An evaluation method and system for quality of pulse signals of the guan chi

Abstract

The application discloses an evaluation method and system for the quality of cun, guan and chi pulse signals. Firstly, waveform preprocessing is performed on the original pulse wave signals collected in real time, so that waveform noise reduction and waveform smoothing are performed on the original pulse wave signals. Then, an FFT conversion method is applied to convert the original pulse wave signals to the frequency domain, so as to obtain frequency domain waveform signals. Then, frequency domain waveform features of the frequency domain waveform signals are obtained. Finally, the quality of the cun, guan and chi pulse signals is evaluated according to the frequency domain waveform features, and data screening is performed on the original pulse wave signals according to the evaluation results. Since the waveforms of the voltage waveform signals collected by collecting the cun pulse pressure, the guan pulse pressure and the chi pulse pressure are different in the frequency domain, the quality of the signals can be evaluated, and whether the current evaluated signal is the cun, guan and chi pulse signal corresponding to the evaluation can be identified.

Description

Technical Field

[0001] This invention relates to the field of biological signal acquisition and preprocessing technology, specifically to a method and system for evaluating the quality of cun, guan, and chi pulse signals. Background Technology

[0002] The Cun, Guan, and Chi pulse signals can be acquired using a three-channel pulse data acquisition device. Post-processing analysis based on the Cun, Guan, and Chi data is used for training disease diagnostic models, etc. Generally, the pulse data acquired by the pulse diagnosis device is first screened, then subjected to various preprocessing steps such as time-frequency domain analysis and filtering, and finally selected for pulse data with good signal quality for further post-processing. However, even pulse data with good signal quality may be invalid data during post-processing (for example, the acquired pulse data may have good interference signal quality), which will bring difficulties to the subsequent data screening and processing. When the acquired pulse data is confirmed to be invalid, it is impossible to re-acquire it (data acquisition and post-processing are generally separate). Therefore, if the quality of the Cun, Guan, and Chi pulse signals can be screened and identified during the pulse signal acquisition process or at the pulse data acquisition stage (if the signal quality is poor, it should be discarded and re-acquired), the effectiveness, usability, and reliability of the pulse data will be greatly increased. Summary of the Invention

[0003] The main technical problem this invention addresses is how to improve the effectiveness and reliability of pulse signal acquisition at the cun, guan, and chi positions.

[0004] According to the first aspect, one embodiment provides a method for evaluating the quality of the cun, guan, and chi pulse signals, comprising:

[0005] The raw pulse wave signal acquired in real time is subjected to waveform preprocessing to perform waveform noise reduction and waveform smoothing; wherein, the raw pulse wave signal includes voltage waveform signals of changes in cun pulse pressure, guan pulse pressure and wei pulse pressure acquired in time-division or synchronously.

[0006] The original pulse wave signal is converted to the frequency domain using the FFT transformation method to obtain the frequency domain waveform signal;

[0007] Obtain the frequency domain waveform characteristics of the frequency domain waveform signal;

[0008] The quality of the Cun-Guan-Chi pulse signal is evaluated based on the frequency domain waveform characteristics, and then the original pulse wave signal is filtered based on the evaluation results.

[0009] In one embodiment, the waveform preprocessing of the raw pulse wave signal acquired in real time includes:

[0010] The low-frequency baseline drift noise of the original pulse wave signal is filtered out using a Butterworth high-pass filter;

[0011] A low-pass filter is applied to remove high-frequency noise from the original pulse wave signal;

[0012] The original pulse wave signal is smoothed and filtered using a window sliding method.

[0013] In one embodiment, obtaining the frequency domain waveform features of the frequency domain waveform signal includes:

[0014] The frequency domain waveform features include a frequency domain waveform function expression, core frequency component parameters, spectral energy distribution parameters, and / or shape and complexity parameters; wherein, the core frequency component parameters include fundamental frequency, harmonics, and / or dominant frequency, the spectral energy distribution parameters include spectral centroid, spectral standard deviation, spectral amplitude, and / or spectral power, and the shape and complexity parameters include bandwidth and / or spectral entropy.

[0015] In one embodiment, evaluating the quality of the Cun-Guan-Chi pulse signal based on the frequency domain waveform characteristics includes:

[0016] The frequency domain waveform function expression is:

[0017] X(f) = A0 + Σ[A n ×e^(-j(2πfnt+φ n ))];

[0018] Where X(f) is the complex value at frequency f, A0 is the DC component, Σ represents the summation sign, n is a natural number indicating the harmonic order, and A n Let φ be the amplitude of the nth harmonic. n Let f be the phase of the nth harmonic, and f be the fundamental frequency.

