Pulse diagnosis device for real-time remote restoration of traditional Chinese medicine pulse condition

Abstract

The invention discloses a pulse diagnosis device for real-time remote restoration of traditional Chinese medicine pulse conditions, which relates to the technical field of biomedicine, and comprises the following steps: synchronously acquiring pulse condition analog signal data through multiple channels, inputting the pulse condition analog signal data to a pulse condition processor for processing, and converting the pulse condition analog signal data into digital pulse condition signal data; the remote diagnosis equipment receives and decrypts the digital pulse condition signal data and converts the digital pulse condition signal data into pulse condition analog signal data; constructing a high-fidelity pulse condition simulator, receiving pulse condition simulation signal data, dynamically adjusting pulse condition parameters by using a high-frequency vibrator and a biosensor, and generating a real pulse condition; and a linear regression model is selected to carry out further adaptive calibration on pulse condition analog signal data, diagnosis is carried out according to the restored real pulse condition, and a treatment scheme is provided. The pulse condition simulation signal data are received through the high-fidelity pulse condition simulator, the pulse condition simulation signal data parameters are dynamically adjusted through the high-frequency vibrator and the biosensor, and real pulse condition simulation reproduction is achieved.

Description

Technical Field

[0001] The invention relates to the technical field of biomedicine, in particular to a pulse diagnosis device for real-time remote restoration of traditional Chinese medicine pulse. Background Art

[0002] In the field of traditional Chinese medicine, pulse diagnosis, as one of the traditional diagnostic methods, has a history of thousands of years. By palpating the patient's pulse, the doctor can understand the state of qi and blood circulation in the body and make a judgment on the condition. However, since pulse diagnosis is highly dependent on the doctor's experience and feel, it is difficult to standardize and popularize pulse diagnosis technology. In addition, traditional pulse diagnosis cannot achieve remote diagnosis, which is an important limitation in the modern medical environment. With the development of information technology and biosensor technology, in recent years, the scientific community and the medical field have begun to explore the combination of modern technology with traditional Chinese medicine pulse diagnosis to improve the accuracy and operability of pulse diagnosis and realize the possibility of remote diagnosis.

[0003] Existing related technologies mainly focus on the collection, transmission and processing of pulse data. Some studies have developed multi-channel pulse collectors that can synchronously collect pulse data from different pulse positions and transmit them to remote equipment wirelessly. However, these technologies still have some shortcomings. First, the accuracy and stability of data acquisition need to be improved, and high-fidelity pulse simulation has not yet been achieved. Secondly, how to ensure the integrity and security of data during data transmission is still a challenge. Finally, the existing technology lacks an adaptive calibration mechanism in data processing and analysis, which affects the accuracy and reliability of remote diagnosis. Summary of the invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a pulse diagnosis device for real-time remote restoration of TCM pulse to solve the problem of real-time remote restoration and diagnosis of TCM pulse.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a pulse diagnosis device for real-time remote restoration of traditional Chinese medicine pulse, comprising:

[0008] The collecting module is used for synchronously collecting pulse analog signal data through multiple channels, inputting the pulse analog signal data into the pulse processor for processing and converting into digital pulse signal data;

[0009] The transmission module is used to compress and encrypt the digital pulse signal data, and transmit the encrypted and compressed digital pulse signal data to the remote diagnosis equipment in real time using an adaptive algorithm;

[0010] A conversion module, used for remote diagnosis equipment to receive and decrypt digital pulse signal data, and convert the digital pulse signal data back to pulse analog signal data;

[0011] A building module is used to build a high-fidelity pulse simulator, receive pulse simulation signal data, dynamically adjust pulse parameters using a high-frequency vibrator and a biosensor, and generate a real pulse;

[0012] The diagnosis module is used to select a linear regression model to further adaptively calibrate the pulse simulation signal data, and to diagnose and propose a treatment plan based on the restored real pulse.

[0013] As a preferred solution of the pulse diagnosis device for real-time remote restoration of TCM pulse condition described in the present invention, wherein: the multiple channels include Cun pulse, Guan pulse and Chi pulse.

[0014] As a preferred solution of the pulse diagnosis device for real-time remote restoration of TCM pulse described in the present invention, the pulse simulation signal data includes pulse rate, pulse amplitude, pulse width, pulse type, pulse pressure, pulse position, pulse variation value and pulse spectrum.

