A millimeter wave radar human heart rate measurement method and system based on respiratory harmonic analysis

Abstract

The application provides a kind of millimeter wave radar human heart rate measurement method and system based on respiratory harmonic analysis.The method uses the I / Q signal collected by millimeter wave radar, uses the extended DACM algorithm to obtain phase change information;Then analyze the time domain waveform of vital sign information, calculate the non-symmetry parameter of respiration and the pause parameter of respiratory gap, to analyze the bandwidth of dynamic adjustment notch filter, while suppressing the influence of respiratory harmonic on the heartbeat spectrum;Finally, through the time domain number peak way, the heart rate estimation range is reduced, and the Chirp-Z transform is applied to obtain higher accuracy heartbeat frequency.The heart rate measurement method of the application is simple, and compared with the previous respiratory harmonic elimination method, the strength of respiratory harmonic is more effectively analyzed and targetedly suppressed, and the measurement accuracy when the heart rate and the respiratory harmonic frequency coincide can be effectively improved.

Description

Technical Field

[0001] This invention relates to the field of heart rate measurement, specifically to a millimeter-wave radar method and system for measuring human heart rate based on respiratory harmonic analysis. Background Technology

[0002] With the continuous advancement of modern technology, millimeter-wave radar, as a non-contact sensing technology, is increasingly widely used in the medical field. Among these applications, heart rate detection based on millimeter-wave radar has become a research focus of considerable attention in recent years. This technology utilizes the high resolution and penetrating power of millimeter-wave radar to monitor heart rate in real time without contact with the patient, providing a more comfortable experience. Furthermore, this non-invasive technology offers significant advantages in hospital, home care, and elderly care settings.

[0003] Among numerous non-contact heart rate measurement methods, millimeter-wave radar offers significant advantages in accuracy, penetration capability, privacy protection, anti-interference ability, and real-time monitoring. Its high penetration capability allows it to operate stably in various environments, unaffected by light or weather conditions. Furthermore, millimeter-wave radar can detect minute changes in vital signs, providing high-precision and high-sensitivity monitoring. Regarding privacy protection, millimeter-wave radar does not generate visual images or videos, ensuring user privacy and security, which makes it a promising candidate for applications in fields such as medicine, remote monitoring, and sports science.

[0004] In the signal preprocessing stage, phase extraction technology is used to extract phase signals reflecting human vital signs from baseband I / Q signals. Among phase extraction methods, the most commonly used is the arctangent demodulation and extended DAM algorithm. By combining the algorithms of the two channels, accurate phase demodulation can be achieved regardless of the target position or displacement amplitude. By applying an arctangent operation to the ratio of the I and Q branch output data, accurate phase demodulation can always be obtained, unaffected by the target position. To address the phase discontinuity problem, an extended differential and cross-multiplication (DACM) algorithm has been proposed for automatic phase unwrapping to achieve unambiguous phase reconstruction.

[0005] In the signal processing stage of millimeter-wave radar vital sign detection, notch filters based on minimum mean square error are used to filter out respiratory harmonics. However, traditional notch filters indiscriminately filter out all signals within a certain frequency range, potentially including heartbeat signals. Mode decomposition algorithms such as VMD, EEMD, and CEEMDAN are used to separate heartbeat signals from other noise signals, but they easily cause spectral aliasing between respiratory harmonics and heartbeat signals, making it impossible to distinguish the frequency of the heartbeat signal. Differential enhancement algorithms are used to enhance the intensity of the heartbeat component, but noise components with frequencies close to the heartbeat are amplified, affecting heart rate estimation. Summary of the Invention

[0006] To overcome the problems in the aforementioned background technology, this invention provides a millimeter-wave radar method and system for measuring human heart rate based on respiratory harmonic analysis. This method aims to reduce interference from respiratory harmonics, thereby improving the accuracy of heart rate estimation. The method consists of three main parts: phase information extraction, respiratory adaptive filtering, and heart rate estimation. The phase information extraction step aims to achieve automatic discontinuity correction based on the acquired phase information. Considering that the time-domain waveform of respiration contains harmonic information, a respiratory adaptive filtering step is introduced. This step dynamically adjusts the bandwidth of the notch filter according to the asymmetry of respiration and the pause time of the respiratory interval to reduce the impact of respiratory harmonics on heart rate estimation. The respiratory adaptive filtering step prevents the excessive suppression of frequencies near respiratory harmonics, a common problem in previous respiratory harmonic processing methods. Furthermore, the heart rate estimation step narrows the frequency search range by using a time-domain peak counting method (calculating the number of peaks in the heartbeat frequency band signal) and improves frequency resolution using Chirp-Z transform to obtain more accurate heart rate information. This method can effectively improve the measurement accuracy when heart rate and respiratory harmonic frequencies coincide.

