Frequency determination method and apparatus, and storage medium, computer device and program product

Abstract

Disclosed in the present invention are a frequency determination method and apparatus, and a storage medium, a computer device and a program product. The method comprises: acquiring an original signal, and filtering the original signal to obtain a filtered signal, wherein the filtered signal contains a signal component related to a vital sign; performing a fast Fourier transformation on the filtered signal to obtain a transformation result signal; performing a maximum likelihood vital sign peak value search within the transformation result signal to obtain a first maximum likelihood peak value and a frequency-domain frequency corresponding to the first maximum likelihood peak value; filtering the original signal to obtain a time-domain vital sign waveform; performing time-domain waveform peak detection on the time-domain vital sign waveform, and obtaining a time-domain frequency on the basis of a segment duration, a signal sampling rate and the number of peaks; and on the basis of the frequency-domain frequency and the time-domain frequency, determining a target frequency of the vital sign in the original signal. The present invention solves the technical problem of the accuracy of the result of identifying a vital sign frequency on the basis of an optical power signal being low.

Description

Frequency determination method and device, storage medium, computer device, and program product

[0001] The present application claims priority to the Chinese patent application No. 202410417032.5, filed on April 8, 2024, and entitled "Frequency determination method and device, storage medium, computer device, and program product", the content of which is incorporated herein by reference in its entirety. TECHNICAL FIELD

[0002] The present application relates to the technical field of signal processing, in particular to a frequency determination method and device, a storage medium, a computer device, and a program product. BACKGROUND

[0003] Vital sign monitoring is an operation of monitoring physiological characteristics of a human body, such as physiological indexes such as heart rate, respiratory rate, body temperature, and blood pressure. At present, vital sign monitoring technologies are mainly divided into skin contact type and non-skin contact type vital sign sensing technologies. Compared with the contact type technology, the non-contact type vital sign monitoring technology is not high in accuracy, and the anti-interference ability is also weaker than the contact type technology. The skin contact type instrument generally needs to be worn or worn on the user's body and may cause the user to feel uncomfortable in the case of long-term monitoring (such as sleep monitoring of a polysomnograph). In addition, some technologies need to use specific occasions and equipment and under the operation of professional personnel, to complete the monitoring. Compared with the contact type technology, the non-skin contact type vital sign sensing technology does not need to be directly in contact with the body, does not need professional personnel or place restrictions, increases the practicability, reduces the user's discomfort, improves the comfort, provides a more convenient and feasible monitoring mode, and is suitable for the needs of ordinary users and the mass market.

[0004] Optical fiber sensors have high sensitivity, anti-electromagnetic interference, small size, safety, and multi-functionality, and are widely used in industries, medical treatment, communication, and other fields. Vital sign monitoring technology based on optical fiber sensors is a relatively new non-skin contact type vital sign monitoring technology. Its small size and easy-to-place characteristics also make it suitable for most people's use scenarios and actual needs. However, how to identify the vital sign frequency with periodic characteristics from the optical power signal of the optical fiber sensor is a difficulty in the prior art, and the signal processing method used in the related technology has low accuracy in identifying the vital sign frequency.

[0005] At present, no effective solution has been proposed for the above problems. SUMMARY

[0006] Embodiments of the present application provide a frequency determination method, device, storage medium, computer device, and program product to at least solve the technical problem of low accuracy of the identification result of identifying the vital sign frequency based on the optical power signal.

[0007] According to an aspect of the embodiments of the present application, a frequency determination method is provided, comprising: obtaining an original signal and filtering the original signal to obtain a filtered signal, wherein the filtered signal contains a signal component of a vital sign, and the original signal is an optical power signal; performing fast Fourier transform on the filtered signal to obtain a transformed result signal; searching for a maximum possible vital sign peak value corresponding to the vital sign in the transformed result signal to obtain a first maximum possible peak value corresponding to the vital sign and a frequency domain frequency corresponding to the first maximum possible peak value; filtering the original signal to obtain a time domain vital sign waveform; searching for a time domain frequency by performing time domain waveform peak value search on the time domain vital sign waveform according to a human body limit frequency corresponding to the vital sign; and determining a target frequency of the vital sign in the original signal according to the frequency domain frequency and the time domain frequency.

[0008] Optionally, when the vital sign is respiration, the target frequency is respiration rate; or, when the vital sign is heartbeat, the target frequency is heart rate.

[0009] Optionally, when the vital sign is heartbeat and the target frequency is heart rate, filtering the original signal to obtain the time domain vital sign waveform comprises: performing modal decomposition on the original signal to obtain a plurality of sub-component signals; performing fast Fourier transform (FFT) on the plurality of sub-component signals respectively to obtain a plurality of sub-component transformed result signals respectively corresponding to the plurality of sub-component signals; analyzing the plurality of sub-component transformed result signals to select a target sub-component transformed result signal from the plurality of sub-component transformed result signals; determining a frequency possible range of the vital sign according to a frequency spectrum of the target sub-component transformed result signal; and filtering the original signal according to the frequency possible range to obtain the time domain vital sign waveform.

[0010] Optionally, determining the frequency possible range of the vital sign according to the target sub-component transformed result signal comprises: performing maximum possible vital sign peak value search on the target sub-component transformed result signal to obtain a third maximum possible peak value and a fourth maximum possible peak value in the target sub-component transformed result signal, wherein the third maximum possible peak value is a minimum value of heartbeat possible peak values in the target sub-component transformed result signal, and the fourth maximum possible peak value is a maximum value of the heartbeat possible peak values in the target sub-component transformed result signal; and determining the frequency possible range according to the third maximum possible peak value and the fourth maximum possible peak value.

[0011] Optionally, the target frequency of the vital sign in the original signal is determined according to the frequency domain frequency and the time domain frequency, comprising: determining a first reliability degree corresponding to the frequency domain frequency according to the frequency domain frequency and a sum of multiple frequencies corresponding to the first maximum possible peak value; determining a second reliability degree corresponding to the time domain frequency according to the time domain frequency, a signal sampling rate, a comparison result of a number of theoretical time domain waveform peaks calculated according to a time domain segment length and a number of actually found time domain waveform peaks; and determining the target frequency according to the frequency domain frequency, the time domain frequency, the first reliability degree and the second reliability degree.

