A respiratory rate calculation method, device and medium based on wearable device

Abstract

The present application relates to a respiratory rate calculation method, apparatus and medium based on a wearable device, wherein the method comprises: obtaining an ECG signal and an ACC signal through an electrocardiogram patch on the wearable device; performing baseline filtering on the ECG signal using a high-pass filter, and calculating a first respiratory signal based on the processed ECG signal; selecting an ACC signal whose signal-to-noise ratio meets a preset condition, performing noise filtering using a band-pass filter, and calculating a second respiratory signal based on the processed ACC signal; screening a time domain calculation method and a frequency domain calculation method for calculating the respiratory rate based on the first respiratory signal and the second respiratory signal, and calculating the respiratory rate using the screened calculation method. Through the present application, the problem of how to accurately, continuously and in real time measure the patient's respiratory rate is solved, and the joint calculation of the respiratory rate based on the ECG signal and the ACC signal is realized.

Description

Technical Field

[0001] The present application relates to the field of respiratory detection technology, and in particular to a respiratory rate calculation method, device and medium based on a wearable device. Background Art

[0002] Respiratory rate (RR), the number of breaths a person takes per minute, is a key vital sign that helps understand a person's overall health and sleep quality. Respiratory rate and breathing pattern are also considered good indicators of a person's underlying health.

[0003] Recent studies have found that respiratory movement can cause periodic changes in the QRS complex and significant changes in heart rate, with the intervals between the RRs decreasing during inspiration and increasing during expiration. Existing solutions typically use smart wearable devices (ECG patches) to obtain respiratory rate, enabling continuous monitoring of respiration without affecting patient activity. However, calculating respiratory rate based solely on ECG signals presents the following issues: Respiratory signal extraction can be inaccurate for patients with abnormal heart rates and symptoms; and measurement is inaccurate in high-frequency breathing, such as when the RR is greater than 25 beats per minute (BrPM).

[0004] Currently, there is no effective solution to the problem of how to accurately, continuously and in real time measure the patient's respiratory rate in related technologies. Summary of the Invention

[0005] The embodiments of the present application provide a respiratory rate calculation method, apparatus, and medium based on a wearable device to at least solve the problem in the related art of how to accurately, continuously, and in real time measure a patient's respiratory rate.

[0006] In a first aspect, an embodiment of the present application provides a method for calculating respiratory rate based on a wearable device, the method comprising:

[0007] Obtain ECG and ACC signals through the ECG patch on the wearable device;

[0008] Performing baseline filtering on the ECG signal through a high-pass filter, and calculating a first respiratory signal based on the processed ECG signal;

[0009] selecting an ACC signal whose signal-to-noise ratio meets a preset condition, filtering out noise through a bandpass filter, and calculating a second respiratory signal based on the processed ACC signal;

[0010] According to the first respiratory signal and the second respiratory signal, a time domain calculation method and a frequency domain calculation method for calculating the respiratory rate are screened, and the respiratory rate is calculated using the screened calculation method.

[0011] In some embodiments, the time domain calculation method and the frequency domain calculation method include:

[0012] Calculate a first respiratory rate corresponding to the first respiratory signal and a second respiratory rate corresponding to the second respiratory signal based on a time domain calculation method;

[0013] The first respiratory signal and the second respiratory signal are processed based on a frequency domain calculation method to obtain a spectrum signal, and a third respiratory rate corresponding to the spectrum signal is calculated.

[0014] In some embodiments, calculating the first respiratory signal based on the processed ECG signal includes:

[0015] calculating a difference between the amplitudes of the R wave and the S wave in the processed ECG signal, and obtaining an RS respiration signal based on the difference;

[0016] calculating an RR interval between R waves in the processed ECG signal, and obtaining an RR respiratory signal based on the RR interval;

[0017] Set a peak threshold and a trough threshold of the respiratory signal, a peak whose peak value is less than the peak threshold is an invalid peak, and a trough whose trough value is greater than the peak threshold is an invalid trough;

[0018] The proportions of effective peaks and troughs in the RS respiration signal and the RR respiration signal are counted respectively, and the respiration signal with the larger proportion is the first respiration signal.

