Blood oxygen value determination method and device, equipment, storage medium and program product

Abstract

The invention relates to a blood oxygen value determination method and device, equipment, a storage medium and a program product. The method comprises the following steps: acquiring a first photoelectric volume pulse wave signal and a motion signal of a detected object, wherein the first photoelectric volume pulse wave signal is superposed with motion noise; performing denoising processing on the first photoelectric volume pulse wave signal according to a denoising model to determine a second photoelectric volume pulse wave signal; and determining a blood oxygen value according to the second photoelectric volume pulse wave signal. According to the method, the obtained first photoelectric volume pulse wave signal is subjected to denoising processing, interference of motion noise on the photoelectric volume pulse wave signal is removed, then the blood oxygen value is determined, the influence of the motion noise can be avoided, and therefore the accuracy of determining the blood oxygen value is effectively improved.

Description

Technical Field

[0001] The present application relates to the field of blood oxygen detection technology, and in particular to a method, apparatus, device, storage medium and program product for determining a blood oxygen value. Background Art

[0002] Blood oxygen value, also known as blood oxygen saturation, is one of the important basic data in clinical medicine. The blood oxygen value refers to the percentage of the combined O2 capacity in the total blood volume to the total available O2 capacity. The normal blood oxygen value of the human body should be between 94% and 98%. The blood oxygen value can be tested by a pulse oximeter.

[0003] Currently, existing pulse oximeters are usually of the finger-clip contact type. Due to the consideration of detection accuracy, blood oxygen saturation is most often measured on the finger.

[0004] However, existing pulse oximeters usually require users to measure blood oxygen levels in a resting state, and the accuracy of blood oxygen values ​​measured during sleep or exercise is low. Summary of the Invention

[0005] Based on this, it is necessary to provide a blood oxygen value determination method, device, equipment, storage medium and program product that can improve the accuracy of blood oxygen value calculation in response to the above technical problems.

[0006] In a first aspect, the present application provides a method for calculating blood oxygen levels, comprising:

[0007] Acquiring a first photoplethysmography signal and a motion signal of the subject, wherein the first photoplethysmography signal is superimposed with motion noise;

[0008] Denoising the first photoplethysmography signal according to a denoising model to determine a second photoplethysmography signal;

[0009] The blood oxygen value is determined based on the second photoplethysmography signal.

[0010] In one embodiment, the blood oxygen value determination method further includes:

[0011] Obtain fixed signal samples emitted by the simulator;

[0012] When a fixed signal sample is applied to the pulse oximeter and the pulse oximeter is interfered with by noise, obtaining an actual signal sample received by the pulse oximeter and a motion signal sample of the pulse oximeter; the actual signal sample includes a noise signal;

[0013] The fixed signal samples, actual signal samples and motion signal samples are fitted to obtain a denoising model.

[0014] In one embodiment, performing denoising on the first photoplethysmography signal according to a denoising model to determine the second photoplethysmography signal includes:

[0015] Inputting the first photoplethysmography signal and the motion signal into a denoising model to obtain a noise signal output by the denoising model;

[0016] A second photoplethysmography signal is determined based on the first photoplethysmography signal and the noise signal.

[0017] In one embodiment, determining a second photoplethysmography signal based on a first photoplethysmography signal and a noise signal includes:

[0018] A second photoplethysmography signal is obtained by removing a noise signal from the first photoplethysmography signal.

[0019] In one embodiment, determining a blood oxygen value based on a second photoplethysmography signal includes:

[0020] determining an AC component and a DC component corresponding to a second photoplethysmography signal;

[0021] The blood oxygen value is determined based on the AC component and the DC component.

[0022] In a second aspect, the present application further provides a blood oxygen value determination device, which is provided in a pulse oximeter and includes:

[0023] an acquisition module, configured to acquire a first photoplethysmography signal and a motion signal of a measured object, wherein the first photoplethysmography signal is superimposed with motion noise;

[0024] a denoising module, configured to perform denoising processing on the first photoplethysmography signal according to a denoising model to determine a second photoplethysmography signal;

[0025] The determination module is configured to determine the blood oxygen value according to the second photoplethysmography signal.