[0019] Signal quality is assessed based on the similarity between the frequency domain waveform signal and the frequency domain waveform function expression of the corresponding Cun-Guan-Chi pulse signal.

[0020] In one embodiment, the step of filtering the raw pulse wave signal based on the evaluation results includes:

[0021] The similarity between the frequency domain waveform signal and the frequency domain waveform function expression of the corresponding Cun-Guan-Chi pulse signal is scored, and the score result is proportional to the quality of the Cun-Guan-Chi pulse signal.

[0022] In one embodiment, scoring the similarity between the frequency domain waveform signal and the frequency domain waveform function expression of the corresponding cun-guan-chi pulse signal includes:

[0023] The number of waveforms and / or peak amplitude values ​​of the frequency domain waveform signal are obtained within a preset frequency peak range based on the frequency domain waveform function expression. The closer the number of waveforms and / or peak amplitude values ​​are to the preset number of waveforms and / or peak amplitude values ​​of the corresponding cun-guan-chi pulse signal, the higher the score value.

[0024] In one embodiment, the evaluation method further includes:

[0025] After the voltage waveform signals of the changes in cun pulse pressure, guan pulse pressure, and chi pulse pressure in the original pulse wave signal are converted to the frequency domain, each corresponds to a different frequency domain waveform function expression. The voltage waveform signals of the changes in cun pulse pressure, guan pulse pressure, or chi pulse pressure are distinguished according to the corresponding different frequency domain waveform function expressions.

[0026] According to a second aspect, one embodiment provides a computer-readable storage medium storing a computer program that can be executed by a processor to implement the method as described in the first aspect.

[0027] According to a third aspect, one embodiment provides a computer program product including a computer program and / or instructions that, when executed by a processor, implement the method described in the first aspect.

[0028] According to the fourth aspect, one embodiment provides an evaluation system for assessing the quality of the cun, guan, and chi pulse signals, for applying the evaluation method as described in the first aspect, the evaluation system comprising:

[0029] The preprocessing unit is used to perform waveform preprocessing on the raw pulse wave signal acquired in real time, so as to perform waveform noise reduction and waveform smoothing on the raw pulse wave signal; wherein, the raw pulse wave signal includes voltage waveform signals of the changes in cun pulse pressure, guan pulse pressure and wei pulse pressure acquired in time-division or synchronously.

[0030] The frequency domain conversion unit is used to apply the FFT conversion method to convert the original pulse wave signal to the frequency domain to obtain a frequency domain waveform signal;

[0031] The feature extraction unit acquires the frequency domain waveform features of the frequency domain waveform signal;

[0032] The data filtering unit evaluates the quality of the cun, guan, and chi pulse signals based on the frequency domain waveform characteristics, and then filters the original pulse wave signals based on the evaluation results.

[0033] Since the voltage waveforms of the collected cun, guan, and chi pulse pressure changes differ in the frequency domain, the evaluation method described above can not only assess the quality of the signal itself, but also identify whether the signal being evaluated corresponds to the pre-evaluated cun, guan, and chi pulse signal. This can effectively detect cross-acquisition errors between cun, guan, and chi pulse pressure caused by incorrect acquisition channel switching, and can also identify whether the acquisition positions of cun, guan, and chi pulses are inaccurate. Attached Figure Description

[0034] Figure 1 This is a schematic diagram of a method for evaluating the quality of pulse signals at the cun, guan, and chi positions in one embodiment.

[0035] Figure 2 This is a functional structure of a system for evaluating the quality of pulse signals at the cun, guan, and chi positions, as described in one embodiment.

[0036] Figure 3 A schematic diagram comparing the voltage waveform signal and the corresponding frequency domain waveform signal of pulse pressure;

[0037] Figure 4 A schematic diagram comparing the voltage waveform signal and the corresponding frequency domain waveform signal of pulse pressure;

[0038] Figure 5 This is a schematic diagram comparing the voltage waveform signal of ulnar pulse pressure and the corresponding frequency domain waveform signal. Detailed Implementation

[0039] The present invention will now be described in further detail with reference to specific embodiments and accompanying drawings. Similar elements in different embodiments are referred to by associated similar element reference numerals. In the following embodiments, many details are described to facilitate a better understanding of this application. However, those skilled in the art will readily recognize that some features may be omitted in different situations, or may be replaced by other elements, materials, or methods. In some cases, certain operations related to this application are not shown or described in the specification. This is to avoid obscuring the core parts of this application with excessive description. For those skilled in the art, detailed description of these related operations is not necessary; they can fully understand the related operations based on the description in the specification and general technical knowledge in the art.

