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

Abstract

Disclosed in the present application are a data processing method, a data processing apparatus, an electronic device, and a readable storage medium, which belong to the technical field of blood oxygen measurement. The data processing method comprises: acquiring a health parameter, the health parameter comprising a photoplethysmography signal; determining a green light amplitude frequency spectrum, a red light amplitude frequency spectrum, and an infrared light amplitude frequency spectrum according to the photoplethysmography signal; determining a human body pulse frequency according to the green light amplitude frequency spectrum; determining a first parameter according to the red light amplitude frequency spectrum and the human body pulse frequency, and determining a second parameter according to the infrared light amplitude frequency spectrum and the human body pulse frequency; and determining a blood oxygen saturation according to the first parameter and the second parameter.

Description

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

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to Chinese patent application No. 202410069116.4, filed on January 17, 2024, entitled “Data processing method, data processing device, electronic device and readable storage medium,” the entire contents of which are incorporated herein by reference. Technical Field

[0003] The present application belongs to the field of blood oxygen detection technology, and specifically relates to a data processing method, a data processing device, an electronic device and a readable storage medium. Background Art

[0004] Blood oxygen saturation (SaO2) is the percentage of oxygen-bound oxyhemoglobin (HbO2) in the blood to the total available hemoglobin (Hb) capacity, that is, the concentration of oxygen in the blood. It is a key physiological parameter of the respiratory circulation. When deoxyhemoglobin in the blood combines with oxygen entering the body, oxyhemoglobin is formed. The two have different absorption ratios for infrared and red light. Oxyhemoglobin absorbs less red light and more infrared light, while deoxyhemoglobin absorbs more red light and less infrared light. Wearable devices with blood oxygen monitoring capabilities typically utilize this characteristic to calculate blood oxygen saturation.

[0005] In related technologies, wearable smart devices such as smartwatches determine the parameters used to calculate blood oxygen saturation using only red and infrared light. In some applications, the reflected signals from these two light sources have low perfusion indices and weak signals, resulting in low accuracy in the calculated blood oxygen saturation. Summary of the Invention

[0006] The purpose of the embodiments of the present application is to provide a data processing method, a data processing device, an electronic device and a readable storage medium, which can solve the problem of low accuracy of blood oxygen saturation determined only by red light and infrared light.

[0007] In a first aspect, an embodiment of the present application provides a data processing method, which includes: obtaining health parameters, the health parameters including photoplethysmography signals; determining a green light amplitude spectrum, a red light amplitude spectrum, and an infrared light amplitude spectrum based on the photoplethysmography 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, and 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 parameter and the second parameter.

[0008] In a second aspect, an embodiment of the present application provides a data processing device, which includes: a processing unit, configured to determine a first parameter and a second parameter, and determine blood oxygen saturation based on the first parameter and the second parameter.

[0009] In a third aspect, an embodiment of the present application provides an electronic device comprising a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the programs or instructions are executed by the processor, the steps of the data processing method of the first aspect are implemented.

[0010] In a fourth aspect, an embodiment of the present application provides a readable storage medium that stores a program or instruction that can be run on a processor. When the program or instruction is executed by the processor, the steps of the data processing method of the first aspect are implemented.

[0011] In a fifth aspect, an embodiment of the present application provides a chip, which includes a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the steps of the data processing method of the first aspect.

[0012] In a sixth aspect, an embodiment of the present application provides a computer program product, which is stored in a storage medium and is executed by at least one processor to implement the steps of the data processing method of the first aspect.

[0013] In a seventh aspect, an embodiment of the present application further provides an electronic device configured to execute the steps of the data processing method of the first aspect.

[0014] The data processing method provided in the embodiment of the present application includes: obtaining health parameters, the health parameters including photoplethysmography signals; determining the green light amplitude spectrum, the red light amplitude spectrum and the infrared light amplitude spectrum according to the photoplethysmography signals; determining the human pulse frequency according to the green light amplitude spectrum; determining the first parameter according to the red light amplitude spectrum and the human pulse frequency, and determining the second parameter according to the infrared light amplitude spectrum and the human pulse frequency; and determining the blood oxygen saturation according to the first parameter and the second parameter. In the embodiment of the present application, the human pulse frequency is extracted by green light with a higher signal-to-noise ratio (the human pulse frequency is determined according to the green light amplitude spectrum), and the first parameter and the second parameter are determined according to 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 make it easier to extract signal features, and the first parameter and the second parameter obtained are more reliable, so that the blood oxygen saturation finally calculated can be more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] FIG1 is a flowchart of a data processing method according to an embodiment of the present application;

[0016] FIG2 is a second flowchart of the data processing method provided in an embodiment of the present application;

[0017] FIG3 is a third flow chart of the data processing method provided in an embodiment of the present application;

[0018] FIG4 is a fourth flowchart of the data processing method provided in an embodiment of the present application;

[0019] FIG5 is a structural block diagram of a data processing device provided in an embodiment of the present application;

[0020] FIG6 is a structural block diagram of an electronic device provided in an embodiment of the present application;