[0026] In one embodiment, the blood oxygen value determination device further includes a fitting module;

[0027] The acquisition module is also used to obtain fixed signal samples emitted by the simulator;

[0028] The acquisition module is further configured to acquire, when the fixed signal sample is applied to the pulse oximeter and the pulse oximeter is interfered with by noise, an actual signal sample received by the pulse oximeter and a motion signal sample of the pulse oximeter; the actual signal sample includes a noise signal;

[0029] The fitting module is used to perform fitting processing on fixed signal samples, actual signal samples and motion signal samples to obtain a denoising model.

[0030] In one embodiment, the denoising module is specifically configured to input the first photoplethysmography signal and the motion signal into a denoising model to obtain a noise signal output by the denoising model; and determine the second photoplethysmography signal based on the first photoplethysmography signal and the noise signal.

[0031] In one embodiment, the denoising module is specifically configured to remove the noise signal from the first photoplethysmography signal to obtain the second photoplethysmography signal.

[0032] In one embodiment, the determination module is specifically configured to determine an AC component and a DC component corresponding to the second photoplethysmography signal; and determine a blood oxygen value based on the AC component and the DC component.

[0033] In a third aspect, the present application further provides a pulse oximeter device, which is a ring-type pulse oximeter, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements any of the methods described in the first aspect above.

[0034] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the methods described in the first aspect above.

[0035] In a fifth aspect, the present application also provides a computer program product, comprising a computer program, which implements any of the methods described in the first aspect when executed by a processor.

[0036] The above-mentioned blood oxygen value determination method, apparatus, device, storage medium, and program product obtain a first photoplethysmography signal and a motion signal of the subject, superimposing motion noise on the first photoplethysmography signal; denoising the first photoplethysmography signal according to a denoising model to determine a second photoplethysmography signal; and determining the blood oxygen value based on the second photoplethysmography signal. In the above-mentioned method, by denoising the obtained first photoplethysmography signal to remove the interference of motion noise on the photoplethysmography signal, and then determining the blood oxygen value, the influence of motion noise can be avoided, thereby effectively improving the accuracy of the blood oxygen value determination. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0038] Figure 1 FIG1 is a flow chart of a method for determining a blood oxygen value in one embodiment;

[0039] Figure 2 is a flow chart of a method for determining a blood oxygen value in another embodiment;

[0040] Figure 3 FIG1 is a flow chart of the step of determining a second photoplethysmography signal in one embodiment;

[0041] Figure 4 FIG1 is a flow chart of the step of determining a blood oxygen value based on a second photoplethysmography signal in one embodiment;

[0042] Figure 5 is a flow chart of a method for determining a blood oxygen value in another embodiment;

[0043] Figure 6 is a structural block diagram of a device for determining a blood oxygen value in one embodiment;

[0044] Figure 7 is a structural block diagram of a device for determining a blood oxygen value in another embodiment;

[0045] Figure 8 FIG. 1 is a diagram showing the internal structure of a pulse oximeter device in one embodiment. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0047] Blood oxygen value, also known as blood oxygen saturation, is one of the important basic data in clinical medicine. The blood oxygen value refers to the percentage of the combined O2 capacity in the total blood volume to the total available O2 capacity. The normal blood oxygen value of the human body should be between 94% and 98%. The blood oxygen value can be tested by a pulse oximeter.

[0048] Currently, existing pulse oximeters are usually of the finger-clip contact type. Due to the consideration of detection accuracy, blood oxygen saturation is most often measured on the finger.

[0049] However, existing pulse oximeters usually require users to measure blood oxygen levels in a resting state, and the accuracy of blood oxygen values ​​measured during sleep or exercise is low.