[0007] This invention is achieved using the following technical solution:

[0008] A millimeter-wave radar method for measuring human heart rate based on respiratory harmonic analysis includes the following steps:

[0009] S1: Phase information extraction:

[0010] S11: The millimeter-wave radar acquires the echo signal and uses an orthogonal mixer to downconvert the echo signal into a baseband I / Q signal;

[0011] S12: Use the extended DCAM algorithm to extract the phase information of the human thoracic cavity from the baseband I / Q signal;

[0012] S2: Suppression of respiratory harmonics: This step analyzes the intensity of respiratory harmonics and performs targeted suppression, minimizing the impact on adjacent spectra while suppressing respiratory harmonics to avoid erroneous suppression of heartbeat information.

[0013] S21: By analyzing the time domain information of the phase information, respiratory information is obtained, and the asymmetric parameters of respiration and respiratory arrest parameters are calculated based on the respiratory information;

[0014] S22: The bandwidth and order of the notch filter are dynamically adjusted according to the asymmetric parameters of breathing and the parameters of respiratory pause to suppress respiratory harmonics of phase information;

[0015] S3: Heart Rate Estimation

[0016] S31: Bandpass filtering is performed on the phase information after respiratory harmonic suppression to obtain the heartbeat frequency band signal, with the passband set to [0.8, 2] Hz;

[0017] S32: By calculating the number of peak values ​​of the heartbeat frequency band signal, the upper cutoff frequency of the heartbeat is determined, and the heartbeat frequency is calculated.

[0018] In the above technical solution, step S12 further comprises:

[0019] Perform time-domain filtering on each frame of the signal: s[k, d] lp = αs[k-1, d] + (1-α)s[k, d], where α represents the smoothing coefficient, and s[k, d]... lp Let s[k, d] represent the time-domain filtered I / Q signal at a distance d from time k. The unit R with the largest input signal amplitude is used as the distance index to the human target. An extended DAM algorithm is then used to extract the phase information of the human chest cavity. Where I[k] and Q[k] represent the in-phase and quadrature components of the peak distance unit at time k, respectively.

[0020] Further, step S21 specifically includes:

[0021] (a) The phase information of the human chest cavity is filtered through a bandpass filter with the passband set to [0.1, 1.5] Hz. The filtered phase information is used as the respiratory information. This step can remove low-frequency DC information while retaining the main harmonic information of respiration.

[0022] (b) The method for calculating the asymmetric parameter of respiration is as follows: Peaks and troughs in the time domain are found through time-domain peak finding to determine the entire respiratory cycle time, expiration time, and inspiratory time, and the asymmetric parameter r of respiration is then calculated.

[0023]

[0024] Among them, T total T represents the total respiratory cycle time. inhale Indicates the inhalation time;

[0025] (c) Substitute the inhalation time, exhalation time, and respiratory pause parameter p into the respiratory expression to obtain the respiratory waveform; the respiratory expression is as follows:

[0026] 1) Inhalation phase: 0 ≤ t < T inhale :

[0027]

[0028] 2) Expiratory phase Tinhale ≤t<T total :

[0029]

[0030] Among them, T exhale The exhalation time is indicated by the parameter p, which represents the duration of the pause in lung contraction during the respiratory interval, and t represents time.

[0031] (d) Calculate the proportion of the entire respiratory cycle where the respiratory amplitude is greater than half the peak value of the respiratory waveform, ΔR. -3dB Then, based on the correspondence, ΔR -3dB The parameter p is converted into a respiratory arrest parameter; the method for obtaining the corresponding relationship is as follows: ΔR is calculated based on the respiratory waveform in step (c). -3dB Then, based on the respiratory arrest parameters p and ΔR -3dB The corresponding relationship is obtained by fitting.