[0021] FIG7 is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application;

[0022] FIG8 is a schematic diagram of a photoplethysmography signal after DC component filtering according to an embodiment of the present application;

[0023] FIG9 is a schematic diagram of a green light amplitude spectrum, a red light amplitude spectrum, and an infrared light amplitude spectrum provided in an embodiment of the present application;

[0024] FIG10 is a schematic diagram of a green light amplitude spectrum provided in an embodiment of the present application;

[0025] FIG11 is a schematic diagram of a red light amplitude spectrum provided in an embodiment of the present application;

[0026] FIG12 is a schematic diagram of an infrared light amplitude spectrum according to an embodiment of the present application;

[0027] FIG13 is a second schematic diagram of the infrared light amplitude spectrum provided in an embodiment of the present application.

[0028] 5 , the correspondence between the reference numerals and component names is as follows: 500 : data processing device; 510 : acquisition module; 520 : first determination module; 530 : second determination module; 540 : third determination module; 550 : fourth determination module; 560 : fifth determination module. DETAILED DESCRIPTION

[0029] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0030] The terms "first," "second," and the like in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of this application can be implemented in an order other than that illustrated or described herein, and that the objects distinguished by "first," "second," and the like are generally of the same type, and do not limit the number of objects; for example, the first object can be one or more. In addition, the term "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0031] The data processing method, data processing device, electronic device, and readable storage medium provided in the embodiments of the present application are described in detail below with reference to specific embodiments and their application scenarios in conjunction with the accompanying drawings.

[0032] As shown in Figures 1, 2, and 3, an embodiment of the present application provides a data processing method. It should be noted that the data processing method can be implemented using a wearable device, and of course, it can also be implemented using other types of devices, such as mobile phones. The wearable device is a smart watch, smart bracelet, or other smart device that can be worn by a user.

[0033] In one embodiment of the present application, as shown in FIG1 , the specific steps of the data processing method include:

[0034] S102, obtaining health parameters, which include photoplethysmography signals.

[0035] The photoplethysmography (PPG) signal includes not only red and infrared light signals but also green light signals. The green, red, and infrared light signals are used to determine whether the conditions for calculating blood oxygen saturation are met. If the conditions for calculating blood oxygen saturation are met, the green, red, and infrared light signals are used to determine the parameters required for calculating blood oxygen saturation.

[0036] S104 , determining a green light amplitude spectrum, a red light amplitude spectrum, and an infrared light amplitude spectrum according to the photoplethysmography signal.

[0037] Optionally, the photoplethysmography signal is processed by a first filter, and the red light DC amplitude and the infrared light DC amplitude are extracted from the photoplethysmography signal. The purpose of this step is to pre-process the photoplethysmography signal. The frequency of the human body's photoplethysmography signal is usually between 0.5Hz and 5Hz. Taking into account the presence of harmonics in the photoplethysmography signal, and the third and higher harmonics are not very obvious, the photoplethysmography signal is processed by a first filter in this step. Optionally, the first filter is a low-pass filter. A low-pass filter is an electronic filtering device that allows signals below the cut-off frequency to pass, but does not allow signals above the cut-off frequency to pass. Optionally, the cut-off frequency of the low-pass filter is 14Hz to 16Hz. Optionally, the cut-off 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 ) as a parameter for calculating blood oxygen saturation in subsequent steps.

[0038] Optionally, the DC component in the photoplethysmography signal is removed by a second filter, and the green light amplitude spectrum, the red light amplitude spectrum, and the infrared light amplitude spectrum are determined. Optionally, the second filter is a high-pass filter. A high-pass filter is an electronic filtering device that allows signals above the cutoff frequency to pass through, but does not allow signals below the cutoff frequency to pass through. Optionally, the cutoff frequency of the high-pass filter is 0.4Hz to 0.6Hz. The cutoff frequency of the high-pass filter is 0.5Hz. Figure 8 is a schematic diagram of the photoplethysmography signal after the DC component is filtered out provided in an embodiment of the present application. After the DC component in the photoplethysmography signal is removed by the second filter, the green light amplitude spectrum is determined by Fourier transform based on the green light signal; the red light amplitude spectrum is determined by Fourier transform based on the red light signal; and the infrared light amplitude spectrum is determined by Fourier transform based on the infrared light signal. Figure 9 is a schematic diagram of the green light amplitude spectrum, the red light amplitude spectrum, and the infrared light amplitude spectrum provided in an embodiment of the present application. It should be noted that Fourier transform belongs to harmonic analysis. In signal processing, the Fourier transform is used to decompose a signal into a frequency spectrum (amplitude spectrum). The frequency spectrum is used to show the amplitude corresponding to the frequency.

[0039] S106, determining the human body pulse frequency according to the green light amplitude spectrum.

