Vital signs monitoring method, device, wearable device and storage medium

Abstract

The present invention discloses a method, device, wearable device and storage medium for monitoring vital signs, wherein the method comprises: collecting physiological signals and motion signals of a human body; obtaining characteristic frequencies of motion signals; determining filtering parameters of a band-stop filter according to the characteristic frequencies; filtering physiological signals through a band-stop filter, and obtaining vital sign index information of a human body according to the physiological signals after filtering. Thus, the influence of motion artifacts on vital sign monitoring can be eliminated, the estimation accuracy of vital sign indexes can be effectively improved, and the validity of the estimation results can be ensured.

Description

Technical Field

[0001] The present invention relates to the field of medical technology, and in particular to a vital sign monitoring method, a vital sign monitoring device, a wearable device and a computer-readable storage medium. Background Art

[0002] By recording the electrical activities of the heart, brain, muscles and other parts of the human body, the corresponding vital signs can be monitored. For example, cardiopulmonary indicators such as heart rate (HR), respiration rate (RR) and blood oxygen saturation (SpO2) can be estimated based on the photoplethysmograph (PPG) signal. In the related art, the robustness of the estimation is highly dependent on the signal quality, which is seriously affected by motion artifacts, resulting in low estimation accuracy of vital signs, which in turn affects the effectiveness of the estimation. Summary of the invention

[0003] The present invention aims to solve at least one of the technical problems in the related art to a certain extent. To this end, the first object of the present invention is to propose a vital sign monitoring method that can eliminate the influence of motion artifacts on vital sign monitoring, effectively improve the estimation accuracy of vital sign indicators, and ensure the validity of the estimation results.

[0004] The second objective of the present invention is to provide a vital signs monitoring device.

[0005] The third objective of the present invention is to provide a wearable device.

[0006] A fourth object of the present invention is to provide a computer-readable storage medium.

[0007] To achieve the above-mentioned purpose, the first aspect of the present invention proposes a vital sign monitoring method, which includes: collecting physiological signals and motion signals of the human body; obtaining the characteristic frequency of the motion signal; determining the filtering parameters of the band-stop filter according to the characteristic frequency; filtering the physiological signal through the band-stop filter, and obtaining the vital sign indicator information of the human body based on the physiological signal after filtering.

[0008] According to the vital sign monitoring method of the embodiment of the present invention, by collecting physiological signals and motion signals of the human body, obtaining the characteristic frequency of the motion signal, determining the filter parameters of the band-stop filter according to the characteristic frequency, filtering the physiological signal through the band-stop filter, and obtaining the vital sign index information of the human body according to the physiological signal after filtering. Thus, the influence of motion artifacts on vital sign monitoring can be eliminated, the estimation accuracy of vital sign indexes can be effectively improved, and the validity of the estimation results can be ensured.

[0009] According to one embodiment of the present invention, obtaining the characteristic frequency of a motion signal includes: obtaining the amplitude-frequency characteristic of the motion signal, and obtaining a characteristic frequency lower limit threshold of the amplitude-frequency characteristic; obtaining a characteristic frequency set based on the characteristic frequency lower limit threshold and the amplitude-frequency characteristic; obtaining a maximum characteristic frequency and a minimum characteristic frequency of the characteristic frequency set; and obtaining the characteristic frequency of the motion signal according to the maximum characteristic frequency and the minimum characteristic frequency.

[0010] According to one embodiment of the present invention, the filtering parameters of the band-stop filter are determined according to the characteristic frequency, including: determining the center suppression frequency of the band-stop filter according to the characteristic frequency; determining the band-stop width of the band-stop filter according to the characteristic frequency and the passband gain, wherein the passband gain is the ratio of the modulus of the gain at the characteristic frequency to the modulus of the passband gain.

[0011] According to one embodiment of the present invention, the band stop filter is a FIR band stop filter, and the transfer function of the FIR band stop filter is:

[0012]

[0013] Wherein, H(z) is the transfer function, z is the Z-transform operator, b0, b1, b2, ..., b M is the filter coefficient, 0, 1, 2, ..., M is the filter order number, and the zero point of the transfer function H(z) is located at and Wherein ω0 is the central suppression frequency.