[0032] Furthermore, step S22 specifically includes:

[0033] The following responses are made to harmonics of different orders:

[0034] For the second harmonic of respiration: Set up a notch filter for the second harmonic of respiration, and establish the relationship between the notch bandwidth B2 and the parameters p and r: B2=min{α r r+α p (p-2), B max}Hz, α r α p B is a scaling factor for pre-defined parameters p and r. max This is the upper limit of the notch bandwidth, which can be set to 0.025Hz;

[0035] For the third and fourth harmonics of respiration: when the respiration waveform satisfies r>η (η is the set threshold), a notch filter is set for the third and fourth harmonics of respiration with a fixed notch bandwidth; otherwise, no notch filter is set for the third and fourth harmonics of respiration.

[0036] Among them, parameters p and r are related to the intensity of respiratory harmonics. Based on these two parameters, the bandwidth and order of the notch filter are adjusted so that respiratory harmonics of different orders can be suppressed in a targeted manner.

[0037] Step S32 specifically involves:

[0038] The number of peaks in the heartbeat frequency band signal is calculated by counting peaks in the time domain to determine the upper cutoff frequency of the heartbeat and the range of the heartbeat frequency is determined to be [0.7Hz, upper cutoff frequency]. The parameters of the Chirp-Z transform are set according to the heartbeat frequency band, and the Chirp-Z transform is applied to the phase information signal after suppressing respiratory harmonics. The peak value in the range of the heartbeat frequency is found as the estimated heartbeat frequency.

[0039] The present invention also provides a millimeter-wave radar human heart rate measurement system based on respiratory harmonic analysis. The system is used to perform the above method and specifically includes a phase information extraction module, a respiratory adaptive filtering module, and a heart rate estimation module.

[0040] The phase information extraction module is used to extract phase signals containing human body information;

[0041] The breathing adaptive filtering module is used to calculate the asymmetric parameters of breathing and the breathing pause parameters based on the breathing information in the phase information, and to dynamically adjust the bandwidth and order of the notch filter using the asymmetric parameters of breathing and the breathing pause parameters to suppress the breathing harmonics in the phase information.

[0042] The heart rate estimation module is used to estimate the heart rate.

[0043] The beneficial effects of this invention are as follows:

[0044] This invention uses time-domain filtered I / Q signals and applies an advanced DAM algorithm to demodulate phase information, suppressing clutter interference and achieving automatic discontinuity correction. By calculating the asymmetric parameters of respiration and respiratory pause parameters, the intensity of each respiratory harmonic is estimated, and a notch filter is dynamically designed accordingly to effectively suppress respiratory interference while minimizing interference to other signals in the spectrum. Simultaneously, in the heart rate estimation process, the frequency search range is narrowed using time-domain peak counting, and the frequency resolution is improved using Chirp-Z transform, directly yielding the estimated heart rate; thus achieving robust heart rate estimation under the influence of respiratory harmonics and noise. This can be further applied to routine health monitoring and medical surveillance. Attached Figure Description

[0045] Figure 1 This is a flowchart of the method of the present invention.

[0046] Figure 2 The transformation relationship is used to calculate the pause parameter p.

[0047] Figure 3 The diagram shows the effect of respiratory parameters p and r on the generation of respiratory harmonics.

[0048] Figure 4 A comparison chart of heart rate signals measured by radar and pulse signals measured by a pulse oximeter. Detailed Implementation

[0049] like Figure 1 The diagram shows a flowchart of the millimeter-wave radar human heart rate measurement method based on respiratory harmonic analysis according to the present invention. This method relies on a millimeter-wave radar human heart rate measurement device based on respiratory harmonic analysis. The millimeter-wave radar human heart rate measurement device based on respiratory harmonic analysis includes a phase information extraction module, a respiratory adaptive notch filtering module, and a heart rate estimation module.

[0050] 1) Phase information extraction module, used to obtain phase signals containing human body information;

[0051] The millimeter-wave radar acquires the echo signal and uses an orthogonal mixer to downconvert the echo signal into a baseband I / Q signal;

[0052] The phase information of the human thoracic cavity is extracted from the baseband I / Q signal using an extended DAM algorithm, specifically as follows:

[0053] Perform time-domain filtering on each frame of the signal: s[k, d] lp =αs[k-1, d]+(1-α)s[k,d].

[0054] Where α represents the smoothing coefficient, s[k, d] lp Let s[k, d] represent the time-domain filtered I / Q signal at a distance d from k.