[0040] Compared with red light and infrared light, green light is more easily absorbed by oxygenated hemoglobin and deoxygenated hemoglobin. Red light and infrared light can pass through skin tissue more easily than green light, so in a reflective blood oxygen measurement device, green light has a larger signal variation amplitude and a high signal-to-noise ratio. The signal-to-noise ratio (Signal to Interference plus Noise Ratio) refers to the ratio of the intensity of the received useful signal to the intensity of the received interference signal (noise and interference). Although the signal-to-noise ratio of the photoelectric volumetric pulse wave signals collected by light of different wavelengths is different, the frequency of the pulse is the same, that is, the frequency of the pulse (human pulse frequency) can be extracted using green light with a high signal-to-noise ratio, and the human pulse frequency is easier to determine based on the green light amplitude spectrum, and the measurement result is more accurate. Optionally, as shown in Figure 10, the frequency corresponding to the maximum amplitude in the green light amplitude spectrum is taken as the human pulse frequency F pulse .

[0041] S108 , 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.

[0042] Optionally, the first parameter includes a red light signal-to-noise ratio, a red light AC amplitude, and a red light second harmonic amplitude.

[0043] Optionally, the second parameter includes an infrared light signal-to-noise ratio, an infrared light AC amplitude, and an infrared light second harmonic amplitude.

[0044] Optionally, the red light signal-to-noise ratio (SNR) is determined based on the red light amplitude spectrum and the human pulse frequency. red ; Determine the infrared light signal-to-noise ratio (SNR) based on the infrared light amplitude spectrum and human pulse frequency ir Optionally, as shown in FIG11 , the red light AC amplitude AC can also be determined based on the red light amplitude spectrum and the human pulse frequency. red The red light AC amplitude is the amplitude corresponding to the human pulse frequency in the red light amplitude spectrum. The amplitude corresponding to P1 in Figure 11 is the correct red light AC amplitude AC red In Figure 11, the amplitude corresponding to P2 and the amplitude corresponding to P3 are both greater than the amplitude corresponding to P1. If the human pulse frequency is not found using the green light amplitude spectrum, it is easy to mistake the amplitude corresponding to P2 and the amplitude corresponding to P3 as the red light AC amplitude. Optionally, as shown in Figure 12, the infrared light AC amplitude AC can also be determined based on the infrared light amplitude spectrum and the human pulse frequency. ir The infrared light AC amplitude is the amplitude corresponding to the human pulse frequency in the infrared light amplitude spectrum. The amplitude corresponding to P1 in Figure 12 is the correct infrared light AC amplitude AC irOptionally, the second harmonic frequency is determined based on the human pulse frequency. Twice the human pulse frequency is used as the second harmonic frequency. Optionally, the red light second harmonic amplitude A 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, as shown in FIG13 , the second harmonic amplitude of infrared light A 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 amplitude corresponding to P1 in Figure 13 is the correct infrared light AC amplitude AC ir The amplitude corresponding to P2 in Figure 13 is the correct infrared light second harmonic amplitude A ir2 Optionally, the red light harmonic amplitude ratio Harmonic_ratio is determined according to the red light second harmonic amplitude and the red light AC amplitude. red Optionally, the infrared light harmonic amplitude ratio Harmonic_ratio is determined according to the infrared light second harmonic amplitude and the infrared light AC amplitude. ir . Since the human body's photoplethysmography signal usually has obvious second harmonics, interference usually makes it difficult to form second harmonics. Whether there is obvious second harmonics in the signal spectrum can be used to determine whether the photoplethysmography signal is a physiological signal. Considering that the 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 using the second harmonic amplitude to judge will 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 the signal-to-noise ratio and the harmonic amplitude meet the blood oxygen detection conditions at the same time, the blood oxygen saturation is further calculated.

[0045] S110: Determine the blood oxygen saturation according to the first parameter and the second parameter.

[0046] Whether to calculate blood oxygen saturation is determined 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 signal is determined to be a physiological signal and suitable for calculating blood oxygen saturation, the 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. This method of determining whether the photoplethysmography signal is a physiological signal and suitable for calculating blood oxygen saturation by coordinating the signal-to-noise ratio and harmonic amplitude ratio is less likely to misidentify non-physiological signals as physiological signals, and less likely to misidentify weak signals as non-physiological signals, compared to methods that determine the quality of photoplethysmography signals based on the correlation coefficient between the AC portion of the red light signal and the AC portion of the green light signal, or the correlation coefficient between the AC portion of the infrared light signal and the AC portion of the green light signal, resulting in more accurate judgments.

[0047] In the embodiments of the present application, the human pulse frequency is extracted using green light having a higher signal-to-noise ratio (determining the human pulse frequency based on the green light amplitude spectrum), and the first parameter and the 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 determining the parameters used to calculate the blood oxygen saturation makes it easier to extract signal features, and the obtained first and second parameters are more reliable, thereby ultimately achieving a more accurate blood oxygen saturation calculation.

[0048] In another embodiment of the present application, as shown in FIG2 , step S108 specifically includes:

[0049] S1081, determining a red light signal-to-noise ratio, a red light alternating current amplitude, and a red light second harmonic amplitude in a red light amplitude spectrum according to a human pulse frequency, and determining an infrared light signal-to-noise ratio, an infrared light alternating current amplitude, and an infrared light second harmonic amplitude in an infrared light amplitude spectrum according to a human pulse frequency.