[0050] In view of this, the present application provides a method for determining a blood oxygen level that improves the accuracy of blood oxygen level calculation. The blood oxygen level determination method provided in the embodiments of the present application can be implemented by a blood oxygen level determination device. This blood oxygen level determination device can be implemented via software, hardware, or a combination of software and hardware. It can be embedded in or independent of a processor in a pulse oximeter device in hardware form, or it can be stored in a memory in the pulse oximeter device in software form. The following method embodiments are all described using the pulse oximeter device as the implementation subject.

[0051] In an exemplary embodiment, Figure 1 As shown, a method for determining a blood oxygen value is provided, comprising the following steps 101 to 103. In which:

[0052] Step 101: Acquire a first photoplethysmography signal and a motion signal of a measured object, wherein the first photoplethysmography signal is superimposed with motion noise.

[0053] The pulse oximeter includes a photoelectric sensor and an accelerometer. A subject wears the pulse oximeter to measure their blood oxygen level. The pulse oximeter can collect the subject's first photoplethysmography signal via the photoelectric sensor and the subject's motion signal via the accelerometer. Thus, the pulse oximeter can obtain both the subject's first photoplethysmography signal and the motion signal. It is understood that the subject is the user of the pulse oximeter.

[0054] Optionally, the photosensor and the acceleration sensor need to maintain the same sampling frequency when collecting the first photoplethysmography signal and the motion signal, that is, the first photoplethysmography signal and the motion signal are synchronized.

[0055] Optionally, the first photoplethysmograph signal (PPG) is a physiological signal obtained through optical technology, mainly composed of DC and AC components. The DC component reflects the static absorption and scattering characteristics of light by skin, tissue, etc.; the AC component is mainly related to the blood volume changes caused by the pulsation of arterial blood vessels, and is the key information for analyzing cardiovascular function.

[0056] Optionally, the PPG signal is easily interfered by various factors, such as motion artifacts, changes in ambient light, etc. Motion artifacts are when the object being measured is moving, which will cause large fluctuations in the PPG signal, affecting the quality and accuracy of the signal. Therefore, the PPG signal obtained by the pulse oximeter is superimposed with motion noise.

[0057] Optionally, the motion signal may include an acceleration signal. When the acceleration sensor includes a three-axis accelerometer and a three-axis gyroscope, a six-axis acceleration signal of the object under test may be obtained, ie, linear acceleration and angular acceleration in three-dimensional space.

[0058] Step 102: De-noise the first photoplethysmography signal according to the de-noising model to determine a second photoplethysmography signal.

[0059] Optionally, the denoising model may be a mathematical model or a neural network model, which is not limited in the embodiments of the present application.

[0060] In one possible implementation, when the first photoplethysmography signal is denoised according to a denoising model, the input of the denoising model can be the first photoplethysmography signal and motion information, and the output of the denoising model can be the second photoplethysmography signal. Therefore, the first photoplethysmography signal and motion information can be input into the denoising model, and the output of the denoising model can be used as the second photoplethysmography signal.

[0061] In another possible implementation, when denoising the first photoplethysmography signal according to the denoising model, the input of the denoising model can be the first photoplethysmography signal and motion information, and the output of the denoising model can be a noise signal. Therefore, the first photoplethysmography signal and motion information can be input into the denoising model, and the second photoplethysmography signal can be determined based on the output of the denoising model and the first photoplethysmography signal. The noise signal can be operating noise or other types of noise, and the embodiments of the present application are not limited to this.

[0062] It is understandable that the process of determining the denoising model may vary depending on the output of the denoising model.

[0063] Step 103: Determine the blood oxygen value according to the second photoplethysmography signal.

[0064] Optionally, the second photoplethysmography signal may be a PPG signal after various noise interferences are removed, and the blood oxygen value of the subject may be accurately determined through the second PPG signal.