[0040] Furthermore, the features, operations, or characteristics described in the specification can be combined in any suitable manner to form various embodiments. At the same time, the steps or actions in the method description can be rearranged or adjusted in a manner obvious to those skilled in the art. Therefore, the various orders in the specification and drawings are only for the clear description of a particular embodiment and do not imply a necessary order, unless otherwise stated that a particular order must be followed.

[0041] The serial numbers assigned to components in this document, such as "first" and "second," are used only to distinguish the described objects and have no sequential or technical meaning. The terms "connection" and "linkage" used in this application, unless otherwise specified, include both direct and indirect connections (linkages).

[0042] The pulse signal acquired by the pulse sensor is a weak physiological signal, frequently affected by external environment, human body, and circuit system interference, especially the cun, guan, and chi pulse signals. Based on multi-channel sensors and analog circuitry, the biological pulse signal is converted into an electrical signal. Because multi-channel circuits have identical structures, close spatial distances, and similar operating modes, and because multiple channels acquire data time-sharing or synchronously, they are more susceptible to interference. This results in the acquired signal containing interference from other channels, meaning the signal acquired on-site may not meet the requirements of subsequent data processing. Consequently, the effectiveness and reliability of the pulse data acquired from the cun, guan, and chi pulse signals are poor, leading to a very high data discard rate. The core of judging signal effectiveness lies in the inherent characteristics of the human pulse signal. Besides the peak strength in the time domain, the pulse wave inevitably exhibits a certain rhythm and frequency specificity because the human body is a living organism, maintained by the regular beating of the heart. Based on this characteristic, in-depth analysis of the pulse data is conducted to address situations where insufficient or excessive sensor contact during signal acquisition results in no signal. Avoiding redundant data acquisition can effectively improve the efficiency of signal acquisition and significantly reduce subsequent data filtering costs. It has certain advantages in data filtering for signal acquisition. During signal acquisition, peak detection can be performed on the acquired pulse wave signal to determine the peak and starting positions, followed by feature extraction of the acquired waveform. Finally, signal quality is evaluated based on multiple waveform feature data. While this method can achieve some optimization, it cannot identify some signal acquisition errors. For example, if the cun pulse signal should be acquired but the guan pulse signal is actually acquired (i.e., a channel signal acquisition error), since both cun and guan pulse signals are valid pulse signals, this mismatch between cun and guan pulse signals cannot be identified by this technical solution.

[0043] In this embodiment of the application, the collected cun, guan, and chi pulse signals are first converted to the frequency domain, and then the signal quality is evaluated based on the frequency domain waveform characteristics. Since the voltage waveform signals of the collected cun, guan, and chi pulse pressure changes are different in the frequency domain, the cross-acquisition error between cun, guan, and chi pulse pressure caused by the acquisition channel switching error can be detected.

[0044] Example 1:

[0045] This application aims to efficiently solve the problem of real-time signal validity during pulse diagnosis signal acquisition, providing evaluation criteria for different signal qualities and effectively determining signal usability. Besides improving signal quality during pulse acquisition, it also reduces the workload of data filtering after acquisition. Please refer to... Figure 1 This is a schematic diagram of a method for evaluating the quality of pulse signals at the cun, guan, and chi positions, as described in one embodiment, including:

[0046] Step 101: Perform waveform preprocessing.

[0047] The raw pulse wave signal acquired in real time undergoes waveform preprocessing to perform waveform noise reduction and smoothing. The raw pulse wave signal includes voltage waveform signals representing the changes in cun, guan, and ulnar pulse pressures acquired time-divisionally or synchronously. In one embodiment, the waveform preprocessing includes applying a Butterworth high-pass filter to remove low-frequency baseline drift noise from the raw pulse wave signal, applying a low-pass filter to remove high-frequency noise from the raw pulse wave signal, and applying a window sliding method to smooth the raw pulse wave signal.

[0048] Step 102, frequency domain conversion.