[0019] In some embodiments, based on the first respiratory signal and the second respiratory signal, a time domain calculation method and a frequency domain calculation method for calculating the respiratory rate are screened, and calculating the respiratory rate using the screened calculation methods includes:

[0020] Counting the proportions of effective respiratory cycles in the first respiratory signal and the second respiratory signal respectively, and selecting a calculation method for calculating the respiratory rate based on the proportions;

[0021] If only the proportion of valid respiratory cycles in the first respiratory signal is greater than a first threshold, calculating the respiratory rate of the first respiratory signal based on a time domain calculation method;

[0022] If only the proportion of valid respiratory cycles in the second respiratory signal is greater than a second threshold, calculating the respiratory rate of the second respiratory signal based on a time domain calculation method;

[0023] If the proportion of the first respiratory signal is greater than a first threshold, and the proportion of the second respiratory signal is greater than a second threshold, the respiratory rates of the first respiratory signal and the second respiratory signal are calculated based on a frequency domain calculation method.

[0024] In some embodiments, respectively calculating the first respiratory rate corresponding to the first respiratory signal and the second respiratory rate corresponding to the second respiratory signal based on a time domain calculation method includes:

[0025] Acquire a plurality of time intervals between adjacent peaks in the first respiratory signal, average the plurality of time intervals to obtain a respiratory cycle corresponding to the first respiratory signal, and calculate a corresponding first respiratory rate based on the respiratory cycle;

[0026] A plurality of time intervals between adjacent peaks in the second respiratory signal are obtained, the plurality of time intervals are averaged to obtain a respiratory cycle corresponding to the second respiratory signal, and a corresponding second respiratory rate is calculated based on the respiratory cycle.

[0027] In some embodiments, processing the first respiratory signal and the second respiratory signal based on a frequency domain calculation method to obtain a spectrum signal, and calculating the third respiratory rate corresponding to the spectrum signal includes:

[0028] Performing Fourier transform on the first respiratory signal and the second respiratory signal respectively to obtain a first spectrum signal and a second spectrum signal;

[0029] Calculating weights of the first respiratory signal and the second respiratory signal respectively, and performing weighted averaging on the first spectrum signal and the second spectrum signal based on the weights to obtain a spectrum signal;

[0030] A corresponding third respiratory rate is calculated based on the spectrum signal.

[0031] In some embodiments, calculating the corresponding first respiratory rate according to the respiratory cycle includes:

[0032] The first respiratory rate is calculated using the formula BrPM=60 / PPI, where BrPM is the first respiratory rate and PPI is the respiratory period.

[0033] In some embodiments, calculating the corresponding third respiratory rate based on the spectrum signal includes:

[0034] The third respiratory rate is calculated by the formula RR=frequency(fft=max(fft))*60, where fft is the spectrum signal, frequency() represents the frequency value corresponding to the spectrum signal, max() represents the maximum value, and RR is the third respiratory rate.

[0035] In a second aspect, an embodiment of the present application provides a respiratory rate calculation device based on a wearable device, the device being configured to execute the method described in the first aspect above, the device comprising a wearable device and a terminal device, wherein the wearable device further comprises an electrocardiogram patch module and a wireless communication module;

[0036] The wearable device is used to obtain ECG signals and ACC signals through the electrocardiogram patch module and transmit the signal data to the terminal device through the wireless communication module;

[0037] The terminal device is used to filter out the baseline of the received ECG signal through a high-pass filter, and calculate a first respiratory signal based on the processed ECG signal; select an ACC signal whose signal-to-noise ratio meets a preset condition from the received ACC signal, filter out the noise through a band-pass filter, and calculate a second respiratory signal based on the processed ACC signal; finally, based on the first respiratory signal and the second respiratory signal, screen the time domain calculation method and the frequency domain calculation method for calculating the respiratory rate, and calculate the respiratory rate using the screened calculation method.

[0038] In a third aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect above.