[0055] Using the distance cell with the largest input signal amplitude as the distance index of the human target, the extended DAM algorithm is used to extract the phase information of the human chest cavity:

[0056]

[0057] Where I[k] and Q[k] represent the in-phase and quadrature components of the peak distance unit at time k, respectively.

[0058] 2) Respiratory Adaptive Filtering Module

[0059] By analyzing the time-domain information of the phase information, respiratory information is obtained, and the asymmetric parameters of respiration and respiratory arrest parameters are calculated based on the respiratory information.

[0060] The bandwidth and order of the notch filter are dynamically adjusted based on the asymmetric parameters of respiration and the parameters of respiratory pauses to suppress respiratory harmonics in phase information.

[0061] Specifically, the calculation of the asymmetric parameters of respiration and the parameters of respiratory arrest is carried out using the following steps:

[0062] (a) Transmitting the phase information of the human thoracic cavity through [f L f H Breathing information is obtained using a bandpass filter of 100Hz, f L To remove DC information, use 0.1Hz, f H 1.5Hz was selected to preserve the main harmonic information of breathing.

[0063] (b) Find the peaks and troughs of respiration by time-domain peak finding and calculate the asymmetric parameter r;

[0064] The asymmetric parameter r of respiration is calculated as follows: Among them, T total T represents the total respiratory cycle time. inhale Indicates the inhalation time.

[0065] (c) Substitute the inhalation time, exhalation time, and respiratory pause parameter p into the respiratory expression to obtain the respiratory waveform; the respiratory expression is as follows:

[0066] 1) Inhalation phase: 0 ≤ t < T inhale :

[0067]

[0068] 2) Expiratory phase T inhale ≤t<T total :

[0069]

[0070] Among them, T exhale The exhalation time is indicated by the parameter p, which represents the duration of the lung contraction during the respiratory interval, and t represents the time.

[0071] (d) Calculate the proportion of the entire respiratory cycle where the respiratory amplitude is greater than half the peak value of the respiratory waveform, ΔR. -3dB Then, based on the correspondence, ΔR -3dB The parameter p is converted into a respiratory arrest parameter; the method for obtaining the corresponding relationship is as follows: ΔR is calculated based on the respiratory waveform in step (c). -3dB Then, based on the respiratory arrest parameters p and ΔR -3dB The corresponding relationships were obtained through fitting, and are shown in the appendix. Figure 2 .

[0072] The method for dynamically adjusting the bandwidth and number of cycles of the notch filter based on the asymmetric parameters of respiration and the parameters of respiratory pauses is as follows:

[0073] (a) For the second harmonic of respiration: Set up a notch filter for the second harmonic of respiration. The relationship between the notch bandwidth B2 and the parameters p and r is: B2=min{αr r+α p (p-2), B max}Hz

[0074] Where, α r α p These are the scaling factors for the pre-defined parameters p and r, respectively; B max The upper limit of the notch bandwidth is set to 0.025Hz;

[0075] (b) For the third and fourth harmonics of respiration: if r > η (η is the set threshold, which can be 0.1), set a notch filter for the third and fourth harmonics of respiration, and set a fixed notch bandwidth B3 = 0.004Hz and B4 = 0.004Hz; otherwise, do not set a notch filter for the third and fourth harmonics of respiration.

[0076] like Figure 3 This diagram illustrates the influence of parameters p and r on the generation of respiratory harmonics. It clearly shows that parameter p primarily affects the intensity of the second harmonic of respiration, while parameter r affects the duration of inspiration and expiration. Significant respiratory asymmetry corresponds to uneven inhalation and expiration, which not only generates the second harmonic but also causes multiple harmonics in the respiratory waveform. Therefore, the intensity of the second harmonic of respiration can be estimated using both parameters p and r, while the generation of higher harmonics can be estimated using parameter r.

[0077] 3) Heart rate estimation module

[0078] Bandpass filtering is performed on the phase information after respiratory harmonic suppression to obtain the heartbeat frequency band signal;

[0079] The upper cutoff frequency of the heartbeat is determined by calculating the number of peak values ​​in the heartbeat frequency band signal, and the heartbeat frequency is calculated using the following method:

[0080] The number of peaks in the heartbeat frequency band signal is calculated by counting peaks in the time domain, thereby determining the upper cutoff frequency of the heartbeat. The range of the heartbeat frequency is [0.7Hz, upper cutoff frequency].