[0065] Exemplarily, the blood oxygen value of the subject can be determined based on the second photoplethysmography signal and the empirical formula method, or the blood oxygen value corresponding to the second photoplethysmography signal can be determined according to a lookup table method, wherein the lookup table is used to characterize the mapping relationship between different PPG signals and corresponding blood oxygen values.

[0066] The above-mentioned method for determining the blood oxygen value obtains a first photoplethysmography signal and a motion signal of the subject, superimposing motion noise on the first photoplethysmography signal; denoising the first photoplethysmography signal according to a denoising model to determine a second photoplethysmography signal; and determining the blood oxygen value based on the second photoplethysmography signal. In this method, by denoising the obtained first photoplethysmography signal to remove the interference of motion noise on the photoplethysmography signal before determining the blood oxygen value, the influence of motion noise can be avoided, thereby effectively improving the accuracy of determining the blood oxygen value.

[0067] It is understood that before executing the above blood oxygen value determination method, a denoising model can also be determined based on the signal sample. In an exemplary embodiment, Figure 2 As shown, optionally, the blood oxygen value determination method further includes the following steps 201 to 203. Among them:

[0068] Step 201: Obtain a fixed signal sample transmitted by a simulator.

[0069] Optionally, the pulse oximeter can obtain a fixed signal sample emitted by the simulator, wherein the fixed signal sample can be a fixed PPG signal, a triangle wave, a sine wave or a square wave, etc. The fixed signal sample can be a signal emitted by the simulator without being interfered with by noise.

[0070] Optionally, a fixed signal sample may serve as a reference signal or a benchmark signal.

[0071] Optionally, the fixed signal sample emitted by the simulator may be a signal sample received by the pulse oximeter without being interfered by noise.

[0072] Step 202: When a fixed signal sample is applied to the pulse oximeter and the pulse oximeter is interfered by noise, obtain an actual signal sample received by the pulse oximeter and a motion signal sample of the pulse oximeter; the actual signal sample includes a noise signal.

[0073] Optionally, the noise interference to the pulse oximeter may be motion acceleration generated by the pulse oximeter due to external interference, and the noise interference may be motion noise interference, for example, the pulse oximeter is shaken, impacted, or vibrated; the noise interference may also be ambient light interference or electromagnetic interference, etc., which is not limited in the embodiments of the present application.

[0074] Optionally, when a fixed signal sample is applied to the pulse oximeter and the pulse oximeter is interfered with by noise, the pulse oximeter can obtain its own actual signal sample through the sensor and obtain its own motion signal sample through the acceleration sensor, wherein the motion signal sample includes a six-axis acceleration signal.

[0075] Step 203: Perform fitting processing on the fixed signal samples, the actual signal samples and the motion signal samples to obtain a denoising model.

[0076] In one possible implementation, a denoising model can be obtained by fitting actual signal samples and motion signal samples as fitting inputs and fixed signal samples as outputs. In this way, the input of the obtained denoising model is the acquired PPG signal and motion signal with superimposed noise signals, and the output is the PPG signal with the noise signal removed.

[0077] In another possible implementation, a denoising model can be obtained by fitting the actual signal samples and the motion signal samples as fitting inputs and the difference signal between the actual signal samples and the fixed signal samples as output. In this way, the input of the obtained denoising model is the acquired PPG signal and motion signal with the superimposed noise signal, and the output is the noise signal.

[0078] Optionally, the denoising model can be a linear fitting formula, and the fitting process can be implemented by the least squares method. The fixed signal samples, actual signal samples and motion signal samples satisfy the linear fitting formula y=ax1+bx2+c, wherein the actual signal samples and motion signal samples are the independent variables x1 and x2 of the linear fitting formula respectively. The y of the linear fitting formula can be determined based on the fixed signal samples, and the parameters a, b and c of the formula are determined by fitting processing, thereby determining the linear fitting formula, that is, determining the denoising model.