[0012] Optionally, the target frequency is determined according to the frequency domain frequency, the time domain frequency, the first reliability degree and the second reliability degree, comprising: performing weighted summation on the frequency domain frequency and the time domain frequency according to the first reliability degree and the second reliability degree to obtain the target frequency.

[0013] According to another aspect of the embodiment of the present application, a frequency determination device is further provided, comprising: a first filtering module configured to obtain an original signal and filter the original signal to obtain a filtered signal, wherein the filtered signal contains a signal component of a vital sign, and the original signal is an optical power signal; a transformation module configured to perform fast Fourier transform on the filtered signal to obtain a transformed result signal; a first peak searching module configured to search for a maximum possible vital sign peak value in the transformed result signal to obtain a first maximum possible peak value corresponding to the vital sign and a frequency domain frequency corresponding to the first maximum possible peak value; a second filtering module configured to filter the original signal to obtain a time domain vital sign waveform; a second peak searching module configured to search for a time domain waveform peak value of the time domain vital sign waveform according to the frequency domain frequency and a limit frequency of the human vital sign to obtain a time domain frequency; and a determination module configured to determine a target frequency of the vital sign in the original signal according to the frequency domain frequency and the time domain frequency.

[0014] According to still another aspect of the embodiment of the present application, a non-volatile storage medium is further provided, comprising a stored program, wherein the program, when running, controls a device in which the non-volatile storage medium is located to perform any one of the frequency determination methods.

[0015] According to still another aspect of the embodiment of the present application, a computer device is further provided, comprising a memory and a processor, the memory is configured to store a program, and the processor is configured to run the program stored in the memory, wherein the program, when running, performs any one of the frequency determination methods.

[0016] According to still another aspect of the embodiment of the present application, a computer program is further provided, which, when executed by a processor, implements the steps of any one of the frequency determination methods.

[0017] In the embodiment of the present application, the original signal is acquired and filtered to obtain a filtered signal, wherein the filtered signal contains a signal component of vital signs, and the original signal is an optical power signal; the filtered signal is subjected to fast Fourier transform to obtain a transformed result signal; a maximum possible vital sign peak value search is performed in the transformed result signal to obtain a first maximum possible peak value corresponding to vital signs and a frequency domain frequency corresponding to the first maximum possible peak value; the original signal is filtered according to human body characteristic features or modal decomposition results to obtain a time domain vital sign waveform; the time domain vital sign waveform is subjected to a peak search according to a signal sampling rate, a time domain waveform segment length and a human body limit frequency corresponding to vital signs to obtain a time domain frequency and a second reliability degree; and a target frequency of vital signs in the original signal is determined according to the frequency domain frequency and the time domain frequency, so that the frequency of the vital sign signal is accurately identified from the optical power signal, thereby achieving the technical effect of improving the monitoring accuracy of the optical fiber sensor applied to the vital sign frequency identification process, and further solving the technical problem of low accuracy of the identification result of identifying the vital sign frequency based on the optical power signal. BRIEF DESCRIPTION OF DRAWINGS

[0018] The accompanying drawings, which are included to provide a further understanding of the present application and are incorporated in and constitute a part of this application, illustrate embodiments of the present application and together with the description serve to explain the present application. In the drawings:

[0019] Fig. 1 shows a hardware structure block diagram of a computer terminal for implementing a frequency determination method;

[0020] Fig. 2 is a flowchart of a frequency determination method according to an embodiment of the present application;

[0021] Fig. 3 is a schematic diagram of an original signal according to an optional embodiment of the present application;

[0022] Fig. 4 is a schematic diagram of a filtered signal according to an optional embodiment of the present application;

[0023] Fig. 5 is a schematic diagram of a fast Fourier transform result signal according to an optional embodiment of the present application;

[0024] Fig. 6 is a schematic diagram of a truncated signal corresponding to the transformed result signal according to an optional embodiment of the present application;

[0025] Fig. 7 is a schematic diagram of a time domain respiration waveform according to an optional embodiment of the present application;

[0026] Fig. 8 is a schematic diagram of a modal decomposition sub-component transformed result signal according to an optional embodiment of the present application;

[0027] Fig. 9 is a schematic diagram of a time domain heartbeat waveform according to an optional embodiment of the present application;

[0028] Fig. 10 is a structural block diagram of a frequency determination apparatus according to an embodiment of the present application. DETAILED DESCRIPTION

[0029] In order to make the persons skilled in the art better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely in combination with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by the persons skilled in the art without creative labor should belong to the protection scope of the present application.

[0030] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be exchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0031] According to the embodiments of the present application, an embodiment of a frequency determination method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that herein.

[0032] The method embodiments provided by the embodiments of the present application can be executed in a mobile terminal, a computer terminal or similar computing device. FIG. 1 shows a hardware structure block diagram of a computer terminal for implementing the frequency determination method. As shown in FIG. 1, the computer terminal 10 can include one or more processors (processors can include, but are not limited to, processing devices such as microprocessors MCU or programmable logic devices FPGA, etc.), a memory 104 configured to store data. In addition, it can also include a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which can be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. Those skilled in the art can understand that the structure shown in FIG. 1 is only schematic, which does not limit the structure of the above-mentioned electronic device. For example, the computer terminal 10 can include more or fewer components than those shown in FIG. 1, or have a different configuration from that shown in FIG. 1.

[0033] It should be noted that the one or more processors and / or other data processing circuits described above can be referred to as "data processing circuits" herein. The data processing circuit can be embodied in whole or in part as software, hardware, firmware or any other combination. In addition, the data processing circuit can be a single independent processing module, or all or part of any one of the other elements combined into the computer terminal 10. As referred to in the embodiments of the present application, the data processing circuit controls the processor (for example, the selection of the variable resistance terminal path connected to the interface).

[0034] The memory 104 can be configured to store software programs and modules of application software, such as program instructions / data storage devices corresponding to the frequency determination method of the embodiments of the present application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, implements the frequency determination method of the application program described above. The memory 104 can include a high-speed random access memory, and can also include a non-volatile memory such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 can further include a memory remotely disposed with respect to the processor, which can be connected to the computer terminal 10 through a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network and a combination thereof.

