitude to determine whether it is a physiological signal. When the signal-to-noise ratio and harmonic amplitude simultaneously meet the conditions for blood oxygen detection, then further calculation of blood oxygen saturation can be performed.

[0079] S416, If the first judgment result is yes, then the photoplethysmography signal is a physiological signal and is suitable for calculating blood oxygen saturation.

[0080] When all four conditions are met (red light signal-to-noise ratio greater than the first threshold, infrared light signal-to-noise ratio greater than the second threshold, red light harmonic amplitude ratio greater than the third threshold, and infrared light harmonic amplitude ratio greater than the fourth threshold), it indicates that the photoplethysmography (PPG) signal is a physiological signal and is suitable for calculating blood oxygen saturation.

[0081] S418, determine the first ratio based on the red light AC amplitude, red light DC amplitude, infrared light AC amplitude, and infrared light DC amplitude.

[0082] Optionally, the first ratio is the ratio of the third ratio to the fourth ratio. The third ratio is the ratio of the red light AC amplitude to the red light DC amplitude; the fourth ratio is the ratio of the infrared light AC amplitude to the infrared light DC amplitude.

[0083] S420, determine blood oxygen saturation based on the first ratio.

[0084] The blood oxygen saturation and the first ratio satisfy the first formula. The first formula is: S p O2=A+B×R+C×R 2 Among them, S p O2 is blood oxygen saturation, R is the first ratio, and A, B, and C are constants.

[0085] S422, If the first judgment result is negative, then the photoplethysmography (PPG) signal is not a physiological signal and / or the PPG signal is not suitable for calculating blood oxygen saturation.

[0086] If at least one of the four conditions (red light signal-to-noise ratio greater than the first threshold, infrared light signal-to-noise ratio greater than the second threshold, red light harmonic amplitude ratio greater than the third threshold, and infrared light harmonic amplitude ratio greater than the fourth threshold) is not met, it indicates that the photoplethysmography (PPG) signal is not a physiological signal and / or the PPG signal is not suitable for calculating blood oxygen saturation. In this case, it is necessary to return to S402.

[0087] In the embodiments of this application, firstly, the human pulse frequency is determined based on the green light amplitude spectrum, the red light AC amplitude is determined based on the red light amplitude spectrum and the human pulse frequency, and the infrared light AC amplitude is determined based on the infrared light amplitude spectrum and the human pulse frequency. This method of determining the red light AC amplitude and infrared light AC amplitude is more reliable than the method of directly extracting the red light AC amplitude and infrared light AC amplitude, thus the blood oxygen saturation calculated is more accurate. Secondly, by combining the signal-to-noise ratio and the harmonic amplitude ratio, it is determined whether the photoplethysmography (PPG) signal is a physiological signal and whether it is suitable for calculating blood oxygen saturation. This method of determination, compared with the method of judging the quality of the PPG signal based on the correlation coefficient between the AC component of the red light signal and the AC component of the green light signal, or the correlation coefficient between the AC component of the infrared light signal and the AC component of the green light signal, is less likely to misjudge non-physiological signals as physiological signals and less likely to misjudge weak signals as non-physiological signals, resulting in a more accurate judgment.

[0088] like Figure 5 As shown in the figure, this application embodiment provides a data processing device 500. The data processing device 500 includes an acquisition module 510, a first determination module 520, a second determination module 530, a third determination module 540, and a fourth determination module 550.

[0089] The acquisition module 510 is used to acquire health parameters, including photoplethysmography (PPG) signals.

[0090] The first determining module 520 is used to determine the green light amplitude spectrum, red light amplitude spectrum and infrared light amplitude spectrum based on the photoplethysmography pulse wave signal.

[0091] The second determining module 530 is used to determine the human pulse frequency based on the green light amplitude spectrum.

[0092] The third determining module 540 is used to determine the first parameter based on the red light amplitude spectrum and the human pulse frequency, and to determine the second parameter based on the infrared light amplitude spectrum and the human pulse frequency.

[0093] The fourth determining module 550 is used to determine blood oxygen saturation based on the first parameter and the second parameter.