[0014] According to an embodiment of the present invention, the characteristic frequency includes at least one, the band-stop filter includes at least one, and the filtering parameters of the at least one band-stop filter correspond one-to-one to the at least one characteristic frequency.

[0015] According to an embodiment of the present invention, the physiological signal is a photoplethysmogram signal, an electrocardiogram signal, an electroencephalogram signal or an electromyogram signal.

[0016] According to one embodiment of the present invention, when the physiological signal is a photoplethysmogram signal, vital sign indicator information of a human body is obtained based on the filtered photoplethysmogram signal, including: obtaining the maximum and minimum values ​​of the filtered photoplethysmogram signal; determining the pulse frequency based on the frequency of occurrence of the maximum value; and determining the blood oxygen saturation based on the ratio of the maximum value to the minimum value.

[0017] To achieve the above-mentioned purpose, the second embodiment of the present invention proposes a vital sign monitoring device, which includes: an acquisition module, used to collect physiological signals and motion signals of the human body; a frequency acquisition module, used to obtain the characteristic frequency of the motion signal; a parameter determination module, used to determine the filtering parameters of the band-stop filter according to the characteristic frequency; an indicator information acquisition module, used to filter the physiological signal through the band-stop filter, and obtain the vital sign indicator information of the human body based on the physiological signal after filtering.

[0018] According to the vital sign monitoring device of the embodiment of the present invention, the acquisition module acquires the physiological signal and motion signal of the human body, and the frequency acquisition module acquires the characteristic frequency of the motion signal, and the parameter determination module determines the filter parameter of the band stop filter according to the characteristic frequency, and the index information acquisition module performs filtering processing on the physiological signal through the band stop filter, and obtains the vital sign index information of the human body according to the physiological signal after filtering. Thus, the influence of motion artifacts on vital sign monitoring can be eliminated, the estimation accuracy of vital sign indexes can be effectively improved, and the validity of the estimation results can be ensured.

[0019] To achieve the above objectives, a third aspect of the present invention proposes a wearable device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the above-mentioned vital signs detection method is implemented.

[0020] According to the wearable device of the embodiment of the present invention, by collecting physiological signals and motion signals of the human body, obtaining the characteristic frequency of the motion signal, determining the filtering parameters of the band-stop filter according to the characteristic frequency, filtering the physiological signal through the band-stop filter, and obtaining the vital sign index information of the human body according to the physiological signal after filtering. Thus, the influence of motion artifacts on vital sign monitoring can be eliminated, the estimation accuracy of vital sign indexes can be effectively improved, and the validity of the estimation results can be ensured.

[0021] To achieve the above objectives, a fourth aspect of the present invention provides a computer-readable storage medium on which a vital signs monitoring program is stored, and when the program is executed by a processor, the above vital signs detection method is implemented.

[0022] According to the computer-readable storage medium of the embodiment of the present invention, by collecting physiological signals and motion signals of a human body, obtaining the characteristic frequency of the motion signal, determining the filter parameters of the band-stop filter according to the characteristic frequency, filtering the physiological signal through the band-stop filter, and obtaining the vital sign index information of the human body according to the physiological signal after filtering, the influence of motion artifacts on vital sign monitoring can be eliminated, the estimation accuracy of the vital sign index can be effectively improved, and the validity of the estimation result can be ensured.

[0023] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a flow chart of a vital sign monitoring method according to an embodiment of the present invention;

[0025] Figure 2 A flowchart of obtaining a characteristic frequency of a motion signal according to an embodiment of the present invention;

[0026] Figure 3 A flowchart of determining filtering parameters of a band-stop filter according to a characteristic frequency according to an embodiment of the present invention;

[0027] Figure 4 is a structural block diagram of a vital sign monitoring device according to an embodiment of the present invention;

[0028] Figure 5 FIG. 4 is a structural block diagram of a wearable device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0030] It should be noted that by recording the electrical activities of the heart, brain, muscles and other parts of the human body, the corresponding vital signs can be monitored. Among them, cardiopulmonary indicators are one of the important vital signs of the human body. Cardiopulmonary indicators such as HR and SpO2 are considered to be important references for diagnosing cardiovascular diseases, and can usually be monitored using ECG (Electro Cardio Gram) signals. However, collecting ECG signals requires placing multiple electrodes at different locations on the body, which results in this monitoring method not only being interfered by motion signals during exercise, affecting detection accuracy, but also seriously affecting the wearer's comfort, making it impossible to apply to portable wearable devices. In addition, SpO2, as a sign of hypoxia and apnea, cannot be obtained from ECG signals.