[0035] The display can be, for example, a touch screen type liquid crystal display (LCD), which can enable a user to interact with the user interface of the computer terminal 10.

[0036] The vital sign monitoring technology based on the optical fiber sensor does not need to be in direct contact with the body, reduces the discomfort of the user, improves the comfort, and provides a more convenient and easy-to-use monitoring method. However, the optical power signal generated by the optical fiber sensor is relatively sensitive, and how to extract the accurate user vital sign frequency of the user from the optical power signal is a problem in the prior art. The present application combines the method steps of time domain signal processing and frequency domain signal processing, and can effectively calculate the vital sign frequency for different human body optical fiber signal inputs.

[0037] Fig. 2 is a flowchart of a frequency determination method according to an embodiment of the present application. As shown in Fig. 2, the method comprises the following steps:

[0038] In step S201, an original signal is obtained and filtered to obtain a filtered signal, wherein the filtered signal contains a vital sign signal component, and the original signal is an optical power signal. The original signal is a signal directly obtained by the monitoring behavior of the optical fiber sensor. Since the monitored object has vital sign activities, the original signal contains the vital sign signal component of the monitored object. The optical fiber sensor can be arranged on a bed used by the user, and the optical fiber sensor is configured to monitor the vital sign frequency of the user when the user is in bed.

[0039] As an optional embodiment, the vital sign of the user can be respiration or heartbeat, and the target frequency is the real frequency of the vital sign of the user. In the case of respiration as the vital sign, the target frequency is the respiration rate of the user; or in the case of heartbeat as the vital sign, the target frequency is the heart rate of the user.

[0040] Optionally, the filtering action in this step can filter out the frequency band in which the vital sign signal in the original signal is impossible to exist. According to the type of vital sign, the filtering action can have slight differences. For example, in the case of respiration as the vital sign to be monitored, a 0.8Hz low-pass filtering method can be used to filter the original signal to obtain the filtered signal. In the case of heartbeat as the vital sign to be monitored, a band-pass filtering method based on the possible cutoff frequency band of the heartbeat BPM can be used to filter the original signal to obtain the filtered signal.

[0041] In step S202, the filtered signal is subjected to fast Fourier transform to obtain a transformed result signal.

[0042] Fast Fourier Transform (FFT) is an efficient algorithm for computing the Discrete Fourier Transform (DFT) and its inverse. FFT is an optimization of the Fourier Transform, which greatly reduces the computational complexity, making the Fourier Transform widely used in practical applications. Fourier Transform is a technique that converts a signal from time domain to frequency domain. This means that it can decompose a signal into different frequency sine and cosine components, allowing the analysis of the spectral characteristics of the signal and the extraction of frequency domain information.

[0043] Optionally, before performing the Fast Fourier Transform on the filtered signal, the filtered signal can be windowed to prevent spectral leakage. After performing the Fast Fourier Transform on the windowed filtered signal, a preliminary transform result can be obtained. After taking half of the preliminary transform result, for example, taking the first half of the preliminary transform result, the transform result signal can be obtained. The reason for taking half is that the direct result of FFT transform has two symmetrical parts, and the taking half operation can eliminate the redundancy in the transform result.

[0044] In Fast Fourier Transform (FFT), windowing operation is an important preprocessing step for signal interception or adjustment to better perform spectral analysis. The basic idea of windowing operation is to multiply the original signal by a window function to limit the range of the signal in the time domain.

[0045] Step S203, searching for the maximum possible peak value in the transform result signal to obtain the first maximum possible peak value corresponding to the vital sign and the frequency domain frequency corresponding to the first maximum possible peak value.

[0046] In this step, the process of searching for the maximum possible peak value of the sign is as follows: first, find the maximum possible peak value of the transform result signal in the possible frequency (hz) range of the sign, and then determine the frequency of the maximum possible peak value as the corresponding frequency domain frequency. The transform result signal is the frequency domain distribution of the original signal, and the multiple frequency peak refers to the peak-shaped protruding part in the frequency distribution graph, which represents the energy concentration of a specific frequency in the signal. This energy concentration can be a multiple of the frequency in the periodic fluctuation signal, or a specific frequency in the aperiodic signal. The signal component of the vital sign has periodicity, so in the transform result signal, there are multiple frequency peaks corresponding to the real frequency of the vital sign signal component, and multiple frequency peaks corresponding to the integer multiple of the real frequency of the vital sign signal component. The lowest frequency in such a group of multiple frequency peaks can be referred to as the fundamental frequency of the group of multiple frequency peaks. In addition, the transform result signal can also include other multiple frequency peaks. These different multiple frequency peaks can be energy peaks in the frequency domain due to other periodic fluctuation signals in the original signal. It can be understood that these other periodic fluctuation signals other than vital signs are not as strong as the signal components generated by vital signs in the original signal, so the highest peak in the group of multiple frequency peaks with the maximum total energy in the transform result signal is considered to be the maximum possible peak value, and the frequency corresponding to the maximum possible peak value is referred to as the frequency domain frequency. The frequency domain frequency is most likely to be close to the real frequency.

[0047] In step S204, the original signal is filtered to obtain a time-domain vital sign waveform. Specifically, the original signal can be filtered according to the frequency domain frequency, the characteristics of the human vital sign, and the EMD result of the modal decomposition to obtain the time-domain vital sign waveform.

[0048] The original signal is an optical power signal collected by an optical fiber sensor, so the original signal is a time-domain signal. Filtering the original signal can obtain a time-domain vital sign waveform, which can be used to analyze the frequency of the signal component of the vital sign in the time domain. The frequency domain frequency can be used to determine the filtering range, and the filtering frequency band is determined based on the frequency domain frequency, and then the original signal is filtered to maximize the interference of irrelevant frequency bands.