[0049] The original pulse wave signal is converted to the frequency domain using the FFT method to obtain a frequency domain waveform signal. A Fourier transform is then performed, and the transformed waveform is fitted using a preset frequency domain waveform function expression. In one embodiment, the frequency domain waveform function expression is:

[0050] X(f) = A0 + Σ[A n × e^(-j(2πfnt+φ n ))];

[0051] Where X(f) is a complex value at frequency f (containing amplitude and phase information, its absolute value (modulus) |X(f)| is the amplitude spectrum), A0 is the DC component (representing the average value of the signal, corresponding to the average blood pressure level in a pulse wave), Σ represents the summation sign, n is a natural number indicating the harmonic order, and A n φ represents the amplitude of the nth harmonic (the contribution of each frequency component to the original waveform). n Let f be the phase of the nth harmonic, and f be the fundamental frequency (f = heart rate / 60Hz).

[0052] Step 103: Obtain frequency domain waveform features.

[0053] Frequency domain waveform features include frequency domain waveform function expressions, core frequency component parameters, spectral energy distribution parameters, and / or shape and complexity parameters. Core frequency component parameters include fundamental frequency, harmonics, and / or dominant frequency; spectral energy distribution parameters include spectral centroid, spectral standard deviation, spectral amplitude, and / or spectral power; and shape and complexity parameters include bandwidth and / or spectral entropy. Since the voltage waveforms of the acquired cun, guan, and chi pulse pressure changes show significant differences after conversion to the frequency domain, one or more difference features can be extracted for signal quality screening, particularly effective in identifying whether the currently acquired pulse signal is a pre-acquired cun, guan, or chi pulse signal.

[0054] Step 104, data filtering.

[0055] The quality of the Cun-Guan-Chi pulse signal is evaluated based on its frequency domain waveform characteristics, and then the original pulse wave signal is filtered based on the evaluation results. In one embodiment of this application, the signal quality is evaluated based on the similarity between the frequency domain waveform signal and the frequency domain waveform function expression of the corresponding Cun-Guan-Chi pulse signal. The similarity between the frequency domain waveform signal and the frequency domain waveform function expression of the corresponding Cun-Guan-Chi pulse signal is scored, and the score value is proportional to the quality of the Cun-Guan-Chi pulse signal. In one embodiment, the number of waveforms and / or peak amplitude values ​​of the frequency domain waveform signal within a preset frequency peak range are obtained based on the frequency domain waveform function expression. The closer the number of waveforms and / or peak amplitude values ​​are to the preset number of waveforms and / or peak amplitude values ​​of the corresponding Cun-Guan-Chi pulse signal, the higher the score value.

[0056] In one embodiment of this application, in order to simplify the process complexity and reduce computational load, focusing only on the amplitude spectrum, the frequency domain waveform function expression is simplified to:

[0057] |X(f)|≈Σ[A n [×δ(f-nf0)];

[0058] Here, δ is the Dirac function, which indicates that energy is concentrated only on the fundamental frequency f0 and its harmonics nf0.

[0059] This can be understood as a series of "spectral peaks" at these discrete frequency points, the height of which is A. n For quantitative analysis, empirical functions are used to fit this decaying harmonic amplitude curve, which can be achieved by extracting A from the actual pulse wave spectrum. n This is used to assess the quality of the pulse wave waveform. For example, a variant of a Gaussian function or an exponentially decaying function is used to approximate A. n As n changes.

[0060] In one embodiment, after the voltage waveform signals of the changes in cun pulse pressure, guan pulse pressure and chi pulse pressure in the original pulse wave signal are converted to the frequency domain, each corresponds to a different frequency domain waveform function expression, and the voltage waveform signal of the changes in cun pulse pressure, guan pulse pressure or chi pulse pressure is distinguished according to the corresponding different frequency domain waveform function expressions.

[0061] To facilitate understanding of the implementation of the scoring and screening process in the embodiments of this application, a specific embodiment is described below, including:

[0062] Based on the analysis of 200 sets of data, a comprehensive evaluation is conducted, with a maximum score of 100. Data scoring 60 points or higher are considered to possess usable frequency domain waveform characteristics and have analytical value, leading to recommended screening conclusions. The waveform quality score is calculated as follows:

[0063] The calculation calculates the number of waveforms with peak frequencies within 5Hz and their peak amplitudes. For peak counts within the range (0, 1), a base score of 50 is given. Further score adjustments are made based on peak distribution. For peak counts between (1, 5), the waveform is considered good and receives a base score of 65, indicating the spectrum is within the normal human frequency range. Further bonus points are awarded based on peak size; larger peaks indicate better signal quality. If the number of peaks within 5Hz exceeds 5, the base score decreases. For scores below 50, adjustments are made based on peak amplitude. A final waveform quality score is obtained by combining all these factors.