[0015] As a preferred solution of the pulse diagnosis device for real-time remote restoration of TCM pulse of the present invention, wherein: the pulse analog signal data is input to the pulse processor for processing and converted into digital pulse signal data, the specific steps are as follows:

[0016] The collected pulse analog signal data is input into the pulse processor and amplified by a low noise amplifier;

[0017] The amplified pulse analog signal data is filtered through an analog filter;

[0018] The pulse condition analog signal data after filtering is divided into low-frequency signal data, medium-frequency signal data and high-frequency signal data;

[0019] The low-frequency signal data, the intermediate-frequency signal data and the high-frequency signal data are enhanced by a multi-band gain control algorithm;

[0020] Performing baseline drift compensation on the enhanced low-frequency signal data;

[0021] Performing characteristic amplitude compensation on the enhanced intermediate frequency signal data;

[0022] Performing noise compensation on the enhanced high-frequency signal data;

[0023] Correcting the error in the pulse simulation signal data according to the compensated multi-band signal data;

[0024] Select a high-precision analog-to-digital converter, input the pulse analog signal after multi-band compensation into the high-precision analog-to-digital converter, and convert it into digital pulse signal data. The expression is:

[0025]

[0026] Where D is the converted digital pulse signal data, V in is the input pulse analog signal voltage value, in is the input symbol, V ref+ is the positive terminal value of the reference voltage, V ref- is the negative terminal value of the reference voltage, ref is the reference value, n is the resolution of the high-precision analog-to-digital converter, and V is the voltage.

[0027] As a preferred solution of the pulse diagnosis device for real-time remote restoration of TCM pulse of the present invention, the digital pulse signal data is compressed and encrypted, and the encrypted and compressed digital pulse signal data is transmitted to the remote diagnosis equipment in real time by using an adaptive algorithm. The specific steps are as follows:

[0028] The converted digital pulse signal data is divided into a plurality of digital pulse signal data segments according to size;

[0029] Add sequence sorting to each digital pulse signal data segment, and compress the sorted digital pulse signal data segment through LZ77 algorithm to generate a digital pulse signal data packet;

[0030] The compressed digital pulse signal data packet is encrypted by AES, and the network environment is monitored by an adaptive transmission algorithm, and the sending rate of the digital pulse signal data packet is adjusted according to the real-time network bandwidth;

[0031] Sending the encrypted and compressed digital pulse signal data packet to the remote diagnosis equipment via a wireless network;

[0032] During the transmission of the digital pulse signal data packet, a CRC check is used to detect whether the digital pulse signal data packet is correct;

[0033] If a digital pulse signal data packet error is detected, the adaptive transmission algorithm will trigger a retransmission mechanism to retransmit the erroneous digital pulse signal data packet until the transmission is successful.

[0034] As a preferred solution of the pulse diagnosis device for real-time remote restoration of TCM pulse of the present invention, wherein: the remote diagnosis equipment receives and decrypts digital pulse signal data, and converts the digital pulse signal data back to pulse analog signal data;

[0035] After receiving the digital pulse signal data packet, the remote diagnosis equipment reassembles it according to the sequence number;

[0036] Perform AES decryption on the reorganized digital pulse signal data packet;

[0037] The decrypted original compressed digital pulse signal data packet is decompressed by LZ77 algorithm;

[0038] Input the decompressed digital pulse signal data into a high-precision digital-to-analog converter;

[0039] The high-precision digital-to-analog converter converts the digital pulse signal data back to the pulse analog signal data, and the expression is:

[0040] V out (t)=(V d (t)-∈·sin(ωt))×(1+α·e -γt );

[0041] Among them, V out (t) is the output pulse analog signal voltage data value that changes with time, out is the output symbol, V d (t) is the input digital pulse signal voltage data value that changes with time, d is the index of the digital pulse signal, ∈ is the noise correction term of the digital pulse signal, ω is the angular frequency of the digital pulse signal, α is the adaptive correction coefficient, γ is the time constant, e is the base of the natural logarithm, and t is the time variable.

[0042] As a preferred solution of the pulse diagnosis device for real-time remote restoration of TCM pulse condition of the present invention, the high-fidelity pulse condition simulator is constructed to receive pulse condition simulation signal data, and the specific steps are as follows:

[0043] Select a high-frequency vibrator and install it in a high-fidelity pulse simulator;

[0044] Connect the high-frequency vibrator to the control center of the high-fidelity pulse simulator;

[0045] Select the STM32F7 control chip, write the control program, and test and debug the control center of the high-fidelity pulse simulator;

[0046] Receiving pulse condition analog signal data, and using a low noise amplifier to preliminarily amplify the pulse condition analog signal data;

[0047] The low-frequency interference signal in the pulse simulation signal data is removed by a high-pass filter;

[0048] The high-frequency noise in the pulse simulation signal data is removed by a low-pass filter.