[0049] As an optional embodiment, in the case of a heartbeat as the vital sign and a heart rate as the target frequency, filtering the original signal to obtain a time-domain vital sign waveform can include the following steps: performing modal decomposition (EMD) on the original signal to obtain a plurality of sub-component signals; performing fast Fourier transform on each of the plurality of sub-component signals to obtain a sub-component transform result signal corresponding to each of the plurality of sub-component signals; analyzing the sub-component transform result signals to select a target sub-component transform result signal from the sub-component transform result signals; analyzing the frequency spectrum characteristics of the target sub-component transform result signal to determine the possible frequency range of the vital sign; and filtering the original signal according to the possible frequency range to obtain a time-domain vital sign waveform.

[0050] In this optional embodiment, the target sub-component transformed result signal is a sub-component in all sub-component transformed result signals that includes vital sign signal components to the greatest extent. For example, some sub-component transformed result signals have too many high-frequency vibration components, too many noise and external interference signals, and do not include vital sign signal components. Therefore, the sub-component transformed result signal is not selected as the target sub-component transformed result signal and is not used to determine the frequency possible range of the vital sign.

[0051] As an optional embodiment, the frequency possible range of the vital sign is determined according to the target sub-component transformed result signal, including the following steps: performing a maximum possible vital sign peak value search on the target sub-component transformed result signal to obtain a third maximum possible peak value and a fourth maximum possible peak value in the target sub-component transformed result signal, wherein the third maximum possible peak value is the minimum value of the heartbeat possible peak values in the target sub-component transformed result signal, and the fourth maximum possible peak value is the maximum value of the heartbeat possible peak values in the target sub-component transformed result signal; and determining the frequency possible range according to the third maximum possible peak value and the fourth maximum possible peak value.

[0052] It can be understood that, since the target sub-component transformed result signal is also a frequency domain signal after fast Fourier transform, the maximum possible vital sign peak value search operation can also be used to search for peaks to find the upper and lower bounds of the heartbeat frequency from multiple target sub-component transformed result signals. The target sub-component transformed result signal can include multiple signals, and therefore multiple signal peaks, which are heartbeat possible peak values, can be identified through the peak search operation. The third maximum possible peak value is the minimum value of the heartbeat possible peak values, which does not mean that the peak height of the third maximum possible peak value is the lowest, but the signal frequency corresponding to the third maximum possible peak value is the minimum among the signal frequencies corresponding to all heartbeat possible peak values. The fourth maximum possible peak value is the maximum value of the heartbeat possible peak values, which does not mean that the peak height of the fourth maximum possible peak value is the highest, but the signal frequency corresponding to the fourth maximum possible peak value is the maximum among the signal frequencies corresponding to all heartbeat possible peak values. Therefore, the upper and lower bounds of the frequency possible range can be determined based on the third maximum possible peak value and the fourth maximum possible peak value.

[0053] In step S205, a time domain waveform peak value search is performed on the time domain vital sign waveform according to the frequency domain frequency and the human body limit frequency corresponding to the vital sign to obtain a second reliability degree corresponding to the vital sign and a time domain frequency. The process of the time domain waveform peak value search can also be referred to as time domain waveform peak detection.

[0054] In this step, the frequency domain frequency and the human body limit frequency corresponding to the vital sign limit the frequency band range of the peak search operation. The frequency peaks beyond the frequency domain frequency and the human body limit frequency range can be ignored, which are not possible to be the frequency of the vital sign signal of the human body.

[0055] In step S206, the target frequency of the vital sign in the original signal is determined according to the frequency domain frequency and the time domain frequency. The target frequency is obtained by synthesizing the results of the frequency domain frequency and the time domain frequency, and can be considered as the estimated real frequency of the vital sign of the monitored object.

[0056] As an optional embodiment, the target frequency of the vital sign in the original signal is determined according to the frequency domain frequency and the time domain frequency, including the following manner: the first reliability degree corresponding to the frequency domain frequency is determined according to the frequency domain frequency and the total sum of the multiple frequency peaks corresponding to the first maximum possible peak value; the second reliability degree corresponding to the time domain frequency is determined according to the time domain frequency and the total sum of the multiple frequency peaks corresponding to the second maximum possible peak value; and the target frequency is determined according to the frequency domain frequency, the time domain frequency, the first reliability degree and the second reliability degree. The first reliability degree and the second reliability degree can respectively reflect the confidence of the frequency domain frequency and the time domain frequency, and the frequency with higher reliability degree can be more referenced when determining the target frequency.

[0057] As an optional embodiment, the target frequency is determined according to the frequency domain frequency, the time domain frequency, the first reliability degree and the second reliability degree, including the following process: the frequency domain frequency and the time domain frequency are weighted and summed according to the first reliability degree and the second reliability degree to obtain the target frequency. Alternatively, the product results of the frequency domain frequency and the first reliability degree and the product results of the time domain frequency and the second reliability degree are summed to obtain a first value; the first reliability degree and the second reliability degree are summed to obtain a second value; and the first value is divided by the second value to obtain the target frequency.

[0058] Through the above steps, the original signal is obtained and filtered to obtain a filtered signal, wherein the filtered signal contains the signal component of the vital sign, and the original signal is an optical power signal; the filtered signal is subjected to fast Fourier transform to obtain a transformed result signal; the first maximum possible peak value corresponding to the vital sign and the frequency domain frequency corresponding to the first maximum possible peak value are obtained by searching for the maximum possible peak value in the transformed result signal; the original signal is filtered to obtain a time domain vital sign waveform; the time domain vital sign waveform is subjected to time domain waveform peak detection according to the frequency domain frequency and the human body limit frequency corresponding to the vital sign to obtain the time domain frequency corresponding to the vital sign; and the target frequency of the vital sign in the original signal is determined according to the frequency domain frequency and the time domain frequency. The above method achieves the purpose of accurately identifying the frequency of the vital sign signal from the optical power signal, thereby realizing the technical effect of improving the monitoring accuracy of the optical fiber sensor applied to the vital sign frequency identification process, and further solving the technical problem of low accuracy of the identification result of identifying the vital sign frequency based on the optical power signal.

[0059] Based on the above embodiments or optional embodiments, the present application provides the following specific embodiments to realize the monitoring of the vital sign frequency of the target object, which includes the following steps one to thirteen, steps one to seven can be used to determine the monitoring value of the respiratory rate, and steps eight to fourteen can be used to determine the monitoring value of the heartbeat.