[0050] Optionally, the red light signal-to-noise ratio (SNR) is determined based on the red light amplitude spectrum and the human pulse frequency. red ; Determine the infrared light signal-to-noise ratio (SNR) based on the infrared light amplitude spectrum and human pulse frequency ir Optionally, the red light AC amplitude, the red light second harmonic amplitude, the infrared light AC amplitude and the infrared light second harmonic amplitude are determined according to the human pulse frequency. As shown in FIG11 , the red light AC amplitude AC can also be determined according to the red light amplitude spectrum and the human pulse frequency. red The red light AC amplitude is the amplitude corresponding to the human pulse frequency in the red light amplitude spectrum. The amplitude corresponding to P1 in Figure 11 is the correct red light AC amplitude AC red In Figure 11, the amplitude corresponding to P2 and the amplitude corresponding to P3 are both greater than the amplitude corresponding to P1. If the human pulse frequency is not found using the green light amplitude spectrum, it is easy to mistake the amplitude corresponding to P2 and the amplitude corresponding to P3 as the red light AC amplitude. Optionally, as shown in Figure 12, the infrared light AC amplitude AC can also be determined based on the infrared light amplitude spectrum and the human pulse frequency. ir The infrared light AC amplitude is the amplitude corresponding to the human pulse frequency in the infrared light amplitude spectrum. The amplitude corresponding to P1 in Figure 12 is the correct infrared light AC amplitude AC ir Optionally, the second harmonic frequency is determined based on the human pulse frequency. Twice the human pulse frequency is used as the second harmonic frequency. Optionally, the red light second harmonic amplitude A 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, as shown in FIG13 , the second harmonic amplitude of infrared light A is determined based on the infrared light amplitude spectrum and the second harmonic frequency. ir2The second harmonic amplitude of infrared light is the amplitude corresponding to the second harmonic frequency in the infrared light amplitude spectrum. The amplitude corresponding to P1 in Figure 13 is the correct infrared light AC amplitude AC ir The amplitude corresponding to P2 in Figure 13 is the correct infrared light second harmonic amplitude A ir2 .

[0051] In another embodiment of the present application, as shown in FIG2 , step S110 includes:

[0052] S1101 , determining a red light harmonic amplitude ratio according to the red light second harmonic amplitude and the red light AC amplitude, and determining an infrared light harmonic amplitude ratio according to the infrared light second harmonic amplitude and the infrared light AC amplitude.

[0053] Optionally, the infrared light second harmonic amplitude A is determined according to 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. red It is the ratio of the red light second harmonic amplitude to the red light AC amplitude. ir It is the ratio of the second harmonic amplitude of infrared light to the AC amplitude of infrared light.

[0054] S1102 , determining whether the photoplethysmography 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.

[0055] When both the red light signal-to-noise ratio and the infrared light signal-to-noise ratio meet the threshold requirements, the signal segment meets the blood oxygen detection criteria. When either the red light signal-to-noise ratio or the infrared light signal-to-noise ratio does not meet the threshold requirements, the signal segment is considered to be unqualified for blood oxygen detection. Furthermore, since human photoplethysmography signals typically have a significant second harmonic, interference often prevents this from forming. The presence of a significant second harmonic in the signal spectrum can be used to determine whether the photoplethysmography 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 low luminous current, directly using the second harmonic amplitude can easily misinterpret a weak signal as a non-physiological signal. Instead, using the ratio of the second harmonic amplitude to the AC amplitude to determine whether the signal is a physiological signal is more appropriate. When both the signal-to-noise ratio and the harmonic amplitude meet the blood oxygen detection criteria, blood oxygen saturation is further calculated.

[0056] S1103 : When it is determined that the photoplethysmography signal is a physiological signal, determine the blood oxygen saturation.

[0057] Optionally, 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.

[0058] Optionally, a first ratio 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; and the blood oxygen saturation is determined based on the first ratio.

[0059] 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 infrared light AC amplitude to the infrared light DC amplitude (AC ir / DC ir ). The first ratio R=(AC red / DC red ) / (AC ir / DC ir ).

[0060] 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 the blood oxygen saturation, R is the first ratio, and A, B, and C are constants.

[0061] It should be noted that the first formula was determined through hypoxia experiments. During the experiment, data was collected to calculate the ratio R (the first ratio), and a blood gas analyzer was used to obtain the blood oxygen saturation at the corresponding moment as the gold standard blood oxygen saturation result. The first formula was obtained by fitting several R values ​​with the gold standard blood oxygen saturation result to determine the functional relationship.

[0062] In another embodiment of the present application, as shown in FIG3 , before step S106 , the data processing method further includes:

[0063] The red light DC amplitude and the infrared light DC amplitude are determined according to the photoplethysmography signal.

[0064] Optionally, this step is the same as the above step S104. This step is used to determine the DC amplitude of the red light (DC red ) and infrared light DC amplitude (DC ir ), which is used as a parameter for calculating blood oxygen saturation in subsequent steps. Optionally, a second filter is used to remove the DC component in the photoplethysmography signal, and the green light amplitude spectrum, the red light amplitude spectrum, and the infrared light amplitude spectrum are determined.