[0031] In contrast, PPG is considered a competitive technical solution for measuring related indicators due to its portability and low cost. In the PPG-based sensing process, a single light source or dual light sources of a specific wavelength are used to illuminate the skin, and the light is reflected or transmitted on the skin and received by the photoelectric sensor. Then, key information such as HR, RR and SpO2 can be extracted based on the periodically changing PPG signal. However, when using a PPG-based monitoring method, motion artifacts will adversely interfere with the quality of the PPG signal, thereby reducing the accuracy and effectiveness of the PPG signal in monitoring cardiopulmonary indicators.

[0032] Based on this, an embodiment of the present invention proposes a vital sign monitoring method, which can eliminate the influence of motion artifacts on vital sign monitoring, effectively improve the estimation accuracy of vital sign indicators, and ensure the validity of the estimation results.

[0033] The following describes a vital sign monitoring method, a vital sign monitoring apparatus, a wearable device, and a computer-readable storage medium provided by embodiments of the present invention with reference to the accompanying drawings.

[0034] Figure 1 is a flow chart of a vital sign monitoring method according to an embodiment of the present invention, referring to Figure 1 As shown, the vital signs monitoring method may include the following steps:

[0035] In step S101, physiological signals and motion signals of a human body are collected.

[0036] Specifically, the physiological signals and motion signals of the human body can be synchronously collected through the same acquisition window and at the same acquisition frequency. Among them, the physiological signal can be a photoelectric volume pulse signal, an electrocardiogram signal, an electroencephalogram signal or an electromyogram signal, and correspondingly, it can be obtained by monitoring PPG, ECG, EEG (Electro Encephalo Gram) or EMG (Electro Myo Graphy); the motion signal can be an acceleration signal, which can be obtained by an accelerometer sensor.

[0037] In step S102, the characteristic frequency of the motion signal is obtained.

[0038] That is, after collecting the motion signal of the human body, the characteristic frequency of the motion signal is obtained so as to design a band-stop filter according to the characteristic frequency of the motion signal.

[0039] Further, refer to Figure 2 As shown, obtaining the characteristic frequency of the motion signal may specifically include the following steps:

[0040] In step S1021, the amplitude-frequency characteristic of the motion signal is obtained, and the characteristic frequency lower limit threshold of the amplitude-frequency characteristic is obtained.

[0041] In step S1022, a characteristic frequency set is acquired based on the characteristic frequency lower limit threshold and the amplitude-frequency characteristic.

[0042] In step S1023, the maximum characteristic frequency and the minimum characteristic frequency of the characteristic frequency set are obtained.

[0043] In step S1024, the characteristic frequency of the motion signal is acquired according to the maximum characteristic frequency and the minimum characteristic frequency.

[0044] Specifically, the motion signal data in the acquisition window can be decomposed by FFT (Fast Fourier Transformation), and the amplitude-frequency characteristics of the motion signal can be obtained according to the FFT decomposition result. Then, the Stein unbiased estimation method can be used for the obtained array to determine the lower limit threshold of the characteristic frequency, and the maximum value in the amplitude-frequency characteristic that is higher than the lower limit threshold is determined as the characteristic frequency set of the motion signal, and then the maximum characteristic frequency and the minimum characteristic frequency of the characteristic frequency set are obtained, and the characteristic frequency of the motion signal can be obtained in the following way:

[0045]

[0046] Among them, f1 is the characteristic frequency of the motion signal, f 1,max is the maximum characteristic frequency, f 1,min is the minimum characteristic frequency.

[0047] In step S103, filtering parameters of the band-stop filter are determined according to the characteristic frequency.

[0048] Among them, the filtering parameters of the band stop filter may include the central suppression frequency and the band stop width of the band stop filter. It can be understood that the characteristic frequency may include at least one, and the band stop filter may include at least one correspondingly, and the filtering parameters of at least one band stop filter correspond to at least one characteristic frequency. That is, when there are different characteristic frequencies in the motion signal, multiple band stop filters can be deployed accordingly to filter for multiple characteristic frequencies.