[0060] Step one: an original optical power signal segment with a time length of t seconds and a sampling rate of fs is recorded as A, as shown in FIG. 3, and the original optical power signal A is the original signal described above. A low-pass filter with a frequency of 3 Hz is performed on A to obtain a signal B containing the respiratory component, as shown in FIG. 4, and the signal B is the filtered signal.

[0061] Step two: the signal B is windowed to prevent spectral leakage, and then the windowed signal is subjected to FFT fast Fourier transform to obtain a preliminary transform result, and the first half of the signal is taken as the Fourier transform result signal FB, as shown in FIG. 5.

[0062] Step three: the signal FB is taken before the part of 3 times the limit frequency (Hz) of the respiratory rate, and the signal is truncated, as shown in FIG. 6. Peak search is performed in the possible hertz range of the respiratory rate to find the maximum possible peak with the frequency peak in this range, recorded as peak_FB (the first maximum possible peak), and the corresponding frequency is recorded as fre_FB (the frequency domain frequency). If multiple possible peaks appear in the possible hertz range of the respiratory rate, the sum of the respective base peak and its frequency peak is considered, and the maximum sum of the peak value and the frequency peak value is selected as fre_FB. The FB signal amplitude sum, peak_FB and FB signal total energy_total in the possible frequency range of the human respiratory rate (for example, 0.1 hz-0.5 hz) are used for feature extraction, such as using the ratio between peak_FB and the total energy of the signal energy_total and the ratio between the signal sum and energy_total in the possible respiratory frequency range of the human body 0.1 hz-0.5 hz, and using the classifier to classify and determine whether the user is in bed.

[0063] Step four: if it is determined according to step three that the human body is off the bed, the calculation of the real frequency of the vital sign is ended, otherwise step five is continued.

[0064] Step five: the frequency domain frequency fre_FB (Hz) is combined with one minute 60 seconds to convert into the respiratory rate, recorded as frequency domain respiratory rate freq_Br. In the signal FB, the sum of fre_FB and the subsequent frequency peak and the FB signal total energy are combined for processing to obtain the frequency domain respiratory quality freq_Br_Quality (which is the first reliability degree in the above optional embodiment).

[0065] Step six: low pass filter the original signal under the breathing band (usually selected between 0.8-1hz) to get the time domain breathing waveform, denoted as signal TB, as shown in Figure 7. For signal TB, in combination with freq_Br and the limit respiratory rate of human physiology, the time domain breathing waveform peak finding operation is performed, and the time domain respiratory rate is calculated, denoted as time_Br (time domain frequency). According to the time length t seconds, time_Br and the signal sampling rate, the time domain breathing quality time_Br_Quality (i.e. the second reliability degree in the above optional embodiment) is calculated.

[0066] The average respiratory rate time_Br in the ideal case of the time length of t seconds appears the number of breathing wave peaks, denoted as N ideal , and the actual detected number of breathing wave peaks is N real ,

[0067] Step seven: calculate the final estimated value of the respiratory rate according to the above steps:

[0068] Respiratory rate = (time domain breathing * second reliability degree + frequency domain breathing * first reliability degree) / (second reliability degree + first reliability degree).

[0069] Step eight: based on the possible cutoff band of the heartbeat signal, band pass filter the original optical power signal A to get the signal C containing the heartbeat component to be judged.

[0070] Step nine: window the signal C to prevent spectral leakage, and then perform FFT Fourier transform on the windowed signal to get the Fourier result, and take the first half, denoted as Fourier result signal FC.

[0071] Step ten: take the part of signal FC less than 3 times the limit frequency of heart rate bpm, and cut off. In the range of the possible frequency band of heartbeat BPM, search for the peak value in the range, find the maximum possible peak value with multiple frequency peaks in the range, denoted as peak_FC, and the corresponding frequency is denoted as fre_FC. Convert fre_FC (Hz) to heart rate bpm by combining 60 seconds in a minute, denoted as frequency domain heart rate freq_Hp. In signal FC, in combination with fre_FC and the sum of subsequent multiple frequency peaks and the total sum of FC signal energy_total, the frequency domain heart rate quality freq_Hp_Quality (i.e. the first reliability degree in the above optional embodiment) is calculated.

[0072] Step eleven: the original waveform is decomposed by EMD. As shown in FIG. 8 (a summary of each component diagram of the final output time-domain heart rate waveform of a random original signal segment after EMD, the first line in FIG. 8 is the original signal and its corresponding FFT; the subsequent five lines in FIG. 8 are each subcomponent obtained by modal decomposition arranged from high frequency to low frequency, and the FFT results corresponding to each subcomponent, and the last line is the final determined time-domain respiration signal and time-domain heart rate signal), after the FFT analysis of each subcomponent obtained in the above step two, it is found that the first subcomponent has too many high-frequency vibration components, too many noise and external interference signals, and does not contain heartbeat components. The second, third and fourth subcomponents contain heartbeat components, and the last remaining subcomponent (residual) is very close to the time-domain respiration signal, but the fourth subcomponent and its FFT result also have a high possibility of containing respiration components, so when calculating the time-domain heart rate, only the second and third subcomponents are considered.

[0073] Step twelve: the FFT results of the second and third subcomponents are respectively subjected to maximum signal frequency peak finding to find the respective maximum possible heartbeat component signal frequencies (Hz) of the two, which are recorded as band2 and band3 respectively.

[0074] Step thirteen: the original signal A is subjected to bandpass Butterworth filtering with a cutoff frequency of band3-band2 to obtain a time-domain heartbeat waveform, which is recorded as signal TH. The signal TH is subjected to time-domain waveform peak finding operation in combination with freq_Hp and the limit heart rate of human physiology under normal circumstances, and the time-domain heart rate is calculated in combination with the sampling rate, which is recorded as time_Hp. In combination with the segment length t seconds, time_Hp and the signal TH, the time-domain heart rate quality of the current segment time_Hp_Quality (i.e. the second reliability degree in the above optional embodiment) is calculated.