[0065] Optionally, the second filter is a high-pass filter. A high-pass filter is an electronic filtering device that allows signals above the cutoff frequency to pass through, but does not allow signals below the cutoff frequency to pass through. Optionally, the cutoff frequency of the high-pass filter is 0.4Hz to 0.6Hz. The cutoff frequency of the high-pass filter is 0.5Hz. Figure 8 is a schematic diagram of the photoplethysmography signal after the DC component is filtered out according to an embodiment of the present application. After the DC component in the photoplethysmography signal is removed by the second filter, the green light amplitude spectrum is determined by Fourier transform based on the green light signal; the red light amplitude spectrum is determined by Fourier transform based on the red light signal; and the infrared light amplitude spectrum is determined by Fourier transform based on the infrared light signal. Figure 9 is a schematic diagram of the green light amplitude spectrum, red light amplitude spectrum and infrared light amplitude spectrum provided in an embodiment of the present application. It should be noted that Fourier transform belongs to harmonic analysis. In signal processing, the purpose of Fourier transform is to decompose the signal into a frequency spectrum (amplitude spectrum). The frequency spectrum is used to display the amplitude corresponding to the frequency.

[0066] S1103 specifically includes: when it is determined that the photoplethysmography signal is a physiological signal, determining the blood oxygen saturation according to the red light AC amplitude, the red light DC amplitude, the infrared light AC amplitude, and the infrared light DC amplitude.

[0067] Optionally, a first ratio 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; and the blood oxygen saturation is determined based on the first ratio.

[0068] In another embodiment of the present application, as shown in FIG3 , step S106 includes:

[0069] S1061: The frequency corresponding to the maximum amplitude in the green light amplitude spectrum is used as the human body pulse frequency.

[0070] As shown in Figure 13, the frequency corresponding to the maximum peak in the green light amplitude spectrum is found as the human pulse frequency. The maximum peak is the maximum amplitude.

[0071] In an embodiment of the present application, the human pulse frequency is extracted by green light with a higher signal-to-noise ratio, and the red light signal-to-noise ratio and infrared light signal-to-noise ratio are determined based on the human pulse frequency. This method makes it easier to extract signal features, and the blood oxygen saturation finally calculated can be more accurate.

[0072] In one embodiment of the present application, as shown in FIG4 , the specific steps of the data processing method include:

[0073] S402 , obtaining health parameters, which include photoplethysmography signals.

[0074] S404 , processing the photoplethysmography signal through a first filter, and extracting the red light DC amplitude and the infrared light DC amplitude from the photoplethysmography signal.

[0075] S406 , removing a DC component from the photoplethysmography signal through a second filter, and determining a green light amplitude spectrum, a red light amplitude spectrum, and an infrared light amplitude spectrum.

[0076] S408 , determining the human pulse frequency according to the green light amplitude spectrum, and determining the red light signal-to-noise ratio and the infrared light signal-to-noise ratio according to the human pulse frequency.

[0077] S410 , determining the red light AC amplitude, the red light second harmonic amplitude, the infrared light AC amplitude, and the infrared light second harmonic amplitude according to the human body pulse frequency.

[0078] S412, determining a red light harmonic amplitude ratio according to the red light second harmonic amplitude and the red light AC amplitude, and determining an infrared light harmonic amplitude ratio according to the infrared light second harmonic amplitude and the infrared light AC amplitude.

[0079] S414 , determining whether the red light signal-to-noise ratio is greater than a first threshold, the infrared light signal-to-noise ratio is greater than a second threshold, the red light harmonic amplitude ratio is greater than a third threshold, and the infrared light harmonic amplitude ratio is greater than a fourth threshold, and generating a first determination result.

[0080] To determine whether a photoplethysmography signal is a physiological signal and suitable for calculating blood oxygen saturation, four conditions must be met. The first condition is that the red light signal-to-noise ratio is greater than the first threshold; the second condition is that the infrared light signal-to-noise ratio is greater than the second threshold; the third condition is that the red light harmonic amplitude ratio is greater than the third threshold; and the fourth condition is that the infrared light harmonic amplitude ratio is greater than the fourth threshold. When both the red light signal-to-noise ratio and the infrared light signal-to-noise ratio meet the threshold requirements, it indicates that this signal segment meets the blood oxygen detection conditions; when the red light signal-to-noise ratio or the infrared light signal-to-noise ratio does not meet the threshold requirements, it is considered that this signal segment does not meet the blood oxygen detection conditions. In addition, because the human body's photoplethysmography signal usually has a significant second harmonic, interference usually makes it difficult to form a second harmonic. The presence of a significant second harmonic in the signal spectrum can be used to determine whether the photoplethysmography signal is a physiological signal. Considering that signal strength is affected by factors such as the sensor's luminous current, when the luminous current is low and the signal is weak, directly using the second harmonic amplitude can 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 the signal-to-noise ratio and harmonic amplitude both meet the blood oxygen detection conditions, blood oxygen saturation is further calculated.