[0039] Compared with the related art, the embodiments of the present application provide a respiratory rate calculation method, device and medium based on a wearable device, wherein the method obtains ECG signals and ACC signals through an electrocardiogram patch on the wearable device; a high-pass filter is used to filter out the baseline of the ECG signal, and a first respiratory signal is calculated based on the processed ECG signal; an ACC signal whose signal-to-noise ratio meets a preset condition is selected, a band-pass filter is used to filter out the noise, and a second respiratory signal is calculated based on the processed ACC signal; according to the first respiratory signal and the second respiratory signal, the time domain calculation method and the frequency domain calculation method for calculating the respiratory rate are screened, and the respiratory rate is calculated by the screened calculation method, which solves the problem of how to measure the patient's respiratory rate accurately, continuously and in real time, and realizes the joint calculation of the respiratory rate based on the ECG signal and the ACC signal. When the ECG signal cannot accurately extract the respiratory signal, the ACC signal is used as an auxiliary to make the calculation of the respiratory rate more accurate and efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0041] Figure 1 is a flowchart of the steps of a method for calculating respiratory rate based on a wearable device according to an embodiment of the present application;

[0042] Figure 2 is a structural block diagram of a respiratory rate calculation device based on a wearable device according to an embodiment of the present application;

[0043] Figure 3 Schematic diagram of the internal structure of an electronic device according to an embodiment of the present application.

[0044] Description of the accompanying drawings: 21. Wearable device; 22. Terminal device; 23. ECG patch module; 24. Wireless communication module. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solutions and advantages of this application more clearly understood, the present application is described and illustrated below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely used to explain this application and are not intended to limit this application. Based on the embodiments provided in this application, all other embodiments obtained by those of ordinary skill in the art without making any creative efforts are within the scope of protection of this application.

[0046] Obviously, the drawings described below are merely examples or embodiments of the present application. Those skilled in the art can, without inventive effort, apply the present application to other similar scenarios based on these drawings. Furthermore, it is also understood that, although the effort involved in such a development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this application, changes in design, manufacturing, or production based on the technical content disclosed in this application are merely conventional technical means and should not be construed as an insufficiency of the content disclosed in this application.

[0047] References to "embodiments" in this application mean that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it refer to independent or alternative embodiments that are mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described in this application may be combined with other embodiments unless there is a conflict.

[0048] Unless otherwise defined, the technical or scientific terms used in this application should have the ordinary meaning understood by a person of ordinary skill in the technical field to which this application belongs. The words "one", "a", "the" and the like used in this application do not indicate a limit on quantity and may indicate the singular or plural. The terms "include", "comprise", "have" and any variations thereof used in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units that are inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like used in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The word "multiple" used in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships can exist. For example, "A and / or B" can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects before and after are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific order for the objects.

[0049] The present invention provides a method for calculating respiratory rate based on a wearable device. Figure 1 is a flowchart of the steps of the respiratory rate calculation method based on the wearable device according to an embodiment of the present application. Figure 1 As shown, the method includes the following steps:

[0050] Step S102, obtaining ECG signals and ACC signals through the electrocardiogram patch on the wearable device;

[0051] It should be noted that ECG is specifically the electrocardiogram of the heart, which is a graph of the voltage versus time of the heart's electrical activity using electrodes placed on the skin. These electrodes detect tiny electrical changes caused by the depolarization and subsequent repolarization of the myocardium during each cardiac cycle (heartbeat). Alterations from the normal ECG pattern occur in many cardiac abnormalities, including arrhythmias (such as atrial fibrillation and ventricular tachycardia), inadequate coronary blood flow (such as myocardial ischemia and myocardial infarction), and electrolyte imbalances (such as hypokalemia and hyperkalemia). ACC (accelerometer) is a tool for measuring appropriate acceleration. Positive acceleration is the acceleration (rate of change of velocity) of an object in its own instantaneous stationary coordinate system, which is different from coordinate acceleration, which is the acceleration in a fixed coordinate system.

[0052] Step S104, performing baseline filtering on the ECG signal using a high-pass filter, and calculating a first respiratory signal based on the processed ECG signal;

[0053] Specifically, the difference between the amplitudes of the R wave and the S wave in the processed ECG signal is calculated, and the RS respiration signal is obtained based on the difference; the RR interval between the R waves in the processed ECG signal is calculated, and the RR respiration signal is obtained based on the RR interval;

[0054] Set the peak threshold and trough threshold of the respiratory signal. A peak with a peak value less than the peak threshold is considered an invalid peak, and a trough with a trough value greater than the peak threshold is considered an invalid trough. Count the proportions of valid peaks and troughs in the RS respiratory signal and the RR respiratory signal respectively. The respiratory signal with the larger proportion is the first respiratory signal.