[0064] In one embodiment of this application, the pulse waveform quality evaluation process only requires simple filtering and noise reduction of the pulse wave, followed by Fourier transform, analysis of the Fourier transform data, peak finding, and counting of features such as the number of waveforms within 5Hz, and score calculation. The process is relatively simple, can be implemented in embedded code, and is fast. It enables rapid data quality assessment.

[0065] Please refer to Figure 2This document describes the functional structure of a system for evaluating the quality of Cun-Guan-Chi pulse signals in one embodiment. The system includes a preprocessing unit 10, a frequency domain conversion unit 20, a feature extraction unit 30, and a data filtering unit 40. The preprocessing unit 10 performs waveform preprocessing on the real-time acquired raw pulse wave signals to reduce noise and smooth the waveforms. The raw pulse wave signals include voltage waveform signals representing the changes in Cun, Guan, and Chi pulse pressures acquired time-divisionally or synchronously. The frequency domain conversion unit 20 applies an FFT transformation method to convert the raw pulse wave signals to the frequency domain to obtain frequency domain waveform signals. The feature extraction unit 30 acquires the frequency domain waveform features of the frequency domain waveform signals. The data filtering unit 40 evaluates the quality of the Cun-Guan-Chi pulse signals based on the frequency domain waveform features and then filters the raw pulse wave signals based on the evaluation results.

[0066] Please refer to Figure 3 , Figure 4 and Figure 5 The diagrams above compare the voltage waveforms and corresponding frequency domain waveforms of the pulse pressure changes at the cun, guan, and chi levels. The left side shows the acquired voltage waveform, and the right side shows the corresponding frequency domain waveform. In the voltage waveform, the horizontal axis represents the sampling point, and the vertical axis represents the signal amplitude. In the frequency domain waveform, the horizontal axis represents the frequency (Hz), and the vertical axis represents the power gain (dB), both relative values. These examples clearly distinguish the cun, guan, and chi pulse signals. It should be noted that the acquisition process of the cun, guan, and chi pulse signals involves both voltage boosting and voltage reduction. In the data analysis example described above, only the data from the voltage boosting process was captured.

[0067] This application discloses a method for evaluating the quality of Cun, Guan, and Chi pulse signals. First, the raw pulse wave signal acquired in real-time undergoes waveform preprocessing to reduce noise and smooth the waveform. Then, the raw pulse wave signal is converted to the frequency domain using an FFT transformation method to obtain a frequency domain waveform signal. Next, the frequency domain waveform characteristics of the frequency domain waveform signal are acquired. Finally, the quality of the Cun, Guan, and Chi pulse signals is evaluated based on the frequency domain waveform characteristics, and the raw pulse wave signals are filtered based on the evaluation results. Since the voltage waveforms of the Cun, Guan, and Chi pulse pressure changes differ in the frequency domain, this method can not only evaluate the quality of the signal itself but also identify whether the currently evaluated signal corresponds to the Cun, Guan, and Chi pulse signal being evaluated.

[0068] Those skilled in the art will understand that all or part of the functions of the various methods in the above embodiments can be implemented by hardware or by computer programs. When all or part of the functions in the above embodiments are implemented by computer programs, the program can be stored in a computer-readable storage medium, which may include: read-only memory, random access memory, disk, optical disk, hard disk, etc., and the program is executed by a computer to achieve the above functions. For example, the program can be stored in the memory of a device, and when the program in the memory is executed by the processor, all or part of the above functions can be achieved. In addition, when all or part of the functions in the above embodiments are implemented by computer programs, the program can also be stored in a server, another computer, disk, optical disk, flash drive, or external hard drive, etc., and can be downloaded or copied to the memory of a local device, or the system of the local device can be updated. When the program in the memory is executed by the processor, all or part of the functions in the above embodiments can be achieved.

[0069] The above examples illustrate the present invention only to aid in understanding it and are not intended to limit the scope of the invention. Those skilled in the art can make various simple deductions, modifications, or substitutions based on the principles of this invention.