[0049] Further, refer to Figure 3 As shown, determining the filtering parameters of the band-stop filter according to the characteristic frequency may include the following steps:

[0050] In step S1031 , the center suppression frequency of the band-stop filter is determined according to the characteristic frequency.

[0051] In step S1032, the stopband width of the stop filter is determined according to the characteristic frequency and the passband gain, wherein the passband gain is the ratio of the modulus of the gain at the characteristic frequency to the modulus of the passband gain.

[0052] Specifically, when determining the filtering parameters of the band-stop filter according to the characteristic frequency, the characteristic frequency can be used as the central suppression frequency of the band-stop filter. Furthermore, since the band-stop filter will be applied to the physiological signal captured in the same time window, and the physiological signal baseline contains a variety of information, such as the PPG signal also contains information about RR, it is necessary to ensure that the effective information of the physiological signal before and after filtering remains unchanged, so the band-stop width of the band-stop filter should be relatively narrow, and its size can be equal to the ratio of the characteristic frequency to the passband gain.

[0053] In a specific example, the stopband can be designed to be The band-stop filter can be a finite impulse response digital filter, and specifically a Butterworth filter can be used, whose maximum order is 20, the response amplitude of the stop band is -80dB, and the response amplitude of the pass band is 0dB.

[0054] In one embodiment, the band-stop filter is a FIR (Finite Impulse Response) band-stop filter, and the transfer function of the FIR band-stop filter is:

[0055]

[0056] Wherein, H(z) is the transfer function, z is the Z-transform operator, b0, b1, b2, ..., b M is the filter coefficient, 0, 1, 2, ..., M is the filter order number, and the zero point of the transfer function H(z) is located at and Wherein ω0 is the central suppression frequency.

[0057] Specifically, the band-stop filter is constructed through FIR, which can achieve stable and linear phase shift, which can be controlled by:

[0058] y[n]=b0x[n]+b1x[n-1]+b2x[n-2]+...+b M x[nM]

[0059] Among them, y[n] is the output signal, x[n], x[n-1], x[n-2], ..., x[nM] are the input signals, b0, b1, b2, ..., b M is the filter coefficient, M is the filter order, and n is the amount of data. In order to perform frequency suppression at the center suppression frequency, the above control equation can be Z-transformed to obtain the transfer function H(z) of the FIR band-stop filter. The zero point of the transfer function H(z) is located at and Wherein ω0 is the central suppression frequency, t is the sampling period, and by adjusting the filter order number M to a suitable size, the pole-zero mode and frequency response of the stopband filter can be optimized, thereby not only improving the sharpness but also enhancing the attenuation of the filter.

[0060] In step S104, the physiological signal is filtered by a band-stop filter, and the vital sign index information of the human body is obtained according to the filtered physiological signal.

[0061] That is to say, the physiological signal in the window is filtered by the above-mentioned band-stop filter to obtain a valid signal, and then the vital sign index information of the human body is obtained according to the valid signal. Since the lower limit frequency and the upper limit frequency of the band-stop filter stop band are determined according to the frequency of the motion signal, the performance of the band-stop filter in the embodiment of the present invention does not depend on the quality of a certain reference signal, so it can effectively reduce the influence of motion artifacts on the monitoring results.

[0062] In a specific example, when the physiological signal is a photoplethysmogram signal, the vital sign indicator information of the human body is obtained based on the filtered photoplethysmogram signal, including: obtaining the maximum and minimum values ​​of the filtered photoplethysmogram signal; determining the pulse frequency based on the frequency of occurrence of the maximum value; and determining the blood oxygen saturation based on the ratio of the maximum value to the minimum value.

[0063] That is to say, when the physiological signal is a PPG signal, the cardiopulmonary index information of the human body can be obtained based on the filtered PPG signal as a valid signal, and the cardiopulmonary index information may include HR, RR and SpO2. Specifically, the maximum and minimum values ​​of the filtered PPG signal can be determined, and the frequency of occurrence of the maximum value can be determined as HR, and the ratio of the maximum value to the minimum value can be determined as SpO2.

[0064] In summary, the vital sign monitoring method according to the embodiment of the present invention collects physiological signals and motion signals of the human body, obtains the characteristic frequency of the motion signal, determines the filtering parameters of the band-stop filter according to the characteristic frequency, filters the physiological signal through the band-stop filter, and obtains the vital sign index information of the human body according to the physiological signal after filtering. Thus, the influence of motion artifacts on vital sign monitoring can be eliminated, the estimation accuracy of vital sign indexes can be effectively improved, and the validity of the estimation results can be ensured.