[0049] As a preferred solution of the pulse diagnosis device for real-time remote restoration of TCM pulse of the present invention, wherein: the pulse parameters are dynamically adjusted by using a high-frequency vibrator and a biosensor to generate a real pulse, the specific steps are as follows:

[0050] Select biosensors and install them in high-fidelity pulse simulators;

[0051] Collect user's finger pressure data and position data through biosensors;

[0052] The collected finger pressure data and position data are transmitted to the control center of the high-fidelity pulse simulator via a wireless network;

[0053] After receiving the finger pressure data and position data, the control center of the high-fidelity pulse simulator performs denoising on the finger pressure data and position data through Kalman filtering to extract the pressure size characteristics and position change characteristics therein;

[0054] According to the extracted pressure size characteristics and position change characteristics, the output power that needs to be adjusted for the high-frequency vibrator is calculated, and the expression is:

[0055]

[0056] Among them, P out is the output power of the high frequency vibrator, P in is the input power value, ΔP is the real-time feedback power error, P ref is the reference power, cos(θ) is the cosine value of the phase angle, and θ is the phase angle;

[0057] Adjust the output power of the high-frequency vibrator in real time according to the calculation results;

[0058] The high-frequency vibrator performs actual physical vibration output according to the adjusted power to generate a real pulse.

[0059] As a preferred solution of the pulse diagnosis device for real-time remote restoration of TCM pulse condition of the present invention, wherein: the linear regression model is selected to further adaptively calibrate the pulse condition simulation signal data, and the specific steps are as follows:

[0060] Select the linear regression model to extract pulse rate, pulse amplitude, pulse width and pulse type as key features from the pulse simulation signal data;

[0061] The original pulse simulation signal data is divided into a training set and a validation set;

[0062] Input the key features and the original pulse simulation signal data into the linear regression model for training;

[0063] During the training process, cross validation and grid search were used to optimize the linear regression model parameters;

[0064] Evaluate the performance of the linear regression model using the validation set;

[0065] The trained linear regression model is used as the self-calibration of the high-fidelity pulse simulator to dynamically adjust the power parameters in the high-fidelity pulse simulator.

[0066] As a preferred solution of the pulse diagnosis device for real-time remote restoration of TCM pulse condition of the present invention, the specific steps of making a diagnosis and proposing a treatment plan based on the restored real pulse condition are as follows:

[0067] According to the real pulse signal restored by the high-fidelity pulse simulator, the patient's pulse characteristic information is obtained;

[0068] Record the patient's pulse characteristics in the medical record;

[0069] Integrate the patient's pulse characteristic information to generate the patient's health record;

[0070] Comprehensive analysis of patients through imaging analysis tools;

[0071] Determine the patient's health status based on the analysis results;

[0072] Based on the analysis results, medication, physical therapy, diet adjustment and lifestyle are formulated as personalized treatment plans for patients.

[0073] The beneficial effects of the present invention are as follows: the present invention receives pulse simulation signal data through a high-fidelity pulse simulator, and dynamically adjusts the pulse simulation signal data parameters using a high-frequency vibrator and a biosensor, thereby realizing the simulation reproduction of a real pulse. The high-frequency vibrator accurately controls pulse characteristics, including pulse rate, pulse amplitude, pulse width, etc., while the biosensor collects finger pressure and position data in real time, and removes noise through Kalman filtering to ensure data accuracy. This design not only reproduces the physical characteristics of the pulse, but also dynamically reflects its changes, so that doctors can accurately perform pulse diagnosis and analysis. In a remote environment, doctors can feel the real pulse, which improves the accuracy and experience of diagnosis, enhances the standardization and popularization of traditional Chinese medicine diagnosis, and provides solid technical support for telemedicine. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0075] Figure 1 Schematic diagram of the pulse diagnosis device for real-time remote restoration of the TCM pulse condition in Example 1.

[0076] Figure 2 It is a schematic diagram of diagnosing and proposing treatment based on the real pulse in Example 1. DETAILED DESCRIPTION

[0077] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0078] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0079] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0080] Example 1, reference Figure 1 and Figure 2 , is the first embodiment of the present invention, which provides a pulse diagnosis device for real-time remote restoration of traditional Chinese medicine pulse, comprising the following steps:

[0081] The pulse analog signal data is collected synchronously through multiple channels, and the pulse analog signal data is input to the pulse processor for processing and conversion into digital pulse signal data.