[0075] The number of heartbeat peaks of the average heart rate time_Hp under the ideal condition of the length of t seconds is recorded as N ideal , and the number of actually detected heart rate peaks is N real ,

[0076] Step fourteen: the final heart rate estimate value is calculated according to the above steps:

[0077] Heartbeat frequency = (time-domain heart rate * second reliability degree + frequency-domain heart rate * first reliability degree) / (first reliability degree + second reliability degree).

[0078] The above embodiment combines time domain and frequency domain signal processing algorithms, and has advantages in calculating user heart rate and respiration rate in a common bed scene. Taking time domain heart rate calculation as an example, the method first performs EMD (Empirical Mode Decomposition) on the original optical fiber signal to find a subcomponent with a higher frequency band in which a heartbeat signal component is likely to exist. Then, the subcomponent that is likely to be a heart rate component is combined to perform FFT (Fast Fourier Transform) operation to determine the appropriate frequency band of each subcomponent. Finally, the original signal is filtered in a band-pass filtering manner using the determined maximum and minimum possible frequencies, and a good time domain heart rate waveform is obtained. According to the time domain heart rate / respiration waveform and its frequency domain characteristics, the average heart rate and respiration rate are calculated. The above embodiment is a method with user in / out of bed judgment and adaptive filtering, which can find the location of the heartbeat signal component as much as possible for each different signal input, and can improve the accuracy of time domain heart rate calculation.

[0079] It should be noted that, for the foregoing method embodiments, in order to simply describe, they are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited by the order of the described actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification all belong to preferred embodiments, and the actions and modules involved are not necessarily necessary for the present application.

[0080] Through the above description of the embodiments, those skilled in the art can clearly understand that the frequency determination method according to the above embodiments can be realized by means of software and a general hardware platform, of course, it can also be realized by hardware, but in many cases the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a plurality of instructions for making a terminal device (which can be a mobile phone, computer, server, or network device, etc.) execute the method of each embodiment of the present application.

[0081] According to the embodiment of the present application, a frequency determination device configured to implement the above frequency determination method is also provided, and FIG. 10 is a structural block diagram of the frequency determination device according to the embodiment of the present application. As shown in FIG. 10, the frequency determination device includes a first filtering module 1001, a transformation module 1002, a first peak searching module 1003, a second filtering module 1004, a second peak searching module 1005, and a determination module 1006. The frequency determination device will be described below.

[0082] The first filtering module 1001 is configured to acquire an original signal and filter the original signal to obtain a filtered signal, wherein the filtered signal contains a signal component of a vital sign, and the original signal is an optical power signal;

[0083] The transform module 1002 is connected to the first filtering module 1001 and configured to perform fast Fourier transform on the filtered signal to obtain a transformed result signal.

[0084] The first peak searching module 1003 is connected to the transform module 1002 and configured to search for a maximum possible vital sign peak in the transformed result signal to obtain a first maximum possible peak corresponding to the vital sign and a frequency domain frequency corresponding to the first maximum possible peak.

[0085] The second filtering module 1004 is connected to the first peak searching module 1003 and configured to filter the original signal to obtain a time domain vital sign waveform.

[0086] The second peak searching module 1005 is connected to the second filtering module 1004 and configured to search for a time domain waveform peak of the time domain vital sign waveform according to a human body limit frequency corresponding to the vital sign to obtain a time domain frequency.

[0087] The determination module 1006 is connected to the second peak searching module 1005 and configured to determine a target frequency of the vital sign in the original signal according to the frequency domain frequency and the time domain frequency.

[0088] It should be noted that the first filtering module 1001, the transform module 1002, the first peak searching module 1003, the second filtering module 1004, the second peak searching module 1005 and the determination module 1006 correspond to steps S201 to S206 in the embodiment, and the plurality of modules have the same instances and application scenarios as the corresponding steps, but are not limited to the contents disclosed in the above embodiment. It should be noted that the above modules can run in the computer terminal 10 provided in the embodiment as a part of the device.

[0089] The embodiment of the present application can provide a computer device. Optionally, in the embodiment, the computer device can be located in at least one network device of a plurality of network devices of a computer network. The computer device comprises a memory and a processor.

[0090] The memory can be configured to store software programs and modules, such as program instructions / modules corresponding to the frequency determination method and device in the embodiments of the present application. The processor executes various functions and data processing by running the software programs and modules stored in the memory, i.e., implements the frequency determination method described above. The memory can include a high-speed random access memory, and can further include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some examples, the memory can further include a memory remotely arranged with respect to the processor, which can be connected to the computer terminal through a network. Examples of the network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0091] The processor can call information and application programs stored in the memory through the transmission device to perform the following steps: obtaining an original signal and filtering the original signal to obtain a filtered signal, wherein the filtered signal contains a signal component of a vital sign, and the original signal is an optical power signal; performing fast Fourier transform on the filtered signal to obtain a transformed result signal; performing a maximum possible vital sign peak search in the transformed result signal to obtain a first maximum possible peak corresponding to the vital sign and a frequency domain frequency corresponding to the first maximum possible peak; filtering the original signal to obtain a time domain vital sign waveform; performing a maximum possible vital sign peak search on the time domain vital sign waveform according to the frequency domain frequency and a human body limit frequency corresponding to the vital sign to obtain a second maximum possible peak corresponding to the vital sign and a time domain frequency corresponding to the second maximum possible peak; and determining a target frequency of the vital sign in the original signal according to the frequency domain frequency and the time domain frequency.

[0092] Optionally, the processor can further execute program codes of the following steps: in the case that the vital sign is respiration, the target frequency is a respiration rate; or in the case that the vital sign is heartbeat, the target frequency is a heart rate.

[0093] Optionally, the processor can further execute program codes of the following steps: in the case that the vital sign is heartbeat and the target frequency is a heart rate, filtering the original signal to obtain a time domain vital sign waveform, including: modal decomposition of the original signal to obtain a plurality of sub-component signals; performing fast Fourier transform on the plurality of sub-component signals respectively to obtain a plurality of sub-component transformed result signals corresponding to the plurality of sub-component signals respectively; analyzing the sub-component transformed result signals to select a target sub-component transformed result signal from the sub-component transformed result signals; determining a frequency possible range of the vital sign according to the target sub-component transformed result signal; and filtering the original signal according to the frequency possible range to obtain the time domain vital sign waveform.