[0065] Figure 4 is a structural block diagram of a vital sign monitoring device according to an embodiment of the present invention, referring to Figure 4 As shown, the vital sign monitoring device 200 includes: a collection module 201 , a frequency acquisition module 202 , a parameter determination module 203 and an indicator information acquisition module 204 .

[0066] Among them, the acquisition module 201 is used to collect physiological signals and motion signals of the human body; the frequency acquisition module 202 is used to obtain the characteristic frequency of the motion signal; the parameter determination module 203 is used to determine the filtering parameters of the band-stop filter according to the characteristic frequency; the indicator information acquisition module 204 is used to filter the physiological signal through the band-stop filter, and obtain the vital sign indicator information of the human body according to the physiological signal after filtering.

[0067] In one embodiment, the frequency acquisition module 202 is specifically used to: obtain the amplitude-frequency characteristics of the motion signal, and obtain the characteristic frequency lower limit threshold of the amplitude-frequency characteristics; obtain a characteristic frequency set based on the characteristic frequency lower limit threshold and the amplitude-frequency characteristics; obtain the maximum characteristic frequency and the minimum characteristic frequency of the characteristic frequency set; and obtain the characteristic frequency of the motion signal based on the maximum characteristic frequency and the minimum characteristic frequency.

[0068] In one embodiment, the parameter determination module 203 is specifically used to: determine the center suppression frequency of the band-stop filter according to the characteristic frequency; determine the band-stop width of the band-stop filter according to the characteristic frequency and the passband gain, wherein the passband gain is the ratio of the modulus of the gain at the characteristic frequency to the modulus of the passband gain.

[0069] Furthermore, the band stop filter is a FIR band stop filter, and its transfer function is:

[0070]

[0071] Wherein, H(z) is the transfer function, z is the Z-transform operator, b0, b1, b2, ..., b M is the filter coefficient, 0, 1, 2, ..., M is the filter order number, and the zero point of the transfer function H(z) is located at and Wherein ω0 is the central suppression frequency.

[0072] In one embodiment, the characteristic frequency includes at least one, the band-stop filter includes at least one, and the filtering parameters of the at least one band-stop filter correspond one-to-one to the at least one characteristic frequency.

[0073] In one embodiment, the physiological signal is a photoplethysmography signal, an electrocardiogram signal, an electroencephalogram signal, or an electromyography signal.

[0074] In one embodiment, when the physiological signal is a photoelectric volumetric pulse signal, the indicator information acquisition module 204 is specifically used to: obtain the maximum and minimum values ​​of the photoelectric volumetric pulse signal after filtering; determine the pulse frequency according to the frequency of occurrence of the maximum value; and determine the blood oxygen saturation according to the ratio of the maximum value to the minimum value.

[0075] It should be noted that, for the description of the vital signs monitoring device in this application, please refer to the description of the vital signs monitoring method in this application, and the details will not be repeated here.

[0076] According to the vital sign monitoring device of the embodiment of the present invention, the acquisition module acquires the physiological signal and motion signal of the human body, and the frequency acquisition module acquires the characteristic frequency of the motion signal, and the parameter determination module determines the filter parameter of the band stop filter according to the characteristic frequency, and the index information acquisition module performs filtering processing on the physiological signal through the band stop filter, and obtains the vital sign index information of the human body according to the physiological signal after filtering. Thus, the influence of motion artifacts on vital sign monitoring can be eliminated, the estimation accuracy of vital sign indexes can be effectively improved, and the validity of the estimation results can be ensured.

[0077] Figure 5 is a structural block diagram of a wearable device according to an embodiment of the present invention, referring to Figure 5 As shown, the wearable device 300 includes: a memory 301, a processor 302, and a computer program stored in the memory 301 and executable on the processor 302. When the processor 302 executes the program, the above-mentioned vital sign detection method is implemented.