[0055] Step S106, selecting an ACC signal whose signal-to-noise ratio meets a preset condition, filtering out noise through a bandpass filter, and calculating a second respiratory signal based on the processed ACC signal;

[0056] Specifically, an ACC signal whose signal-to-noise ratio meets preset conditions is selected, and a bandpass filter is used to filter out noise from the signals on the three coordinate axes in the ACC signal respectively. The three-axis signals are then fused through the PCA algorithm, and a second respiratory signal is calculated based on the processed and fused ACC signal. It should be noted that because the position of the ECG patch and the user's body posture cannot be determined, it is impossible to accurately determine which axis of the X, Y, and Z axes can be used to calculate the respiratory signal in advance and more accurately. Therefore, fusing the three can make the method of calculating the respiratory signal based on the ACC signal more flexible and avoid interference from factors such as the position of the ECG patch and the user's body posture.

[0057] Step S108 , screening a time domain calculation method and a frequency domain calculation method for calculating the respiratory rate according to the first respiratory signal and the second respiratory signal, and calculating the respiratory rate using the screened calculation method.

[0058] Specifically, the proportion of effective breathing cycles in the first breathing signal and the second breathing signal (PE = effective breathing cycle / (effective breathing cycle + invalid breathing cycle)) is counted respectively, and the calculation method of the respiratory rate is filtered based on the proportion; if only the proportion of effective breathing cycles in the first breathing signal is greater than the first threshold, the respiratory rate of the first breathing signal is calculated based on the time domain calculation method; if only the proportion of effective breathing cycles in the second breathing signal is greater than the second threshold, the respiratory rate of the second breathing signal is calculated based on the time domain calculation method; if the proportion of the first breathing signal is greater than the first threshold, and the proportion of the second breathing signal is greater than the second threshold, the respiratory rates of the first and second breathing signals are calculated based on the frequency domain calculation method.

[0059] It should be noted that the first threshold and the second threshold are different in size, and both are obtained through model learning based on a large amount of experimental data.

[0060] Preferably, respectively calculating the first respiratory rate corresponding to the first respiratory signal and the second respiratory rate corresponding to the second respiratory signal based on a time domain calculation method includes:

[0061] Obtaining a plurality of time intervals between adjacent peaks in the first respiratory signal, averaging the plurality of time intervals to obtain a respiratory period corresponding to the first respiratory signal, and calculating a corresponding first respiratory rate based on the respiratory period; further calculating the first respiratory rate using the formula BrPM=60 / PPI, where BrPM is the first respiratory rate and PPI is the respiratory period corresponding to the first respiratory signal;

[0062] Obtain several time intervals between adjacent peaks in the second respiratory signal, average the several time intervals to obtain the respiratory cycle corresponding to the second respiratory signal, and calculate the corresponding second respiratory rate based on the respiratory cycle; further, calculate the second respiratory rate using the formula BrPM=60 / PPI, where BrPM is the second respiratory rate and PPI is the respiratory cycle corresponding to the second respiratory signal.

[0063] Preferably, the first respiratory signal and the second respiratory signal are processed based on a frequency domain calculation method to obtain a spectrum signal, the frequency range of normal breathing is set to 0.1 Hz to 0.7 Hz, and calculating the third respiratory rate corresponding to the spectrum signal includes:

[0064] Performing Fourier transform on the first respiratory signal and the second respiratory signal respectively to obtain a first spectrum signal and a second spectrum signal;

[0065] Calculating weights of the first respiratory signal and the second respiratory signal respectively, and performing weighted averaging on the first spectrum signal and the second spectrum signal based on the weights to obtain a spectrum signal;

[0066] The corresponding third respiratory rate is calculated based on the spectrum signal; further, the third respiratory rate is calculated by the formula RR=frequency(fft=max(fft))*60, where fft is the spectrum signal, frequency() represents the frequency value corresponding to the spectrum signal, max() represents the maximum value, and RR is the third respiratory rate.

[0067] Through steps S102 to S108 in the embodiment of the present application, the problem of how to accurately, continuously and in real time measure the patient's respiratory rate is solved, and the joint calculation of the respiratory rate based on the ECG signal and the ACC signal is realized. When the ECG signal cannot accurately extract the respiratory signal, the ACC signal serves as an auxiliary to make the calculation of the respiratory rate more accurate and efficient.