[0081] S416: If the first judgment result is yes, the photoplethysmography signal is a physiological signal and is suitable for calculating blood oxygen saturation.

[0082] When all four conditions (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) are met, it indicates that the photoplethysmography signal is a physiological signal and is suitable for calculating blood oxygen saturation.

[0083] S418 , determining a first ratio according to the red light AC amplitude, the red light DC amplitude, the infrared light AC amplitude, and the infrared light DC amplitude.

[0084] 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; and the fourth ratio is the ratio of the infrared light AC amplitude to the infrared light DC amplitude.

[0085] S420: Determine the blood oxygen saturation according to the first ratio.

[0086] 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 the blood oxygen saturation, R is the first ratio, and A, B, and C are constants.

[0087] S422: If the first judgment result is no, the photoplethysmography signal is not a physiological signal and / or the photoplethysmography signal is not suitable for calculating blood oxygen saturation.

[0088] If at least one of the four conditions (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) is not met, it means that the photoplethysmography signal is not a physiological signal and / or the photoplethysmography signal is not suitable for calculating blood oxygen saturation, and it is necessary to return to S402.

[0089] In the embodiments of the present application, first, 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 the infrared light AC amplitude is more reliable than directly extracting the red light AC amplitude and the infrared light AC amplitude, thereby providing a more accurate blood oxygen saturation calculation. Second, the photoplethysmography signal is judged to be a physiological signal and suitable for calculating blood oxygen saturation by combining the signal-to-noise ratio with the harmonic amplitude ratio. Compared to judging the quality of the photoplethysmography signal based on the correlation coefficient between the AC portion of the red light signal and the AC portion of the green light signal, or the correlation coefficient between the AC portion of the infrared light signal and the AC portion of the green light signal, this judgment method is less likely to misjudge a non-physiological signal as a physiological signal, and less likely to misjudge a weak signal as a non-physiological signal, resulting in a more accurate judgment result.

[0090] As shown in FIG5 , an embodiment of the present application provides a data processing device 500 , which 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 .

[0091] The acquisition module 510 is used to acquire health parameters, including photoplethysmography signals;

[0092] The first determination module 520 is used to determine the green light amplitude spectrum, the red light amplitude spectrum and the infrared light amplitude spectrum according to the photoplethysmography signal;

[0093] The second determination module 530 is used to determine the human body pulse frequency according to the green light amplitude spectrum;

[0094] The third determination module 540 is configured to determine a first parameter based on the red light amplitude spectrum and the human pulse frequency, and to determine a second parameter based on the infrared light amplitude spectrum and the human pulse frequency;

[0095] The fourth determining module 550 is configured to determine the blood oxygen saturation according to the first parameter and the second parameter.

[0096] Optionally, the third determination module 540 is specifically used to determine the red light signal-to-noise ratio, the red light AC amplitude and the red light second harmonic amplitude in the red light amplitude spectrum according to the human pulse frequency, and to determine the infrared light signal-to-noise ratio, the infrared light AC amplitude and the infrared light second harmonic amplitude in the infrared light amplitude spectrum according to the human pulse frequency.

[0097] Optionally, the fourth determination 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 determine the infrared light harmonic amplitude ratio based on the infrared light second harmonic amplitude and the infrared light AC amplitude; determine whether the photoplethysmography 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 determine the blood oxygen saturation when it is determined that the photoplethysmography signal is a physiological signal.

[0098] Optionally, the data processing device 500 further includes a fifth determining module 560, and the fifth determining module 560 is configured to determine the red light AC amplitude and the red light DC amplitude according to the photoplethysmography signal.

[0099] In addition, the fourth determination module 550 is further configured to determine the blood oxygen saturation according to the red light AC amplitude, the red light DC amplitude, the infrared light AC amplitude, and the infrared light DC amplitude when it is determined that the photoplethysmography signal is a physiological signal.

[0100] Optionally, the second determining module 530 is specifically configured to use the frequency corresponding to the maximum amplitude in the green light amplitude spectrum as the human pulse frequency.

[0101] In the embodiment of the present application, the human pulse frequency is extracted using green light with a higher signal-to-noise ratio (determined 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 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, thereby ultimately achieving a more accurate blood oxygen saturation calculation.

[0102] The data processing device 500 in the embodiment of the present application can be an electronic device or a component in an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other device other than a terminal. For example, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a mobile Internet device (MID), an augmented reality (AR) / virtual reality (VR) device, a robot, a wearable device, an ultra-mobile personal computer (UMPC), a netbook or a personal digital assistant (PDA), etc. It can also be a server, a network attached storage (NAS), a personal computer (PC), a television (TV), a teller machine or a self-service machine, etc., and the embodiment of the present application does not specifically limit it.

[0103] The data processing device 500 in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0104] The data processing device 500 provided in the embodiment of the present application can implement each process implemented by the method embodiments of Figures 1 to 4, and has the beneficial effects of any of the above embodiments. To avoid repetition, they will not be described here.