[0078] According to the wearable device of the embodiment of the present invention, by collecting physiological signals and motion signals of the human body, obtaining the characteristic frequency of the motion signal, determining the filtering parameters of the band-stop filter according to the characteristic frequency, filtering the physiological signal through the band-stop filter, and obtaining the vital sign index information of the human body according to the physiological signal after filtering. Thus, the influence of motion artifacts on vital sign monitoring can be eliminated, the estimation accuracy of vital sign indexes can be effectively improved, and the validity of the estimation results can be ensured.

[0079] In one embodiment, a computer-readable storage medium is provided, on which a vital sign monitoring program is stored. When the program is executed by a processor, the above-mentioned vital sign detection method is implemented.

[0080] According to the computer-readable storage medium of the embodiment of the present invention, by collecting physiological signals and motion signals of a human body, obtaining the characteristic frequency of the motion signal, determining the filter parameters of the band-stop filter according to the characteristic frequency, filtering the physiological signal through the band-stop filter, and obtaining the vital sign index information of the human body according to the physiological signal after filtering, the influence of motion artifacts on vital sign monitoring can be eliminated, the estimation accuracy of the vital sign index can be effectively improved, and the validity of the estimation result can be ensured.

[0081] It should be understood that although Figure 1-3 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1-3 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0082] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0083] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0084] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0085] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0086] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0087] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for monitoring vital signs, characterized in that: The method comprises: Collect physiological signals and motion signals of the human body; Acquiring a characteristic frequency of the motion signal; Determine the filtering parameters of the band-stop filter according to the characteristic frequency; Filtering the physiological signal through the band-stop filter, and obtaining the vital sign index information of the human body according to the filtered physiological signal; Acquiring the characteristic frequency of the motion signal includes: Acquire the amplitude-frequency characteristic of the motion signal, and acquire the characteristic frequency lower limit threshold of the amplitude-frequency characteristic; Acquire a characteristic frequency set based on the characteristic frequency lower limit threshold and the amplitude-frequency characteristic; Obtaining the maximum characteristic frequency and the minimum characteristic frequency of the characteristic frequency set; Acquire the characteristic frequency of the motion signal according to the maximum characteristic frequency and the minimum characteristic frequency; Determining filtering parameters of the band-stop filter according to the characteristic frequency includes: Determine the center suppression frequency of the band-stop filter according to the characteristic frequency; Determining the band stop width of the band stop filter according to the characteristic frequency and the passband gain, wherein the passband gain is the ratio of the modulus of the gain at the characteristic frequency to the modulus of the passband gain; The band stop filter is a FIR band stop filter, and the transfer function of the FIR band stop filter is: Wherein, H(z) is the transfer function, z is the Z-transform operator, b0, b1, b2, ..., b M is the filter coefficient, 0, 1, 2, ..., M is the filter order number, and the zero point of the transfer function H(z) is located at and Wherein ω0 is the central suppression frequency.

2. The method according to claim 1, characterized in that The characteristic frequency includes at least one, the band-stop filter includes at least one, and the filtering parameters of at least one band-stop filter correspond to the at least one characteristic frequency in a one-to-one manner.

3. The method according to claim 1, characterized in that The physiological signal is a photoelectric volumetric pulse signal, an electrocardiogram signal, an electroencephalogram signal or an electromyography signal.

4. The method according to claim 3, characterized in that When the physiological signal is the photoplethysmogram signal, obtaining the vital sign index information of the human body according to the filtered photoplethysmogram signal includes: Obtaining the maximum and minimum values ​​of the photoplethysmogram signal after filtering; Determine the pulse frequency according to the frequency of occurrence of the maximum value; The blood oxygen saturation is determined according to the ratio of the maximum value to the minimum value.

5. A vital signs monitoring device, characterized in that: The device is used to perform the method according to any one of claims 1 to 4, and the device comprises: An acquisition module, used to acquire physiological signals and motion signals of the human body; A frequency acquisition module, used to acquire the characteristic frequency of the motion signal; A parameter determination module, used to determine the filtering parameters of the band-stop filter according to the characteristic frequency; The index information acquisition module is used to filter the physiological signal through the band-stop filter, and obtain the vital sign index information of the human body according to the physiological signal after filtering.

6. A wearable device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the vital sign monitoring method according to any one of claims 1 to 4 is implemented.

7. A computer-readable storage medium, characterized in that: A vital sign monitoring program is stored thereon, and when the program is executed by a processor, the vital sign monitoring method as described in any one of claims 1-4 is implemented.

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