[0081] The parameters of the Chirp-Z transform are set according to the heart rate frequency band, and the Chirp-Z transform is applied to the phase information signal after removing respiratory harmonics.

[0082] Find the peak value within the interval of heart rate and use it as the heart rate.

[0083] Figure 4 The figure shows the heart rate signal measured by radar and the pulse signal measured by a pulse oximeter using the method of the present invention. As can be seen from the figure, the peak frequency of the heart rate signal measured by radar obtained by the present invention is basically the same as that of the reference signal (pulse signal), indicating that the present invention can measure accurate heart rate results.

Claims

1. A millimeter-wave radar method for measuring human heart rate based on respiratory harmonic analysis, characterized in that, Includes the following steps: S1: Phase Information Extraction: Obtaining phase signals containing human body information; S11: The millimeter-wave radar acquires the echo signal and uses an orthogonal mixer to downconvert the echo signal into a baseband I / Q signal; S12: Use the extended DCAM algorithm to extract the phase information of the human thoracic cavity from the baseband I / Q signal; S2: Respiratory adaptive filtering: S21: By analyzing the time domain information of the phase information, respiratory information is obtained, and the asymmetric parameters of respiration and respiratory arrest parameters are calculated based on the respiratory information; S22: The bandwidth and order of the notch filter are dynamically adjusted according to the asymmetric parameters of breathing and the parameters of respiratory pause to suppress respiratory harmonics of phase information; S3: Heart Rate Estimation S31: Bandpass filtering is performed on the phase information after respiratory harmonic suppression to obtain the heartbeat frequency band signal; S32: By calculating the number of peak values ​​of the heartbeat frequency band signal, determine the upper cutoff frequency of the heartbeat, and calculate the heartbeat frequency; Step S21 specifically involves: (a) The phase information of the human chest cavity is filtered through a bandpass filter to obtain respiratory information; the passband of the bandpass filter is set to [0.1, 1.5] Hz; (b) The method for calculating the asymmetric parameters of respiration is as follows: Based on the peaks and troughs of time-domain information, determine the entire respiratory cycle time, expiration time, and inspiratory time; calculate the asymmetric parameters of respiration. : ； in, This indicates the duration of the entire respiratory cycle. Indicates the inhalation time; (c) Parameters of inhalation time, expiration time, and respiratory pause Substituting these values ​​into the breathing expression, we obtain the breathing waveform; the breathing expression is as follows: 1) Inhalation phase : ； 2) Exhalation phase : ； in, Indicates expiratory time, respiratory pause parameter The duration of the pause in lung contraction during the respiratory interval is indicated by t, which represents time. (d) Calculate the proportion of the entire respiratory cycle in which the respiratory amplitude is greater than half of the peak value of the respiratory waveform. Then, based on the corresponding relationship, Converted to respiratory arrest parameters The method for obtaining the correspondence is as follows: calculated based on the respiratory waveform in step (c). Then based on the respiratory arrest parameters and The corresponding relationship is obtained by fitting.

2. The millimeter-wave radar method for measuring human heart rate based on respiratory harmonic analysis according to claim 1, characterized in that, Step S12 specifically involves: Perform time-domain filtering on each frame of the signal: ,in, Represents the smoothing coefficient. express Time Distance Coordinates The I / Q signal at that point after time-domain filtering. express Time Distance Coordinates The I / Q signals at the location are used; the unit with the largest input signal amplitude is used as the distance index of the human target, and the extended DAM algorithm is used to extract the phase information of the human chest cavity: ,in, and These represent the peak distance units at... In-phase and quadrature components at time points.

3. The millimeter-wave radar method for measuring human heart rate based on respiratory harmonic analysis according to claim 1, characterized in that, Step S22 specifically involves: (a) For the second harmonic of respiration: Set a notch filter for the second harmonic of respiration, with a notch bandwidth of With parameters and Relationship between them: Hz, , Each is a pre-set parameter and Scale factor, This represents the upper limit of the notch bandwidth; (b) For the third and fourth harmonics of respiration: if hour, For the set threshold, set a notch filter for the third and fourth harmonics of respiration with a fixed notch bandwidth; otherwise, do not set a notch filter for the third and fourth harmonics of respiration.