[0079] The above method obtains fixed signal samples emitted by the simulator; when the fixed signal samples are applied to the pulse oximeter and the pulse oximeter is interfered with by noise, obtains actual signal samples received by the pulse oximeter and motion signal samples of the pulse oximeter; the actual signal samples include noise signals; the fixed signal samples, the actual signal samples and the motion signal samples are fitted to obtain a denoising model; in the above method, the denoising model is accurately fitted by fitting the fixed signal samples, the signal samples received when the pulse oximeter is interfered with by noise, and the motion signal fitting data of the pulse oximeter, thereby performing denoising processing.

[0080] In an exemplary embodiment, Figure 3 As shown, optionally, performing denoising processing on the first photoplethysmography signal according to the denoising model to determine the second photoplethysmography signal includes the following steps 301 to 302. In which:

[0081] Step 301: Input the first photoplethysmography signal and the motion signal into a denoising model to obtain a noise signal output by the denoising model.

[0082] Optionally, in an embodiment of the present application, the input of the denoising model is the first photoplethysmography signal and the motion signal, and the output is a noise signal. Therefore, the first photoplethysmography signal and the motion signal can be input into the denoising model to obtain the noise signal.

[0083] Optionally, the first photoplethysmography signal and the motion signal may be pre-processed, such as outlier processing, before being input into the denoising model.

[0084] Step 302: Determine a second photoplethysmography signal according to the first photoplethysmography signal and the noise signal.

[0085] Optionally, the second photoplethysmography signal may be determined by removing a noise signal from the first photoplethysmography signal to obtain the second photoplethysmography signal.

[0086] In one possible implementation, the noise signal may be subtracted from the first photoplethysmography signal to obtain a second photoplethysmography signal.

[0087] In another possible implementation, the noise signal may be filtered out from the first photoplethysmography signal by filtering to obtain the second photoplethysmography signal.

[0088] In another possible implementation, the first photoplethysmography signal can be transformed using a variable domain method, such as converting the time domain signal into a frequency domain signal using a fast Fourier transform (FFT). A masking function is then designed in the frequency domain based on spectral analysis of the noise signal to zero or attenuate the frequency components corresponding to the noise signal. Finally, an inverse transform (such as an inverse fast Fourier transform (IFFT)) is used to convert the processed frequency domain signal back into the time domain, yielding a second photoplethysmography signal after removing the noise signal.

[0089] The above method inputs the first photoplethysmography signal and the motion signal into the denoising model to obtain a noise signal output by the denoising model, and determines the second photoplethysmography signal based on the first photoplethysmography signal and the noise signal; in this way, the noise signal in the first photoplethysmography signal can be determined by the denoising model obtained by fitting in advance, and the second photoplethysmography signal with the noise removed can be obtained, thereby avoiding noise interference when determining the blood oxygen value.

[0090] In an exemplary embodiment, Figure 4 As shown, optionally, determining the blood oxygen value according to the second photoplethysmography signal includes the following steps 401 to 402. In which:

[0091] Step 401: Determine the AC component and DC component corresponding to the second photoplethysmography signal.

[0092] Optionally, the AC component and the DC component are different components in the second photoplethysmography signal, the AC component is a light absorption component that varies with the pulse, and the DC component is a light absorption component that does not vary with the pulse.

[0093] Optionally, the DC component may be a periodic average value of the PPG signal, and the DC component may be determined by determining the periodic average value of the second photoplethysmography signal. After determining the DC component, the AC component may be determined based on the second photoplethysmography signal and the DC component.

[0094] For example, the AC component may be determined based on the difference between the second photoplethysmography signal and the DC component.

[0095] Step 402: Determine the blood oxygen value based on the AC component and the DC component.

[0096] Optionally, the second photoplethysmography signal may include a red light PPG signal and an infrared light PPG signal, the corresponding DC component may include a red light DC component and an infrared light DC component, and the AC component may include a red light AC component and an infrared light AC component.