[0094] Optionally, the processor can further execute program codes of the following steps: determining the frequency possible range of the vital sign according to the target sub-component transformed result signal, comprising: performing a maximum possible sign peak search on the target sub-component transformed result signal to obtain a third maximum possible peak and a fourth maximum possible peak in the target sub-component transformed result signal, wherein the third maximum possible peak is the minimum value of the possible heart beat peak in the target sub-component transformed result signal, and the fourth maximum possible peak is the maximum value of the possible heart beat peak in the target sub-component transformed result signal; and determining the frequency possible range according to the third maximum possible peak and the fourth maximum possible peak.

[0095] Optionally, the processor can further execute program codes of the following steps: determining the target frequency of the vital sign in the original signal according to the frequency domain frequency and the time domain frequency, comprising: determining a first reliability degree corresponding to the frequency domain frequency according to the frequency domain frequency and the sum of the multiple frequency peaks corresponding to the first maximum possible peak; determining a second reliability degree corresponding to the time domain frequency according to the time domain frequency and the sum of the multiple frequency peaks corresponding to the second maximum possible peak; and determining the target frequency according to the frequency domain frequency, the time domain frequency, the first reliability degree and the second reliability degree.

[0096] Optionally, the processor can further execute program codes of the following steps: determining the target frequency according to the frequency domain frequency, the time domain frequency, the first reliability degree and the second reliability degree, comprising: performing a weighted sum on the frequency domain frequency and the time domain frequency according to the first reliability degree and the second reliability degree to obtain the target frequency.

[0097] Those skilled in the art can understand that all or part of the steps in the above-mentioned embodiments can be instructed by a program to the hardware related to the terminal device, and the program can be stored in a non-volatile storage medium, which can include a flash disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0098] The embodiments of the present application also provide a non-volatile storage medium. Optionally, in the present embodiment, the non-volatile storage medium can be configured to save the program codes executed by the frequency determination method provided in the above-mentioned embodiments.

[0099] Optionally, in the present embodiment, the non-volatile storage medium can be located in any one of the computer terminal in the computer terminal group in the computer network, or in any one of the mobile terminal in the mobile terminal group.

[0100] Optionally, in the embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: obtaining an original signal and filtering the original signal to obtain a filtered signal, wherein the filtered signal contains a signal component of a vital sign, and the original signal is an optical power signal; performing fast Fourier transform on the filtered signal to obtain a transformed result signal; performing a maximum possible vital sign peak search in the transformed result signal to obtain a first maximum possible peak corresponding to the vital sign and a frequency domain frequency corresponding to the first maximum possible peak; filtering the original signal to obtain a time domain vital sign waveform; performing a maximum possible vital sign peak search on the time domain vital sign waveform according to the frequency domain frequency and a human body limit frequency corresponding to the vital sign to obtain a second maximum possible peak corresponding to the vital sign and a time domain frequency corresponding to the second maximum possible peak; and determining a target frequency of the vital sign in the original signal according to the frequency domain frequency and the time domain frequency.

[0101] Optionally, in the embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: in a case where the vital sign is respiration, the target frequency is a respiration rate; or in a case where the vital sign is heartbeat, the target frequency is a heart rate.

[0102] Optionally, in the embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: in a case where the vital sign is heartbeat and the target frequency is a heart rate, filtering the original signal to obtain a time domain vital sign waveform, comprising: performing modal decomposition on the original signal to obtain a plurality of sub-component signals; performing fast Fourier transform on the plurality of sub-component signals respectively to obtain a plurality of sub-component transformed result signals corresponding to the plurality of sub-component signals respectively; analyzing the plurality of sub-component transformed result signals to select a target sub-component transformed result signal from the plurality of sub-component transformed result signals; determining a frequency possible range of the vital sign according to the target sub-component transformed result signal; and filtering the original signal according to the frequency possible range to obtain the time domain vital sign waveform.

[0103] Optionally, in the embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: determining the frequency possible range of the vital sign according to the target sub-component transformed result signal, comprising: performing a maximum possible vital sign peak search on the target sub-component transformed result signal to obtain a third maximum possible peak and a fourth maximum possible peak in the target sub-component transformed result signal, wherein the third maximum possible peak is a minimum value of heartbeat possible peaks in the target sub-component transformed result signal, and the fourth maximum possible peak is a maximum value of the heartbeat possible peaks in the target sub-component transformed result signal; and determining the frequency possible range according to the third maximum possible peak and the fourth maximum possible peak.

[0104] Optionally, in the embodiment, the nonvolatile storage medium is configured to store program code for performing the following steps: determining the target frequency of the vital sign in the original signal according to the frequency domain frequency and the time domain frequency, comprising: determining a first reliability degree corresponding to the frequency domain frequency according to the frequency domain frequency and the sum of the multiple frequency peaks corresponding to the first maximum possible peak; determining a second reliability degree corresponding to the time domain frequency according to the time domain frequency and the sum of the multiple frequency peaks corresponding to the second maximum possible peak; and determining the target frequency according to the frequency domain frequency, the time domain frequency, the first reliability degree and the second reliability degree.

[0105] Optionally, in the embodiment, the nonvolatile storage medium is configured to store program code for performing the following steps: determining the target frequency according to the frequency domain frequency, the time domain frequency, the first reliability degree and the second reliability degree, comprising: performing weighted summation on the frequency domain frequency and the time domain frequency according to the first reliability degree and the second reliability degree to obtain the target frequency.

[0106] The above-mentioned serial numbers of the embodiments of the application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0107] In the above-mentioned embodiments of the application, the description of each embodiment has its own emphasis, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0108] In several embodiments provided in the present application, it should be understood that the disclosed technical contents can be implemented by other manners. Among them, the above-mentioned device embodiments are only schematic, for example, the division of units can be a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units or modules shown or discussed can be indirect coupling or communication connection through some interfaces, units or modules, which can be electrical or other forms.

[0109] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on multiple units. Part or all of the units can be selected to achieve the purpose of the embodiment according to actual needs.

[0110] In addition, each functional unit in each embodiment of the application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The above integrated unit can be realized in the form of hardware or in the form of software functional unit.