4. The millimeter-wave radar method for measuring human heart rate based on respiratory harmonic analysis according to claim 1, characterized in that, Step S32 specifically involves: Calculate the number of peak values ​​of the heartbeat frequency band signal, determine the upper cutoff frequency of the heartbeat, and determine the range of the heartbeat frequency as [0.7 Hz, upper cutoff frequency]; set the parameters of the Chirp-Z transform according to the heartbeat frequency band, and apply the Chirp-Z transform to the phase information signal after suppressing respiratory harmonics; Find the peak value within the interval of heart rate and use it as the heart rate.

5. A millimeter-wave radar human heart rate measurement system based on respiratory harmonic analysis, used to perform the method as described in any one of claims 1-4, characterized in that, It includes a phase information extraction module, a respiratory adaptive filtering module, and a heart rate estimation module; The phase information extraction module is used to extract phase signals containing human body information; The breathing adaptive filtering module is used to calculate the asymmetric parameters of breathing and the breathing pause parameters based on the breathing information in the phase information, and to dynamically adjust the bandwidth and order of the notch filter using the asymmetric parameters of breathing and the breathing pause parameters to suppress the breathing harmonics in the phase information. The heart rate estimation module is used to estimate the heart rate.

6. The millimeter-wave radar human heart rate measurement system based on respiratory harmonic analysis according to claim 5, characterized in that, The phase information extraction module is used to extract phase signals containing human body information. The specific method is as follows: The millimeter-wave radar acquires the echo signal and uses an orthogonal mixer to downconvert the echo signal into a baseband I / Q signal; Phase information of the human thoracic cavity is extracted from the baseband I / Q signal using an extended DAM algorithm.

7. The millimeter-wave radar human heart rate measurement system based on respiratory harmonic analysis according to claim 5, characterized in that, The method for calculating the asymmetric parameters of respiration and the respiratory pause parameters based on the respiratory information in the phase information is as follows: (a) The phase information of the human chest cavity is filtered through a bandpass filter to obtain respiratory information; the passband of the bandpass filter is set to [0.1, 1.5] Hz; (b) The method for calculating the asymmetric parameters of respiration is as follows: Based on the peaks and troughs of time-domain information, determine the entire respiratory cycle time, expiration time, and inspiratory time; calculate the asymmetric parameters of respiration. : ； in, This indicates the duration of the entire respiratory cycle. Indicates the inhalation time; (c) Parameters of inhalation time, expiration time, and respiratory pause Substituting these values ​​into the breathing expression, we obtain the breathing waveform; the breathing expression is as follows: 1) Inhalation phase : ； 2) Exhalation phase : ； in, Indicates expiratory time, respiratory pause parameter The duration of the pause in lung contraction during the respiratory interval is indicated by t, which represents time. (d) Calculate the proportion of the entire respiratory cycle in which the respiratory amplitude is greater than half of the peak value of the respiratory waveform. Then, based on the corresponding relationship, Converted to respiratory arrest parameters The method for obtaining the correspondence is as follows: calculated based on the respiratory waveform in step (c). Then based on the respiratory arrest parameters and The corresponding relationship is obtained by fitting.

8. The millimeter-wave radar human heart rate measurement system based on respiratory harmonic analysis according to claim 7, characterized in that, The method of dynamically adjusting the bandwidth and order of the notch filter using the asymmetric parameters of respiration and the parameters of respiratory pause to suppress respiratory harmonics of phase information is as follows: (a) For the second harmonic of respiration: Set a notch filter for the second harmonic of respiration, with a notch bandwidth of With parameters and Relationship between them: Hz, , Each is a pre-set parameter and Scale factor, This represents the upper limit of the notch bandwidth; (b) For the third and fourth harmonics of respiration: if hour, For the set threshold, set a notch filter for the third and fourth harmonics of respiration with a fixed notch bandwidth; otherwise, do not set a notch filter for the third and fourth harmonics of respiration.

9. The millimeter-wave radar human heart rate measurement system based on respiratory harmonic analysis according to claim 5, characterized in that, The heart rate estimation module is used to estimate heart rate, and the specific method is as follows: Bandpass filtering is performed on the phase information after respiratory harmonic suppression to obtain the heartbeat frequency band signal; By calculating the number of peak values ​​in the heartbeat frequency band signal, the upper cutoff frequency of the heartbeat is determined, and the heartbeat frequency is calculated.

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