[0097] Optionally, a ratio value R may be determined based on the ratio of the AC component to the DC component, and then the blood oxygen value may be calculated by means of a calibration curve. The calculation process of the ratio value R may be expressed by the following formula:

[0098] R=AC 红光 ÷DC 红光 ÷(AC 红外光 ÷DC 红外光 )

[0099] Among them, AC 红光 and AC 红外光 They are the AC components of red light and infrared light, DC 红光 and DC 红外光 are the DC components of red light and infrared light respectively. The ratio value R can also be calculated by other variations of the above formula or equivalent formulas.

[0100] As an optional implementation, Figure 5 As shown, the method for determining the blood oxygen value provided in the embodiment of the present application may include the following specific steps:

[0101] Step 501: Obtain a fixed signal sample transmitted by the simulator;

[0102] Step 502: When a fixed signal sample is applied to the pulse oximeter and the pulse oximeter is subject to noise interference, obtain an actual signal sample received by the pulse oximeter and a motion signal sample of the pulse oximeter; the actual signal sample includes a noise signal;

[0103] Step 503: Fitting the fixed signal samples, the actual signal samples and the motion signal samples to obtain a denoising model;

[0104] Step 504: Acquire a first photoplethysmography signal and a motion signal of the subject, wherein the first photoplethysmography signal is superimposed with motion noise;

[0105] Step 505: Input the first photoplethysmography signal and the motion signal into a denoising model to obtain a noise signal output by the denoising model;

[0106] Step 506: Remove the noise signal from the first photoplethysmography signal to obtain a second photoplethysmography signal;

[0107] Step 507: Determine the AC component and DC component corresponding to the second photoplethysmography signal;

[0108] Step 508: Determine the blood oxygen value based on the AC component and the DC component.

[0109] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0110] Based on the same inventive concept, embodiments of the present application also provide a blood oxygen level determination device for implementing the aforementioned blood oxygen level determination method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more blood oxygen level determination device embodiments provided below can be found in the aforementioned limitations of the blood oxygen level determination method and are not further elaborated here.

[0111] In an exemplary embodiment, Figure 6As shown, a blood oxygen value determination device 600 is provided, comprising: an acquisition module 601, a denoising module 602 and a determination module 603, wherein:

[0112] An acquisition module 601 is configured to acquire a first photoplethysmography signal and a motion signal of a subject, wherein the first photoplethysmography signal is superimposed with motion noise;

[0113] a denoising module 602 for performing denoising processing on the first photoplethysmography signal according to a denoising model to determine a second photoplethysmography signal;

[0114] The determination module 603 is configured to determine the blood oxygen value according to the second photoplethysmography signal.

[0115] In one embodiment, Figure 7 As shown, the blood oxygen value determination device 600 further includes a fitting module 604;

[0116] The acquisition module 601 is further used to obtain a fixed signal sample transmitted by the simulator;

[0117] The acquisition module 601 is further configured to acquire, when a fixed signal sample is applied to the pulse oximeter and the pulse oximeter is interfered with by noise, an actual signal sample received by the pulse oximeter and a motion signal sample of the pulse oximeter; the actual signal sample includes a noise signal;

[0118] The fitting module 604 is used to perform fitting processing on the fixed signal samples, the actual signal samples and the motion signal samples to obtain a denoising model.

[0119] In one embodiment, the denoising module 602 is specifically configured to input the first photoplethysmography signal and the motion signal into a denoising model to obtain a noise signal output by the denoising model; and determine a second photoplethysmography signal based on the first photoplethysmography signal and the noise signal.

[0120] In one embodiment, the denoising module 602 is specifically configured to remove the noise signal from the first photoplethysmography signal to obtain the second photoplethysmography signal.

[0121] In one embodiment, the determination module 603 is specifically configured to determine an AC component and a DC component corresponding to the second photoplethysmography signal; and determine the blood oxygen value according to the AC component and the DC component.