[0082] Furthermore, the high-sensitivity pressure sensor of the multi-channel pulse collector is accurately aligned with the patient's three pulse positions of Cun, Guan and Chi to ensure that the sensor is close to the skin. In order to ensure the accuracy of the pulse simulation signal data, the sensor is fixed on the pulse position with a fixing belt;

[0083] The Cun pulse is located on the inner side of the wrist near the thumb and is mainly used to detect cardiopulmonary function;

[0084] Guan pulse is located below Cun pulse, in the middle of the wrist, and is mainly used to detect liver and spleen function;

[0085] The Chi pulse is located below the Guan pulse, close to the little finger side of the wrist, and is mainly used to detect kidney function;

[0086] Start the pulse simulation signal data acquisition equipment, and the equipment automatically adjusts the initial pressure of each sensor;

[0087] Prepare to start collecting pulse analog signal data of each pulse position in real time (including pulse rate, pulse amplitude, pulse width, pulse type, pulse pressure, pulse position, pulse variation value and pulse spectrum). Each sensor adjusts the pressure in real time through a micro feedback device to ensure the accuracy of the collected signal;

[0088] Pulse rate reflects the frequency of heartbeats and is usually expressed in beats per minute (BPM);

[0089] Pulse amplitude reflects the strength of the pulse or the magnitude of pressure changes, reflecting the force of blood flow;

[0090] Pulse width reflects the duration of a single pulse, reflecting the width or duration of the pulse;

[0091] The pulse type reflects the shape of the pulse waveform, including the rise time, fall time and peak time, reflecting the specific morphological characteristics of the pulse;

[0092] Pulse pressure reflects the difference between systolic and diastolic pressures, reflecting the changes in blood pressure during one heartbeat cycle;

[0093] The pulse position reflects the pulse signals collected at different pulse positions (such as Cun pulse, Guan pulse, and Chi pulse), reflecting the pulse characteristics of different pulse positions;

[0094] The pulse variation value reflects the changing rules and fluctuations of the pulse signal, including periodic changes and irregular fluctuations;

[0095] The pulse spectrum reflects the frequency domain characteristics of the pulse signal through spectrum analysis methods such as Fourier transform, reflecting the frequency components and energy distribution of the pulse signal;

[0096] The collected pulse analog signal data is input into the pulse processor and amplified by a low noise amplifier to ensure that the signal strength is sufficient for subsequent processing;

[0097] The amplified pulse analog signal data is filtered through an analog filter to eliminate high-frequency noise and low-frequency interference to ensure the purity of the signal;

[0098] A high-pass filter removes low-frequency interference signals (such as baseline drift);

[0099] A low-pass filter removes high-frequency noise (such as power supply noise);

[0100] Performing multi-band decomposition on the filtered pulse condition simulation signal data, and dividing the pulse condition simulation signal data into low-frequency signal data, intermediate-frequency signal data and high-frequency signal data;

[0101] The low-frequency signal data, the intermediate-frequency signal data and the high-frequency signal data are enhanced by a multi-band gain control algorithm to improve the overall quality and accuracy of the pulse simulation signal data;

[0102] Enhance low-frequency signal data to reduce the impact of low-frequency interference and baseline drift;

[0103] Enhance the intermediate frequency signal data to improve the accuracy and detail of the signal;

[0104] Enhance high-frequency signal data to reduce the interference of high-frequency noise on the signal;

[0105] Combined with the pulse characteristic database, multi-band compensation is performed on the enhanced low-frequency signal data, medium-frequency signal data and high-frequency signal data to correct possible minor errors. The compensation algorithm makes subtle adjustments to the signals of each frequency band based on the existing pulse characteristic information in the pulse characteristic database to ensure the accuracy of the signal.

[0106] Perform baseline drift compensation on the enhanced low-frequency signal data to ensure signal stability;

[0107] Perform characteristic amplitude compensation on the enhanced intermediate frequency signal data to enhance the characteristic performance of the signal;

[0108] Perform noise compensation on the enhanced high-frequency signal data to further eliminate residual noise;

[0109] According to the compensated multi-band signal data, the errors (including acquisition error, amplifier error, filtering error, frequency division and enhancement error, and baseline drift and noise error) existing in the pulse simulation signal data are corrected;

[0110] When the sensor collects pulse signals, it may be affected by ambient temperature, humidity or electromagnetic interference. The signal deviation caused by these factors is usually a small error. For example, the output signal of the sensor may be interfered with at the microvolt level.

[0111] Low noise amplifiers may introduce gain errors or noise during signal amplification. These errors are usually in the microvolt to millivolt level. For example, the gain stability of the amplifier may cause a small change in the signal amplitude.