[0105] In one embodiment of the present application, as shown in Figure 6, the electronic device 600 includes a processor 602 and a memory 604, and the memory 604 stores programs or instructions that can be run on the processor 602. When the program or instruction is executed by the processor 602, the various steps of the data processing method in any of the above embodiments are implemented and the same technical effect can be achieved. To avoid repetition, they are not repeated here.

[0106] It should be noted that the electronic device 600 in the embodiment of the present application includes the above-mentioned mobile electronic device and non-mobile electronic device.

[0107] FIG7 is a schematic diagram of the hardware structure of an electronic device implementing an embodiment of the present application.

[0108] The electronic device 700 includes but is not limited to: a radio frequency unit 701, a network module 702, an audio output unit 703, an input unit 704, a sensor 705, a display unit 706, a user input unit 707, an interface unit 708, a memory 709 and a processor 710.

[0109] Those skilled in the art will appreciate that the electronic device 700 may further include a power source (e.g., a battery) to power various components. The power source may be logically connected to the processor 710 via a power management system, thereby enabling the power management system to manage charging, discharging, and power consumption. The electronic device structure shown in FIG7 does not limit the electronic device. The electronic device may include more or fewer components than shown, or may combine certain components or arrange the components differently, which will not be described in detail here.

[0110] Among them, processor 710 is used to obtain health parameters, which include photoplethysmography signals; determine the green light amplitude spectrum, red light amplitude spectrum and infrared light amplitude spectrum based on the photoplethysmography signals; determine the human pulse frequency based on the green light amplitude spectrum; 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; determine the blood oxygen saturation based on the first parameter and the second parameter.

[0111] Optionally, the processor 710 is specifically used to determine the red light signal-to-noise ratio, the red light AC amplitude and the red light second harmonic amplitude in the red light amplitude spectrum according to the red light amplitude spectrum and the human pulse frequency, and to determine the infrared light signal-to-noise ratio, the infrared light AC amplitude and the infrared light second harmonic amplitude according to the human pulse frequency in the infrared light amplitude spectrum and the human pulse frequency.

[0112] Optionally, the processor 710 is specifically configured to determine a red light harmonic amplitude ratio according to the red light second harmonic amplitude and the red light AC amplitude, and determine an infrared light harmonic amplitude ratio according to the infrared light second harmonic amplitude and the infrared light AC amplitude;

[0113] determining whether the photoplethysmography 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;

[0114] When it is determined that the photoplethysmography signal is a physiological signal, the blood oxygen saturation is determined.

[0115] Optionally, the processor 710 is specifically used to determine the red light DC amplitude and the infrared light DC amplitude based on the photoplethysmography signal; when it is determined that the photoplethysmography signal is a 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.

[0116] Optionally, the processor 710 is specifically configured to use the frequency corresponding to the maximum amplitude in the green light amplitude spectrum as the human pulse frequency.

[0117] It should be understood that in an embodiment of the present application, the input unit 704 may include a graphics processing unit (GPU) 7041 and a microphone 7042, and the graphics processor 7041 processes the image data of a static picture or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The display unit 706 may include a display panel 7061, and the display panel 7061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 707 includes a touch panel 7071 and at least one of other input devices 7072. The touch panel 7071 is also called a touch screen. The touch panel 7071 may include two parts: a touch detection device and a touch controller. Other input devices 7072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and an operating stick, which will not be repeated here.

[0118] The memory 709 can be used to store software programs and various data. The memory 709 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store an operating system, applications or instructions required for at least one function (such as a sound playback function, an image playback function, etc.). In addition, the memory 709 may include volatile memory or non-volatile memory, or the memory 709 may include both volatile and non-volatile memory.

[0119] Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM) or a flash memory. The volatile memory can be a random access memory (RAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDRSDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synchronous link dynamic random access memory (SLDRAM) and a direct memory bus random access memory (DRRAM). The memory 709 in the embodiment of the present application includes but is not limited to these and any other suitable types of memory.

[0120] Processor 710 may include one or more processing units. Optionally, processor 710 integrates an application processor and a modem processor. The application processor primarily handles operations related to the operating system, user interface, and application programs, while the modem processor primarily processes wireless communication signals, such as a baseband processor. It is understood that the modem processor may not be integrated into processor 710.

[0121] In one embodiment of the present application, a program or instruction is stored on a readable storage medium. When the program or instruction is executed by a processor, the various processes of the data processing method in any of the above embodiments are implemented and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0122] The processor is the processor in the electronic device in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0123] In one embodiment of the present application, the chip includes a processor and a communication interface, the communication interface and the processor are coupled, and 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 achieve the same technical effect. To avoid repetition, they will not be described here.

[0124] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0125] In one embodiment of the present application, a computer program product is stored in a storage medium, and the program product is executed by at least one processor 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 repeated here.

[0126] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0127] Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of the present application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in reverse order depending on the functions involved. For example, the methods described may be performed in an order different from that described, and various steps may be added, omitted, or combined. Furthermore, features described with reference to certain examples may be combined in other examples.