[0122] Each module in the device may be implemented in whole or in part through software, hardware, or a combination thereof. Each of the aforementioned modules may be embedded in or independent of the processor of the pulse oximeter device in hardware form, or may be stored in a memory of the pulse oximeter device in software form, so that the processor can call and execute the corresponding operations of each of the aforementioned modules.

[0123] In an exemplary embodiment, a pulse oximeter device is provided, the internal structure of which can be shown as follows: Figure 8 As shown. The pulse oximeter device includes a processor, a memory, an input / output interface (I / O) and a communication interface. The processor, memory and input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the pulse oximeter device is used to provide computing and control capabilities. The memory of the pulse oximeter device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the pulse oximeter device is used to store data. The input / output interface of the pulse oximeter device is used to exchange information between the processor and an external device. The communication interface of the pulse oximeter device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for determining a blood oxygen value is implemented.

[0124] Those skilled in the art will understand that Figure 8 The structure shown in the figure is merely a block diagram of a portion of the structure related to the present application solution, and does not constitute a limitation on the pulse oximeter device to which the present application solution is applied. The specific pulse oximeter device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0125] In an exemplary embodiment, a pulse oximeter device is provided. The pulse oximeter device is a finger ring pulse oximeter, including a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the following steps are implemented:

[0126] Acquiring a first photoplethysmography signal and a motion signal of the subject, wherein the first photoplethysmography signal is superimposed with motion noise;

[0127] Denoising the first photoplethysmography signal according to a denoising model to determine a second photoplethysmography signal;

[0128] The blood oxygen value is determined based on the second photoplethysmography signal.

[0129] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0130] Obtain fixed signal samples emitted by the simulator;

[0131] When a fixed signal sample is applied to the pulse oximeter and the pulse oximeter is interfered with by noise, obtaining an actual signal sample received by the pulse oximeter and a motion signal sample of the pulse oximeter; the actual signal sample includes a noise signal;

[0132] The fixed signal samples, actual signal samples and motion signal samples are fitted to obtain a denoising model.

[0133] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0134] Inputting the first photoplethysmography signal and the motion signal into a denoising model to obtain a noise signal output by the denoising model;

[0135] A second photoplethysmography signal is determined based on the first photoplethysmography signal and the noise signal.

[0136] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0137] A second photoplethysmography signal is obtained by removing a noise signal from the first photoplethysmography signal.

[0138] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0139] determining an AC component and a DC component corresponding to a second photoplethysmography signal;

[0140] The blood oxygen value is determined based on the AC component and the DC component.

[0141] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0142] Acquiring a first photoplethysmography signal and a motion signal of the subject, wherein the first photoplethysmography signal is superimposed with motion noise;

[0143] Denoising the first photoplethysmography signal according to a denoising model to determine a second photoplethysmography signal;

[0144] The blood oxygen value is determined based on the second photoplethysmography signal.

[0145] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0146] Obtain fixed signal samples emitted by the simulator;

[0147] When a fixed signal sample is applied to the pulse oximeter and the pulse oximeter is interfered with by noise, obtaining an actual signal sample received by the pulse oximeter and a motion signal sample of the pulse oximeter; the actual signal sample includes a noise signal;

[0148] The fixed signal samples, actual signal samples and motion signal samples are fitted to obtain a denoising model.

[0149] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0150] Inputting the first photoplethysmography signal and the motion signal into a denoising model to obtain a noise signal output by the denoising model;

[0151] A second photoplethysmography signal is determined based on the first photoplethysmography signal and the noise signal.

[0152] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0153] A second photoplethysmography signal is obtained by removing a noise signal from the first photoplethysmography signal.

[0154] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0155] determining an AC component and a DC component corresponding to a second photoplethysmography signal;

[0156] The blood oxygen value is determined based on the AC component and the DC component.

[0157] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0158] Acquiring a first photoplethysmography signal and a motion signal of the subject, wherein the first photoplethysmography signal is superimposed with motion noise;

[0159] Denoising the first photoplethysmography signal according to a denoising model to determine a second photoplethysmography signal;

[0160] The blood oxygen value is determined based on the second photoplethysmography signal.