[0111] If the integrated unit is implemented in the form of a software function unit and sold or used as an independent product, it can be stored in a nonvolatile storage medium. Based on this understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions to make a computer device (which can be a personal computer, a server or a network device, etc.) execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0112] The above is only the preferred embodiment of the present application, and it should be noted that those skilled in the art can make some improvements and refinements without departing from the principles of the present application, and these improvements and refinements should also be considered within the scope of protection of the present application. Industrial applicability

[0113] The scheme provided by the embodiments of the present application can be applied to the field of signal processing. In the embodiments of the present application, an original signal is obtained and filtered to obtain a filtered signal, wherein the filtered signal contains a signal component of a vital sign; the filtered signal is subjected to fast Fourier transform to obtain a transformed result signal; a maximum possible vital sign peak value and a frequency domain frequency corresponding to the maximum possible vital sign peak value are obtained by searching for the maximum possible vital sign peak value in the transformed result signal; the original signal is filtered to obtain a time domain vital sign waveform; the time domain vital sign waveform is subjected to time domain waveform peak detection to obtain a time domain frequency in cooperation with a segment length, a signal sampling rate and a number of peaks; and a target frequency of the vital sign in the original signal is determined according to the frequency domain frequency and the time domain frequency. The embodiment solves the technical problem of low accuracy of the identification result of identifying the vital sign frequency based on the optical power signal, and achieves the purpose of accurately identifying the frequency of the vital sign signal from the optical power signal, thereby achieving the technical effect of improving the monitoring accuracy of the optical fiber sensor applied to the vital sign frequency identification process.

Claims

1. A frequency determination method, comprising: Acquire an original signal and filter the original signal to obtain a filtered signal, wherein the filtered signal contains a signal component of a vital sign, and the original signal is an optical power signal; Performing a fast Fourier transform on the filtered signal to obtain a transformed result signal; Performing a maximum possible peak value search corresponding to the vital sign in the transformed result signal to obtain a first maximum possible peak value corresponding to the vital sign and a frequency domain frequency corresponding to the first maximum possible peak value; Filtering the original signal to obtain a time-domain vital sign waveform; Performing a time domain waveform peak search on the time domain vital sign waveform according to the human body limit frequency corresponding to the vital sign to obtain the time domain frequency; A target frequency of the vital sign in the original signal is determined according to the frequency domain frequency and the time domain frequency.

2. The method according to claim 1, wherein When the vital sign is respiration, the target frequency is the respiratory rate; or when the vital sign is heartbeat, the target frequency is the heart rate.

3. The method according to claim 2, wherein: In the case where the vital sign is a heartbeat and the target frequency is a heart rate, filtering the original signal to obtain a time-domain vital sign waveform includes: Performing modal decomposition on the original signal to obtain multiple sub-component signals; Performing fast Fourier transform (FFT) on the multiple sub-component signals respectively to obtain sub-component transformation result signals corresponding to the multiple sub-component signals; analyzing the sub-component transformation result signals, and selecting a target sub-component transformation result signal from the sub-component transformation result signals; determining a possible frequency range of the vital sign according to the target subcomponent transformation result signal; The original signal is filtered according to the possible frequency range to obtain the time-domain vital sign waveform.

4. The method according to claim 3, wherein: Determining the possible frequency range of the vital sign according to the target sub-component transformation result signal includes: Performing a maximum possible sign peak search on the target sub-component transformation result signal to obtain a third maximum possible peak and a fourth maximum possible peak in the target sub-component transformation result signal, wherein the third maximum possible peak is a minimum value of possible heartbeat peaks in the target sub-component transformation result signal, and the fourth maximum possible peak is a maximum value of possible heartbeat peaks in the target sub-component transformation result signal; The possible frequency range is determined according to the third maximum possible peak value and the fourth maximum possible peak value.

5. The method according to claim 1, wherein The determining, based on the frequency domain frequency and the time domain frequency, a target frequency of the vital sign in the original signal includes: determining a first reliability corresponding to the frequency domain frequency according to the frequency domain frequency and a sum of frequency multiplication peaks corresponding to the first maximum possible peak value; Determining a second reliability corresponding to the time domain frequency based on the time domain frequency, the signal sampling rate, a comparison result of a theoretical number of time domain waveform peaks calculated based on the time domain segment duration, and an actually found number of time domain waveform peaks; The target frequency is determined according to the frequency domain frequency, the time domain frequency, the first reliability level, and the second reliability level.

6. The method according to claim 5, wherein: The determining the target frequency according to the frequency domain frequency, the time domain frequency, the first reliability level, and the second reliability level includes: According to the first reliability level and the second reliability level, a weighted sum is performed on the frequency domain frequency and the time domain frequency to obtain the target frequency.

7. A frequency determination device, comprising: a first filtering module configured to acquire an original signal and filter the original signal to obtain a filtered signal, wherein the filtered signal contains a signal component of a vital sign, and the original signal is an optical power signal; a transform module configured to perform a fast Fourier transform on the filtered signal to obtain a transform result signal; a first peak-finding module configured to search for a maximum possible peak value corresponding to the vital sign in the transformed result signal, and obtain a first maximum possible peak value corresponding to the vital sign and a frequency domain frequency corresponding to the first maximum possible peak value; a second filtering module, configured to filter the original signal to obtain a time-domain vital sign waveform; A second peak-finding module is configured to perform a time-domain waveform peak search on the time-domain vital sign waveform according to a human body limit frequency corresponding to the vital sign to obtain a time-domain frequency; The determination module is configured to determine a target frequency of the vital sign in the original signal according to the frequency domain frequency and the time domain frequency.

8. A non-volatile storage medium comprising a stored program, wherein: When the program is running, the device where the non-volatile storage medium is located is controlled to execute the frequency determination method according to any one of claims 1 to 6.

9. A computer device comprising a memory and a processor, wherein the memory is configured to store a program, and the processor is configured to run the program stored in the memory, wherein: When the program is executed, the frequency determination method according to any one of claims 1 to 6 is executed.

10. A computer program product comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the steps of the frequency determination method according to any one of claims 1 to 6.

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