[0094] Optionally, the third determining module 540 is specifically used to determine the red light signal-to-noise ratio, red light AC amplitude, and red light second harmonic amplitude in the red light amplitude spectrum based on the human pulse frequency, and to determine the infrared light signal-to-noise ratio, infrared light AC amplitude, and infrared light second harmonic amplitude in the infrared light amplitude spectrum based on the human pulse frequency.

[0095] Optionally, the fourth determining module 550 is specifically used to determine the red light harmonic amplitude ratio based on the red light second harmonic amplitude and the red light AC amplitude, and to determine the infrared light harmonic amplitude ratio based on the infrared light second harmonic amplitude and the infrared light AC amplitude; to determine whether the photoplethysmography (PPG) signal is a physiological signal based on the red light signal-to-noise ratio, the infrared light signal-to-noise ratio, the red light harmonic amplitude ratio, and the infrared light harmonic amplitude ratio; and to determine the blood oxygen saturation if the PPG signal is determined to be a physiological signal.

[0096] Optionally, the data processing device 500 further includes a fifth determining module 560, which is used to determine the red light AC amplitude and the red light DC amplitude based on the photoplethysmography signal.

[0097] In addition, the fourth determining module 550 is also used to determine blood oxygen saturation based on the red light AC amplitude, red light DC amplitude, infrared light AC amplitude, and infrared light DC amplitude when the photoplethysmography signal is determined to be a physiological signal.

[0098] Optionally, the second determining module 530 is specifically used to take the frequency corresponding to the largest amplitude value in the green light amplitude spectrum as the human pulse frequency.

[0099] In this embodiment, the human pulse frequency is extracted using green light with a higher signal-to-noise ratio (the human pulse frequency is determined based on the amplitude spectrum of the green light), and a first parameter and a second parameter are determined based on the human pulse frequency. This method of determining whether the conditions for calculating blood oxygen saturation are met, and the method of determining the parameters used to calculate blood oxygen saturation, makes it easier to extract signal features, and the obtained first and second parameters are more reliable, thus resulting in a more accurate calculated blood oxygen saturation.

[0100] The data processing device 500 in this embodiment can be an electronic device or a component within an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices besides a terminal. For example, the electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, mobile internet device (MID), augmented reality (AR) / virtual reality (VR) device, robot, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc. It can also be a server, network attached storage (NAS), personal computer (PC), television set (TV), ATM, or self-service machine, etc. This embodiment does not specifically limit the functionality of the electronic device.

[0101] The data processing device 500 in this embodiment can be a device with an operating system. The operating system can be Android, iOS, or other possible operating systems; this embodiment does not specifically limit the specific operating system.

[0102] The data processing device 500 provided in this embodiment can achieve... Figures 1 to 4 The various processes implemented in the method embodiments have the beneficial effects of any of the above embodiments, and will not be described again here to avoid repetition.

[0103] In one embodiment according to this application, such as Figure 6 As shown, the electronic device 600 includes a processor 602 and a memory 604. The memory 604 stores a program or instructions that can run on the processor 602. When the program or instructions are executed by the processor 602, they implement the various steps of the data processing method in any of the above embodiments and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0104] It should be noted that the electronic device 600 in this application embodiment includes the aforementioned mobile electronic device and non-mobile electronic device.

[0105] Figure 7 A schematic diagram of the hardware structure of an electronic device to implement an embodiment of this application.

[0106] The electronic device 700 includes, but is not limited to, components such as: radio frequency unit 701, network module 702, audio output unit 703, input unit 704, sensor 705, display unit 706, user input unit 707, interface unit 708, memory 709, and processor 710.

[0107] Those skilled in the art will understand that the electronic device 700 may also include a power supply (such as a battery) for supplying power to various components. The power supply may be logically connected to the processor 710 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system. Figure 7 The electronic device structure shown does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0108] The processor 710 is used to acquire health parameters, including photoplethysmography (PPG) signals; determine the green light amplitude spectrum, red light amplitude spectrum, and infrared light amplitude spectrum based on the PPG signals; determine the human pulse frequency based on the green light amplitude spectrum; determine a first parameter based on the red light amplitude spectrum and the human pulse frequency; determine a second parameter based on the infrared light amplitude spectrum and the human pulse frequency; and determine blood oxygen saturation based on the first and second parameters.