[0161] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0162] Obtain fixed signal samples emitted by the simulator;

[0163] When a fixed signal sample is applied to the pulse oximeter and the pulse oximeter is interfered with by noise, obtaining an actual signal sample received by the pulse oximeter and a motion signal sample of the pulse oximeter; the actual signal sample includes a noise signal;

[0164] The fixed signal samples, actual signal samples and motion signal samples are fitted to obtain a denoising model.

[0165] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0166] Inputting the first photoplethysmography signal and the motion signal into a denoising model to obtain a noise signal output by the denoising model;

[0167] A second photoplethysmography signal is determined based on the first photoplethysmography signal and the noise signal.

[0168] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0169] A second photoplethysmography signal is obtained by removing a noise signal from the first photoplethysmography signal.

[0170] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0171] determining an AC component and a DC component corresponding to a second photoplethysmography signal;

[0172] The blood oxygen value is determined based on the AC component and the DC component.

[0173] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0174] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0175] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for determining a blood oxygen value, characterized in that: For use in a pulse oximeter, the method comprises: Acquiring a first photoplethysmography signal and a motion signal of a measured object, wherein the first photoplethysmography signal is superimposed with motion noise; performing denoising processing on the first photoplethysmography signal according to a denoising model to determine a second photoplethysmography signal; The blood oxygen value is determined according to the second photoplethysmography signal.

2. The method according to claim 1, characterized in that The method further comprises: Obtain fixed signal samples emitted by the simulator; When the fixed signal sample is applied to the pulse oximeter and the pulse oximeter is interfered by noise, obtaining an actual signal sample received by the pulse oximeter and a motion signal sample of the pulse oximeter; the actual signal sample includes a noise signal; The fixed signal samples, the actual signal samples and the motion signal samples are fitted to obtain the denoising model.

3. The method according to claim 2, characterized in that The denoising process is performed on the first photoplethysmography signal according to the denoising model to determine the second photoplethysmography signal, including: Inputting the first photoplethysmography signal and the motion signal into the denoising model to obtain a noise signal output by the denoising model; A second photoplethysmography signal is determined based on the first photoplethysmography signal and the noise signal.

4. The method according to claim 3, characterized in that The determining of a second photoplethysmography signal according to the first photoplethysmography signal and the noise signal comprises: The noise signal is removed from the first photoplethysmography signal to obtain the second photoplethysmography signal.

5. The method according to claim 1, wherein Determining the blood oxygen value according to the second photoplethysmography signal includes: determining an AC component and a DC component corresponding to the second photoplethysmography signal; A blood oxygen value is determined according to the AC component and the DC component.

6. A device for determining a blood oxygen value, characterized in that: Set in a pulse oximeter, the device includes: an acquisition module, configured to acquire a first photoplethysmography signal and a motion signal of a subject, wherein the first photoplethysmography signal is superimposed with motion noise; a denoising module, configured to perform denoising processing on the first photoplethysmography signal according to a denoising model to determine a second photoplethysmography signal; A determination module is used to determine the blood oxygen value according to the second photoplethysmography signal.

7. The device according to claim 6, characterized in that The device also includes a fitting module; The acquisition module is further used to acquire fixed signal samples emitted by the simulator; The acquisition module is further configured to acquire, when the fixed signal sample is applied to the pulse oximeter and the pulse oximeter is interfered with by noise, an actual signal sample received by the pulse oximeter and a motion signal sample of the pulse oximeter; the actual signal sample includes a noise signal; The fitting module is used to perform fitting processing on the fixed signal samples, the actual signal samples and the motion signal samples to obtain the denoising model.

8. A pulse oximeter device, the pulse oximeter device being a ring-type pulse oximeter, the pulse oximeter device comprising a memory and a processor, the memory storing a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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