[0112] When processing signals, analog filters may introduce phase errors or amplitude attenuation. These errors are usually in the range of a few percent. For example, the filter may produce a slight attenuation on signals in certain frequency bands.

[0113] In the process of multi-band decomposition and gain control, the algorithm may introduce small calculation errors or approximation errors, which are usually in the order of magnitude. For example, incomplete frequency separation in multi-band processing may lead to small deviations in amplitude.

[0114] Baseline drift of low-frequency signals and noise interference of high-frequency signals are also typical sources of small errors. These errors may be caused by physiological jitter or equipment noise, usually at the microvolt to millivolt level;

[0115] Select a high-precision analog-to-digital converter (ADC), such as a 24-bit Σ-Δ ADC, to ensure the accuracy of signal conversion. Input the pulse analog signal after multi-band compensation into the high-precision analog-to-digital converter and convert it into digital pulse signal data. The expression is:

[0116]

[0117] Where D is the converted digital pulse signal data, V in is the input pulse simulation signal voltage value, in is the input symbol, which identifies the input value of the variable, V ref+ is the positive terminal value of the reference voltage, V ref- is the negative terminal value of the reference voltage, ref is the reference value, representing a benchmark or reference value, used as a standard for comparison, n is the resolution of the high-precision analog-to-digital converter (e.g., 24 bits), and V is the voltage;

[0118] The formula converts the input pulse analog signal voltage value into digital pulse signal data, ensures the accuracy of the conversion through the positive end value and the negative end value of the reference voltage, and utilizes the number of bits of a high-precision analog-to-digital converter (ADC) to improve the resolution, ensure the accurate collection and processing of the pulse analog signal data, realize the accurate conversion of the signal from analog to digital, and improve the overall reliability and accuracy.

[0119] Calibrate the converted digital pulse signal data to eliminate errors and deviations in the conversion process;

[0120] Specifically,

[0121] In the absence of pulse signal input, record the output of the high-precision analog-to-digital converter and set the baseline value;

[0122] Input a known signal (such as a standard sine wave) and adjust the gain parameter of the high-precision analog-to-digital converter so that its output signal is consistent with the expected value of the input signal;

[0123] In the signal acquisition environment, record the noise value when there is no signal input and deduct it from the actual signal;

[0124] After the calibration is completed, the digital pulse signal data of different pulse parameters (such as pulse rate, pulse amplitude, etc.) are separated and stored in different registers of the pulse processor for subsequent processing and analysis;

[0125] It should be noted that the accuracy of pulse analog signal data acquisition is ensured by synchronously collecting pulse analog signal data through multiple channels and using high-sensitivity pressure sensors to accurately locate the pulse position. The signal is amplified by a low-noise amplifier to eliminate high-frequency noise and low-frequency interference. Combined with multi-band gain control and compensation technology, the signal is further enhanced and corrected to ensure signal purity and stability. A high-precision analog-to-digital converter is used to convert the compensated pulse analog signal data into digital pulse signal data, which improves the resolution and accuracy of the signal. The combination of these technical measures effectively improves the overall quality and accuracy, ensures the reliability of pulse analog signal data in remote diagnosis, and provides a solid foundation for high-precision pulse simulation and diagnosis.

[0126] The digital pulse signal data is compressed and encrypted, and the encrypted and compressed digital pulse signal data is transmitted to the remote diagnosis equipment in real time using an adaptive algorithm.

[0127] Further, the digital pulse signal data after the conversion is divided into a plurality of digital pulse signal data segments (for example, each data segment 1KB) according to a certain size;

[0128] Add sequence sorting to each digital pulse signal data segment, the sequence sorting includes the sequence number of the digital pulse signal data segment, the total number of data segments, the check code, etc., to ensure that the digital pulse signal data can be correctly identified and reorganized during the transmission process, and the sorted digital pulse signal data segment is compressed by the LZ77 algorithm to reduce the digital pulse signal data volume and transmission time, and generate a digital pulse signal data packet;

[0129] The compressed digital pulse signal data packet is encrypted with AES to ensure the security and integrity of the digital pulse signal data transmission. An adaptive transmission algorithm is used to monitor the network environment (including bandwidth, delay, packet loss rate, etc.). According to the real-time network bandwidth, the transmission rate of the digital pulse signal data packet is adjusted. The adaptive transmission algorithm can dynamically adjust transmission parameters, such as the size of the digital pulse signal data packet, the transmission interval, the retransmission strategy, etc. For example, when the network condition is good, the digital pulse signal data packet size and the transmission rate can be increased; when the network condition is poor, the digital pulse signal data packet size is reduced and the number of retransmissions is increased;