[0128] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course 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 the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of each embodiment of the present application.

[0129] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

Claims

1. A data processing method, comprising: Obtaining health parameters, where the health parameters include photoplethysmogram signals; Determining a green light amplitude spectrum, a red light amplitude spectrum, and an infrared light amplitude spectrum according to the photoplethysmogram 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; Determining a blood oxygen saturation according to the first parameter and the second parameter.

2. The data processing method according to claim 1, wherein, The step of 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 includes: Determining a red light signal-to-noise ratio, a red light AC amplitude, and a red light second harmonic amplitude in the red light amplitude spectrum according to the human pulse frequency, and determining an infrared light signal-to-noise ratio, an infrared light AC amplitude, and an infrared light second harmonic amplitude in the infrared light amplitude spectrum according to the human pulse frequency.

3. The data processing method according to claim 2, wherein, The step of determining a blood oxygen saturation according to the first parameter and the second parameter includes: Determining a red light harmonic amplitude ratio according to the red light second harmonic amplitude and the red light AC amplitude, and determining an infrared light harmonic amplitude ratio according to the infrared light second harmonic amplitude and the infrared light AC amplitude; Determining whether the photoplethysmogram signal is a physiological signal according to 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; Determining the blood oxygen saturation when it is determined that the photoplethysmogram signal is the physiological signal.

4. The data processing method according to claim 3, before determining the human pulse frequency according to the green light amplitude spectrum, the data processing method further includes: Determining a red light DC amplitude and an infrared light DC amplitude according to the photoplethysmogram signal; The step of determining the blood oxygen saturation when it is determined that the photoplethysmogram signal is the physiological signal includes: When it is determined that the photoplethysmogram signal is the physiological signal, determining the blood oxygen saturation according to the red light AC amplitude, the red light DC amplitude, the infrared light AC amplitude, and the infrared light DC amplitude.

5. The data processing method according to any one of claims 1 to 4, wherein The step of determining the human pulse frequency according to the green light amplitude spectrum includes: Taking the frequency corresponding to the maximum amplitude in the green light amplitude spectrum as the human pulse frequency.

6. A data processing apparatus, comprising: An obtaining module, configured to obtain health parameters, where the health parameters include photoplethysmogram signals; A first determining module, configured to determine a green light amplitude spectrum, a red light amplitude spectrum, and an infrared light amplitude spectrum according to the photoplethysmogram signal; A second determining module, configured to determine a human pulse frequency according to the green light amplitude spectrum; A third determining module, configured to determine a first parameter according to the red light amplitude spectrum and the human pulse frequency, and determine a second parameter according to the infrared light amplitude spectrum and the human pulse frequency; A fourth determining module, configured to determine a blood oxygen saturation according to the first parameter and the second parameter.

7. The data processing device according to claim 6, wherein, The third determination module is specifically configured to determine the red light signal-to-noise ratio, the red light alternating current amplitude, and the red light second harmonic amplitude in the red light amplitude spectrum according to the human pulse frequency, and determine the infrared light signal-to-noise ratio, the infrared light alternating current amplitude, and the infrared light second harmonic amplitude in the infrared light amplitude spectrum according to the human pulse frequency.

8. The data processing apparatus according to claim 7, wherein, The fourth determination module is specifically configured to determine the red light harmonic amplitude ratio according to the red light second harmonic amplitude and the red light alternating current amplitude, and determine the infrared light harmonic amplitude ratio according to the infrared light second harmonic amplitude and the infrared light alternating current amplitude; Determine whether the photoplethysmogram signal is a physiological signal according to 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; When it is determined that the photoplethysmogram signal is the physiological signal, determine the blood oxygen saturation.

9. The data processing device according to claim 8, further comprising: A fifth determination module, configured to determine the red light direct current amplitude and the infrared light direct current amplitude according to the photoplethysmogram signal, wherein the fourth determination module is further configured to, when it is determined that the photoplethysmogram signal is the physiological signal, determine the blood oxygen saturation according to the red light alternating current amplitude, the red light direct current amplitude, the infrared light alternating current amplitude, and the infrared light direct current amplitude.

10. The data processing device according to any one of claims 6 to 9, wherein, The second determination module is specifically configured to use the frequency corresponding to the maximum amplitude in the green light amplitude spectrum as the human pulse frequency.

11. An electronic device, comprising a processor and a memory, where the memory stores a program or instruction that can run on the processor, and when the program or the instruction is executed by the processor, the steps of the data processing method according to any one of claims 1 to 5 are implemented.

12. A readable storage medium, where the readable storage medium stores a program or instruction, and when the program or the instruction is executed by a processor, the steps of the data processing method according to any one of claims 1 to 5 are implemented.

13. A computer program product, where the program product is stored in a storage medium, and the program product is executed by at least one processor to implement the steps of the data processing method according to any one of claims 1-5.

14. An electronic device, configured to execute the steps of the data processing method according to any one of claims 1-5.

15. A chip, the chip includes a processor and a communication interface, the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the steps of the data processing method according to any one of claims 1-5.

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