[0068] It should be noted that the steps shown in the above process or the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0069] The present invention provides a respiratory rate calculation device based on a wearable device. Figure 2 is a structural block diagram of a respiratory rate calculation device based on a wearable device according to an embodiment of the present application. Figure 2 As shown, the device is configured to execute the method in the above embodiment, and the device includes a wearable device 21 and a terminal device 22, wherein the wearable device further includes an electrocardiogram patch module 23 and a wireless communication module 24:

[0070] The wearable device 21 is used to obtain ECG signals and ACC signals through the electrocardiogram patch module 23 and transmit the signal data to the terminal device through the wireless communication module 24;

[0071] The terminal device 21 is used to filter out the baseline of the received ECG signal through a high-pass filter, and calculate a first respiratory signal based on the processed ECG signal; select an ACC signal whose signal-to-noise ratio meets a preset condition from the received ACC signal, filter out the noise through a band-pass filter, and calculate a second respiratory signal based on the processed ACC signal; finally, based on the first respiratory signal and the second respiratory signal, screen the time domain calculation method and the frequency domain calculation method for calculating the respiratory rate, and calculate the respiratory rate using the screened calculation method.

[0072] Through the wearable device 21 and terminal device 22 in the embodiment of the present application, the problem of how to accurately, continuously and in real time measure the patient's respiratory rate is solved, and the joint calculation of the respiratory rate based on the ECG signal and the ACC signal is realized. When the ECG signal cannot accurately extract the respiratory signal, the ACC signal serves as an auxiliary to make the calculation of the respiratory rate more accurate and efficient.

[0073] It should be noted that the above modules can be functional modules or program modules, and can be implemented through software or hardware. For modules implemented through hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0074] This embodiment further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0075] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0076] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be repeated here.

[0077] In addition, in conjunction with the respiratory rate calculation method based on a wearable device in the above embodiments, embodiments of the present application may provide a storage medium for implementation. The storage medium stores a computer program; when the computer program is executed by a processor, it implements any of the respiratory rate calculation methods based on a wearable device in the above embodiments.

[0078] In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a respiratory rate calculation method based on a wearable device is implemented. The display screen of the computer device may be a liquid crystal display or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a button, trackball, or touchpad provided on the computer device housing, or an external keyboard, touchpad, or mouse.

[0079] In one embodiment, Figure 3 is a schematic diagram of the internal structure of an electronic device according to an embodiment of the present application, such as Figure 3 As shown, an electronic device is provided, which may be a server, and its internal structure diagram may be as shown in FIG. Figure 3 As shown. The electronic device includes a processor, a network interface, an internal memory, and a non-volatile memory connected via an internal bus, wherein the non-volatile memory stores an operating system, a computer program, and a database. The processor is used to provide computing and control capabilities, the network interface is used to communicate with an external terminal via a network connection, the internal memory is used to provide an environment for the operation of the operating system and the computer program. When the computer program is executed by the processor, it implements a respiratory rate calculation method based on a wearable device, and the database is used to store data.

[0080] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the electronic device to which the solution of the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0081] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, which 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. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0082] Those skilled in the art should understand that the various technical features of the above-described embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the various technical features in the above-described 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 specification.

[0083] 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 invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A respiratory rate calculation method based on a wearable device, characterized in that: The method comprises: Obtaining ECG signals and ACC signals through an electrocardiogram patch on a wearable device, wherein the ACC signal is an accelerometer signal; Performing baseline filtering on the ECG signal through a high-pass filter, and calculating a first respiratory signal based on the processed ECG signal; selecting an ACC signal whose signal-to-noise ratio meets a preset condition, filtering out noise through a bandpass filter, and calculating a second respiratory signal based on the processed ACC signal; Counting the proportions of effective respiratory cycles in the first respiratory signal and the second respiratory signal respectively, and selecting a calculation method for calculating the respiratory rate based on the proportions; If only the proportion of valid respiratory cycles in the first respiratory signal is greater than a first threshold, calculating the respiratory rate of the first respiratory signal based on a time domain calculation method; If only the proportion of valid respiratory cycles in the second respiratory signal is greater than a second threshold, calculating the respiratory rate of the second respiratory signal based on a time domain calculation method; If the proportion of the first respiratory signal is greater than a first threshold, and the proportion of the second respiratory signal is greater than a second threshold, the respiratory rates of the first respiratory signal and the second respiratory signal are calculated based on a frequency domain calculation method.