[0130] Send the encrypted and compressed digital pulse signal data packet to the remote diagnosis equipment via a wireless network (such as Wi-Fi, 4G / 5G);

[0131] The communication equipment (including the whole of the acquisition, processing, transmission and reception equipment) establishes a secure connection with the remote diagnosis equipment (such as using the TLS protocol for encrypted connection);

[0132] Send each encrypted digital pulse signal data packet in sequence and monitor the transmission status in real time;

[0133] During the transmission of the digital pulse signal data packet, a CRC check is used to detect whether the digital pulse signal data packet is correct;

[0134] If a digital pulse signal data packet error is detected, the adaptive transmission algorithm will trigger a retransmission mechanism to retransmit the erroneous digital pulse signal data packet until the transmission is successful;

[0135] It should be noted that by compressing and encrypting the digital pulse signal data and using an adaptive algorithm for real-time transmission, the efficiency and security of the digital pulse signal data transmission are ensured. The digital pulse signal data segmentation and sequence sorting ensure the correct identification and reorganization of the digital pulse signal data during data transmission. The LZ77 algorithm compression reduces the amount of digital pulse signal data and transmission time. AES encryption ensures the security of the digital pulse signal data. The adaptive transmission algorithm dynamically adjusts the transmission parameters according to the network conditions, optimizes the transmission rate and the size of the digital pulse signal data packet, and uses the CRC check and retransmission mechanism to ensure the integrity and accuracy of the digital pulse signal data, thereby realizing reliable data reception and efficient communication of remote diagnostic equipment.

[0136] The remote diagnosis equipment receives and decrypts the digital pulse signal data, and converts the digital pulse signal data back into pulse analog signal data.

[0137] Furthermore, after receiving the digital pulse signal data packet, the remote diagnosis equipment reorganizes it according to the sequence number. Even if the digital pulse signal data packet has been sorted and compressed at the transmitting end, the digital pulse signal data packet may be reordered or damaged during the network transmission process. Therefore, when the remote equipment receives the digital pulse signal data, it needs to reorganize it according to the sequence number to ensure the integrity and order of the digital pulse signal data.

[0138] Perform AES decryption on the reorganized digital pulse signal data packet to restore the original compressed digital pulse signal data packet;

[0139] The decrypted original compressed digital pulse signal data packet is decompressed by LZ77 algorithm to restore the original digital pulse signal data;

[0140] Verify the restored original digital pulse signal data segment to ensure the integrity and accuracy of the digital pulse signal data;

[0141] The decompressed digital pulse signal data is input into a high-precision digital-to-analog converter (D / A) to ensure that its resolution and sampling rate are suitable for the characteristics of the analog signal that needs to be restored;

[0142] The high-precision digital-to-analog converter converts the digital pulse signal data back to the pulse analog signal data, and the expression is:

[0143] V out (t)=(V d (t)-∈·sin(ωt))×(1+α·e -γt );

[0144] Among them, V out (t) is the output pulse analog signal voltage data value that changes with time. The voltage signal restored by high-precision digital-to-analog converter (D / A conversion) represents the processed pulse analog signal voltage data value. Out is the output symbol used to identify the output value of the variable. V d (t) is the input digital pulse signal voltage data value that changes with time. It is a voltage signal after conversion by a high-precision analog-to-digital converter (ADC), expressed in digital form, and is the voltage representation of the pulse analog signal data in the digital domain. d is the index of the digital pulse signal, which is used to distinguish the digital pulse signal from other types of signals. Specifically, it identifies the input digital pulse signal voltage value. ∈ is the noise correction term of the digital pulse signal, which is used to correct the digital pulse signal error caused by noise. sin is a sine function, which is used to describe the fluctuation of periodic signals. ω is the angular frequency of the digital pulse signal. α is an adaptive correction coefficient, which is used to dynamically adjust the amplitude of the pulse analog signal to adapt to different environments and situations. γ is a time constant, which controls the rate of exponential decay. e is the base of the natural logarithm (approximately equal to 2.71828), which is used to describe the change of the exponential function. t is a time variable, which is used to describe the change of the pulse analog signal data over time.