[0109] Optionally, the processor 710 is specifically used to determine the red light signal-to-noise ratio, red light AC amplitude, and red light second harmonic amplitude in the red light amplitude spectrum based on the red light amplitude spectrum and the human pulse frequency, and to determine the infrared light signal-to-noise ratio, infrared light AC amplitude, and infrared light second harmonic amplitude in the infrared light amplitude spectrum and the human pulse frequency based on the human pulse frequency.

[0110] Optionally, the processor 710 is specifically used to determine the red light harmonic amplitude ratio based on the red light second harmonic amplitude and the red light AC amplitude, and to determine the infrared light harmonic amplitude ratio based on the infrared light second harmonic amplitude and the infrared light AC amplitude.

[0111] Based on the red light signal-to-noise ratio, infrared light signal-to-noise ratio, red light harmonic amplitude ratio, and infrared light harmonic amplitude ratio, determine whether the photoplethysmography (PPG) signal is a physiological signal.

[0112] Determine blood oxygen saturation after confirming that the photoplethysmography (PPG) signal is a physiological signal.

[0113] Optionally, the processor 710 is specifically used to determine the DC amplitude of red light and the DC amplitude of infrared light based on the photoplethysmography (PPG) signal; and, if the PPG signal is determined to be a physiological signal, to determine the blood oxygen saturation based on the AC amplitude of red light, the DC amplitude of red light, the AC amplitude of infrared light, and the DC amplitude of infrared light.

[0114] Optionally, the processor 710 is specifically used to take the frequency corresponding to the largest amplitude value in the green light amplitude spectrum as the human pulse frequency.

[0115] It should be understood that, in this embodiment, the input unit 704 may include a graphics processing unit (GPU) 7041 and a microphone 7042. The GPU 7041 processes image data of still images or videos obtained by an image capture device (such as a camera) in video capture mode or image capture mode. The display unit 706 may include a display panel 7061, which may be configured in the form of a liquid crystal display, an organic light-emitting diode, or the like. The user input unit 707 includes at least one of a touch panel 7071 and other input devices 7072. The touch panel 7071 is also called a touch screen. The touch panel 7071 may include a touch detection device and a touch controller. Other input devices 7072 may include, but are not limited to, physical keyboards, function keys (such as volume control buttons, power buttons, etc.), trackballs, mice, and joysticks, which will not be described in detail here.

[0116] The memory 709 can be used to store software programs and various data. The memory 709 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store the operating system, application programs or instructions required for at least one function (such as sound playback function, image playback function, etc.). Furthermore, the memory 709 may include volatile memory or non-volatile memory, or both.

[0117] The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DRRAM). The memory 709 in this embodiment includes, but is not limited to, these and any other suitable types of memory.

[0118] Processor 710 may include one or more processing units. Optionally, processor 710 integrates an application processor and a modem processor, wherein the application processor mainly handles operations related to the operating system, user interface, and applications, and the modem processor mainly handles wireless communication signals, such as a baseband processor. It is understood that the aforementioned modem processor may also not be integrated into processor 710.

[0119] In one embodiment of this application, a program or instructions are stored on a readable storage medium. When the program or instructions are executed by a processor, they implement the various processes of the data processing method in any of the above embodiments and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0120] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0121] In one embodiment of this application, the chip includes a processor and a communication interface, the communication interface and the processor are coupled, the processor is used to run programs or instructions to implement the various processes of the data processing method in any of the above embodiments, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0122] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0123] In one embodiment of this application, a computer program product is stored in a storage medium and is executed by at least one processor to implement the various processes of the data processing method as described in any of the above embodiments, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0124] It should be noted that, in this document, 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. Unless otherwise specified, 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 that element.

[0125] Furthermore, it should be noted that the scope of the methods and apparatus in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. In addition, features described with reference to certain examples may be combined in other examples.