2. The method according to claim 1, characterized in that The time domain calculation method and the frequency domain calculation method include: Calculate a first respiratory rate corresponding to the first respiratory signal and a second respiratory rate corresponding to the second respiratory signal based on a time domain calculation method; The first respiratory signal and the second respiratory signal are processed based on a frequency domain calculation method to obtain a spectrum signal, and a third respiratory rate corresponding to the spectrum signal is calculated.

3. The method according to claim 1, characterized in that Calculating the first respiratory signal based on the processed ECG signal includes: calculating a difference between the amplitudes of the R wave and the S wave in the processed ECG signal, and obtaining an RS respiration signal based on the difference; calculating an RR interval between R waves in the processed ECG signal, and obtaining an RR respiratory signal based on the RR interval; Set a peak threshold and a trough threshold of the respiratory signal, a peak whose peak value is less than the peak threshold is an invalid peak, and a trough whose trough value is greater than the trough threshold is an invalid trough; The proportions of effective peaks and troughs in the RS respiration signal and the RR respiration signal are counted respectively, and the respiration signal with the larger proportion is the first respiration signal.

4. The method according to claim 2, characterized in that Calculating a first respiratory rate corresponding to the first respiratory signal and a second respiratory rate corresponding to the second respiratory signal based on a time domain calculation method includes: Acquire a plurality of time intervals between adjacent peaks in the first respiratory signal, average the plurality of time intervals to obtain a respiratory cycle corresponding to the first respiratory signal, and calculate a corresponding first respiratory rate based on the respiratory cycle; A plurality of time intervals between adjacent peaks in the second respiratory signal are obtained, the plurality of time intervals are averaged to obtain a respiratory cycle corresponding to the second respiratory signal, and a corresponding second respiratory rate is calculated based on the respiratory cycle.

5. The method according to claim 2, characterized in that Processing the first respiratory signal and the second respiratory signal based on a frequency domain calculation method to obtain a spectrum signal, and calculating a third respiratory rate corresponding to the spectrum signal includes: Performing Fourier transform on the first respiratory signal and the second respiratory signal respectively to obtain a first spectrum signal and a second spectrum signal; Calculating weights of the first respiratory signal and the second respiratory signal respectively, and performing weighted averaging on the first spectrum signal and the second spectrum signal based on the weights to obtain a spectrum signal; A corresponding third respiratory rate is calculated based on the spectrum signal.

6. The method according to claim 4, characterized in that Calculating the corresponding first respiratory rate according to the respiratory cycle includes: The first respiratory rate is calculated using the formula BrPM=60 / PPI, where BrPM is the first respiratory rate and PPI is the respiratory period.

7. The method according to claim 5, characterized in that Calculating the corresponding third respiratory rate based on the spectrum signal includes: The third respiratory rate is calculated by the formula RR=frequency(fft=max(fft))*60, where fft is the spectrum signal, frequency() represents the frequency value corresponding to the spectrum signal, max() represents the maximum value, and RR is the third respiratory rate.

8. A respiratory rate calculation device based on a wearable device, characterized in that: The device is configured to perform the method according to any one of claims 1 to 7, the device comprising a wearable device and a terminal device, wherein the wearable device further comprises an electrocardiogram patch module and a wireless communication module; The wearable device is used to obtain ECG signals and ACC signals through the electrocardiogram patch module and transmit the signal data to the terminal device through the wireless communication module; The terminal device is used to filter out the baseline of the received ECG signal through a high-pass filter, and calculate a first respiratory signal based on the processed ECG signal; select an ACC signal whose signal-to-noise ratio meets a preset condition from the received ACC signal, filter out the noise through a band-pass filter, and calculate a second respiratory signal based on the processed ACC signal; finally, based on the first respiratory signal and the second respiratory signal, screen the time domain calculation method and the frequency domain calculation method for calculating the respiratory rate, and calculate the respiratory rate using the screened calculation method.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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