[0145] This formula dynamically adjusts the output voltage, corrects the noise and frequency change of the pulse simulation signal data, ensures the purity and accuracy of the pulse simulation signal data, combines the characteristics of sine wave and exponential decay, provides accurate simulation of the pulse simulation signal data, and enhances the accuracy and effect of diagnosis;

[0146] It should be noted that by receiving and decrypting the digital pulse signal data through the remote diagnosis equipment, and then converting it back into pulse analog signal data, complete restoration is achieved. The remote diagnosis equipment reorganizes the digital pulse signal data packets according to the serial number to ensure the order and integrity of the digital pulse signal data, and decompresses it through AES decryption and LZ77 algorithm to restore the original digital pulse signal data. Subsequently, the digital pulse signal data is converted back into pulse analog signal data through a high-precision digital-to-analog converter and verified to ensure the accuracy of the pulse analog signal data. This process ensures the security and integrity of the digital pulse signal data during remote transmission, while accurately restoring the pulse analog signal data, enabling doctors to obtain reliable diagnostic information and improving the effectiveness and reliability of telemedicine.

[0147] Build a high-fidelity pulse simulator, receive pulse simulation signal data, use high-frequency vibrators and biosensors to dynamically adjust parameters, and generate a real pulse.

[0148] Furthermore, a high-frequency vibrator is selected and installed in a high-fidelity pulse simulator, and it is ensured to be stable to avoid vibrations generated during operation affecting the measurement accuracy;

[0149] Connect the high-frequency vibrator to the control center of the high-fidelity pulse simulator to ensure the stability and reliability of signal transmission;

[0150] Select the STM32F7 (STMicroelectronics) control chip, which has fast processing capabilities and low power consumption. Write the control program to ensure that it can receive input signals and control the output of the electromagnetic vibration device. Test and debug the control center of the high-fidelity pulse simulator to ensure that the control program can accurately control the output of the electromagnetic vibration device.

[0151] Receive pulse analog signal data, and use a low-noise amplifier to preliminarily amplify the pulse analog signal data to ensure that the signal strength is sufficient for subsequent processing;

[0152] The low-frequency interference signal (such as baseline drift) in the pulse simulation signal data is removed by a high-pass filter to ensure the purity of the signal;

[0153] The high-frequency noise (such as power supply noise) in the pulse simulation signal data is removed by a low-pass filter to ensure the stability of the signal;

[0154] Select biosensors and install them in high-fidelity pulse simulators;

[0155] Collect user's finger pressure data and position data through biosensors;

[0156] According to the structure of the high-fidelity pulse simulator, determine the best installation position of the biosensor to ensure that it covers the key areas for the doctor's palpation;

[0157] Install the biosensor firmly in the designated location, arrange the biosensor's connecting wires neatly, and connect them to the data acquisition center to ensure the stability of signal transmission;

[0158] The collected finger pressure data and position data are transmitted to the control center of the high-fidelity pulse simulator via a wireless network;

[0159] After receiving the finger pressure data and position data, the control center of the high-fidelity pulse simulator performs denoising on the finger pressure data and position data through Kalman filtering to ensure the accuracy of the data and extract the pressure size characteristics and position change characteristics;

[0160] According to the extracted pressure size characteristics and position change characteristics, the output power that needs to be adjusted for the high-frequency vibrator is calculated, and the expression is:

[0161]

[0162] Among them, P out is the output power of the high-frequency vibrator, which is the final output power applied by the high-frequency vibrator and is used to simulate the physical manifestation of the pulse. in is the input power value, which is the initial power signal entering the high-frequency vibrator and serves as the basis for the high-frequency vibrator output. ΔP is the real-time feedback power error, which represents the difference between the actual detected pressure and the preset reference pressure. It is measured through real-time feedback and is used to adjust the output power to achieve a more accurate simulation effect. P ref is the reference power, which is a preset reference pressure value. It is used as a comparison benchmark to evaluate the deviation between the actual pressure and the expected pressure. cos(θ) is the cosine value of the phase angle, and θ is the phase angle. The phase angle θ determines the direction and amplitude of the pressure adjustment. Through the cosine function adjustment, the adjusted power output is smoother and more accurate. The value range of the cosine function is between -1 and 1, so the output power can be adjusted positively or negatively.

[0163] This formula ensures the accuracy of pulse simulation by dynamically adjusting the output power of the high-frequency vibrator, enhances the accuracy and effect of diagnosis, realizes high-fidelity reproduction of pulse signals, and improves the accuracy and reliability of remote diagnosis.