[0126] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0127] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A data processing method, characterized in that, include: Acquire health parameters, including photoplethysmography (PPG) signals; The green light amplitude spectrum, red light amplitude spectrum, and infrared light amplitude spectrum are determined based on the photoplethysmography pulse wave signal. The human pulse frequency is determined based on the green light amplitude spectrum. The red light signal-to-noise ratio, red light AC amplitude, and red light second harmonic amplitude are determined in the red light amplitude spectrum based on the human pulse frequency. The infrared light signal-to-noise ratio, infrared light AC amplitude, and infrared light second harmonic amplitude are determined in the infrared light amplitude spectrum based on the human pulse frequency. The red light harmonic amplitude ratio is determined based on the red light second harmonic amplitude and the red light AC amplitude, and the infrared light harmonic amplitude ratio is determined based on the infrared light second harmonic amplitude and the infrared light AC amplitude. Based on the red light signal-to-noise ratio, the infrared light signal-to-noise ratio, the red light harmonic amplitude ratio, and the infrared light harmonic amplitude ratio, determine whether the photoplethysmography (PPG) signal is a physiological signal. Once it is determined that the photoplethysmography signal is the physiological signal, blood oxygen saturation is determined.

2. The data processing method according to claim 1, characterized in that, Before determining the human pulse frequency based on the green light amplitude spectrum, the data processing method further includes: The DC amplitude of red light and the DC amplitude of infrared light are determined based on the photoplethysmography (PPG) signal. Determining blood oxygen saturation, in the case that the photoplethysmography signal is determined to be the physiological signal, includes: If the photoplethysmography (PPG) signal is determined to be the physiological signal, the blood oxygen saturation is determined based on the red light AC amplitude, the red light DC amplitude, the infrared light AC amplitude, and the infrared light DC amplitude.

3. The data processing method according to claim 1 or 2, characterized in that, The step of determining the human pulse frequency based on the green light amplitude spectrum includes: The frequency corresponding to the largest amplitude value in the green light amplitude spectrum is taken as the human pulse frequency.

4. A data processing apparatus, characterized in that, include: The acquisition module is used to acquire health parameters, including photoplethysmography (PPG) signals. The first determining module is used to determine the green light amplitude spectrum, red light amplitude spectrum and infrared light amplitude spectrum based on the photoplethysmography pulse wave signal. The second determining module is used to determine the human pulse frequency based on the green light amplitude spectrum. The third determining module is used to determine the red light signal-to-noise ratio, red light AC amplitude, and red light second harmonic amplitude in the red light amplitude spectrum based on the human pulse frequency, and to determine the infrared light signal-to-noise ratio, infrared light AC amplitude, and infrared light second harmonic amplitude in the infrared light amplitude spectrum based on the human pulse frequency. The fourth determining module is used to determine the red light harmonic amplitude ratio based on the red light second harmonic amplitude and the red light AC amplitude, and to determine the infrared light harmonic amplitude ratio based on the infrared light second harmonic amplitude and the infrared light AC amplitude. Based on the red light signal-to-noise ratio, the infrared light signal-to-noise ratio, the red light harmonic amplitude ratio, and the infrared light harmonic amplitude ratio, determine whether the photoplethysmography (PPG) signal is a physiological signal. Once it is determined that the photoplethysmography signal is the physiological signal, blood oxygen saturation is determined.

5. The data processing apparatus according to claim 4, characterized in that, Also includes: The fifth determining module is used to determine the DC amplitude of red light and the DC amplitude of infrared light based on the photoplethysmography (PPG) signal. The fourth determining module is further configured to determine blood oxygen saturation based on the red light AC amplitude, the red light DC amplitude, the infrared light AC amplitude, and the infrared light DC amplitude when the photoplethysmography signal is determined to be the physiological signal.

6. The data processing apparatus according to claim 4 or 5, characterized in that, The second determining module is specifically used to take the frequency corresponding to the largest amplitude value in the green light amplitude spectrum as the human pulse frequency.

7. An electronic device, characterized in that, It includes a processor and a memory, the memory storing a program or instructions that can run on the processor, the program or instructions being executed by the processor to implement the steps of the data processing method as described in any one of claims 1 to 3.

8. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the steps of the data processing method as described in any one of claims 1 to 3.

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