Claims

1. A method for evaluating the quality of pulse signals at the cun, guan, and chi positions, characterized in that, include: The raw pulse wave signal acquired in real time is subjected to waveform preprocessing to perform waveform noise reduction and waveform smoothing; wherein, the raw pulse wave signal includes voltage waveform signals of changes in cun pulse pressure, guan pulse pressure and wei pulse pressure acquired in time-division or synchronously. The original pulse wave signal is converted to the frequency domain using the FFT transformation method to obtain the frequency domain waveform signal; The frequency domain waveform features of the frequency domain waveform signal are obtained; the frequency domain waveform features include a frequency domain waveform function expression, core frequency component parameters, spectral energy distribution parameters, and / or shape and complexity parameters; wherein, the core frequency component parameters include fundamental frequency, harmonics, and / or dominant frequency, the spectral energy distribution parameters include spectral centroid, spectral standard deviation, spectral amplitude, and / or spectral power, and the shape and complexity parameters include bandwidth and / or spectral entropy; The quality of the Cun-Guan-Chi pulse signal is evaluated based on the frequency domain waveform characteristics, and then the original pulse wave signal is filtered based on the evaluation results. The evaluation of the quality of the Cun-Guan-Chi pulse signal based on the frequency domain waveform characteristics includes: The frequency domain waveform function expression is: X(f)=A0+Σ[A n ×e^(-j(2πfnt+φ n ))]; Where X(f) is the complex value at frequency f, A0 is the DC component, Σ represents the summation sign, n is a natural number indicating the harmonic order, and A n Let φ be the amplitude of the nth harmonic. n Let f be the phase of the nth harmonic, and f be the fundamental frequency. Signal quality is assessed based on the similarity between the frequency domain waveform signal and the frequency domain waveform function expression of the corresponding Cun-Guan-Chi pulse signal. The data filtering of the original pulse wave signal based on the evaluation results includes: The similarity between the frequency domain waveform signal and the frequency domain waveform function expression of the corresponding Cun-Guan-Chi pulse signal is scored, and the score result is proportional to the quality of the Cun-Guan-Chi pulse signal.

2. The evaluation method as described in claim 1, characterized in that, The waveform preprocessing of the raw pulse wave signal acquired in real time includes: The low-frequency baseline drift noise of the original pulse wave signal is filtered out using a Butterworth high-pass filter; A low-pass filter is applied to remove high-frequency noise from the original pulse wave signal; The original pulse wave signal is smoothed and filtered using a window sliding method.

3. The evaluation method as described in claim 1, characterized in that, The similarity between the frequency domain waveform signal and the corresponding cun-guan-chi pulse signal is scored, including: The number of waveforms and / or peak amplitude values ​​of the frequency domain waveform signal are obtained within a preset frequency peak range based on the frequency domain waveform function expression. The closer the number of waveforms and / or peak amplitude values ​​are to the preset number of waveforms and / or peak amplitude values ​​of the corresponding cun-guan-chi pulse signal, the higher the score value.

4. The evaluation method as described in claim 1, characterized in that, Also includes: After the voltage waveform signals of the changes in cun pulse pressure, guan pulse pressure, and chi pulse pressure in the original pulse wave signal are converted to the frequency domain, each corresponds to a different frequency domain waveform function expression. The voltage waveform signals of the changes in cun pulse pressure, guan pulse pressure, or chi pulse pressure are distinguished according to the corresponding different frequency domain waveform function expressions.

5. A computer-readable storage medium, characterized in that, The medium stores a computer program that can be executed by a processor to implement the method as described in any one of claims 1-4.

6. A computer program product, comprising a computer program and / or instructions, characterized in that, When the computer program and / or instructions are executed by the processor, they implement the method of any one of claims 1-4.

7. A system for evaluating the quality of pulse signals at the cun, guan, and chi positions, characterized in that, For applying the evaluation method as described in any one of claims 1 to 4, the evaluation system comprises: The preprocessing unit is used to perform waveform preprocessing on the raw pulse wave signal acquired in real time, so as to perform waveform noise reduction and waveform smoothing on the raw pulse wave signal; wherein, the raw pulse wave signal includes voltage waveform signals of the changes in cun pulse pressure, guan pulse pressure and wei pulse pressure acquired in time-division or synchronously. The frequency domain conversion unit is used to apply the FFT conversion method to convert the original pulse wave signal to the frequency domain to obtain a frequency domain waveform signal; The feature extraction unit is used to obtain the frequency domain waveform features of the frequency domain waveform signal; The data filtering unit is used to evaluate the quality of the Cun-Guan-Chi pulse signal based on the frequency domain waveform characteristics, and then filter the original pulse wave signal based on the evaluation results.

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