[0164] According to the calculation results, the output power of the high-frequency vibrator is adjusted in real time to ensure that the vibration frequency and amplitude of the vibrator accurately reflect the input pulse signal;

[0165] The high-frequency vibrator performs actual physical vibration output according to the adjusted power to generate a real pulse;

[0166] Specifically, the high-frequency vibrator performs physical vibration output according to the adjusted parameters;

[0167] Monitor the effect of vibration output in real time and ensure that the output is consistent with the input signal through biosensor feedback;

[0168] Doctors can feel the restored pulse signal through the high-fidelity pulse simulator and make detailed diagnosis;

[0169] It should be noted that by constructing a high-fidelity pulse simulator, receiving pulse simulation signal data, and using high-frequency vibrators and biosensors to dynamically adjust the pulse simulation signal data parameters, a highly simulated reproduction of the real pulse is achieved. High-frequency vibrators and biosensors accurately control the pulse simulation signal data parameters to ensure the authenticity and stability of the pulse simulation signal data. Kalman filtering technology further ensures the purity and accuracy of the pulse simulation signal data, enabling doctors to accurately perceive and diagnose the pulse in a remote environment, significantly improving the accuracy and effectiveness of the diagnosis, while enhancing the standardization and application breadth of remote Chinese medicine diagnosis and treatment.

[0170] A linear regression model is selected to further adaptively calibrate the pulse simulation signal data, and a diagnosis is made and a treatment plan is proposed based on the restored real pulse.

[0171] Furthermore, a linear regression model is selected to extract pulse rate, pulse amplitude, pulse width and pulse type as key features from the pulse simulation signal data;

[0172] Pulse rate reflects the frequency of heartbeats, usually expressed in beats per minute (BPM). It is one of the most intuitive and basic pulse characteristics, which can reflect the health status of the heart and the rhythm of the heart rate.

[0173] Pulse amplitude reflects the strength of the pulse or the amplitude of pressure changes, which can describe the strength of blood flow. The change of pulse amplitude can indicate important physiological information such as cardiac output and vascular elasticity.

[0174] Pulse width reflects the duration of a single pulse, that is, the width or duration of the pulse. The measurement of pulse width can reflect the contraction and relaxation time of the heart and provide detailed information about heart function.

[0175] The pulse pattern reflects the shape of the pulse waveform, including the rise time, fall time, and peak time. The specific morphological characteristics of the pulse pattern can reveal the hemodynamic status and vascular health status;

[0176] These characteristics (pulse rate, pulse amplitude, pulse width and pulse type) can fully and accurately reflect the main physiological information of pulse signals and provide a multifaceted perspective on the function of the cardiovascular system;

[0177] Through these characteristics (pulse rate, pulse amplitude, pulse width and pulse shape), it is possible to ensure that the main information in the pulse signal is captured and reduce the noise and errors that may occur in signal processing;

[0178] The original pulse simulation signal data was divided into a training set (80%) and a validation set (20%);

[0179] Input the key features and the original pulse simulation signal data into the linear regression model for training;

[0180] During the training process, cross validation and grid search are used to optimize the linear regression model parameters to ensure the accuracy and generalization ability of the linear regression model;

[0181] The difference between the predicted value and the true value is measured by the mean square error;

[0182] Evaluate the stability and generalization ability of the model by splitting the validation set data multiple times through cross-validation;

[0183] Evaluate the performance of the linear regression model through the validation set to ensure that it can maintain high accuracy in different environments and conditions;

[0184] The trained linear regression model is used as the self-calibration of the high-fidelity pulse simulator, and the feedback is analyzed in real time to dynamically adjust the parameters in the high-fidelity pulse simulator to optimize the output signal.

[0185] According to the real pulse signal restored by the high-fidelity pulse simulator, the patient's pulse characteristic information, such as pulse rate, pulse amplitude, pulse width, pulse type, etc., is obtained;

[0186] Record the patient's pulse characteristics in the medical record as a basis for comprehensive analysis;

[0187] Integrate the patient's pulse characteristic information to generate the patient's health record;

[0188] Comprehensively analyze patients through imaging analysis tools (such as X-ray, CT, MRI, etc.);

[0189] Determine the patient's health status based on the analysis results;

[0190] Based on the analysis results, develop medication, physical therapy, diet adjustment and lifestyle as a personalized treatment plan for the patient;

[0191] It should be noted that by selecting a linear regression model to adaptively calibrate the pulse simulation signal data, high accuracy and generalization ability of pulse simulation signal data analysis are achieved. Extract key features and divide the pulse simulation signal data into training sets and validation sets to ensure that the model maintains high accuracy under different conditions. The trained model adjusts the parameters of the high-fidelity pulse simulator in real time to optimize the output pulse simulation signal data. Doctors obtain the patient's pulse characteristic information based on the restored pulse simulation signal data, record it in the medical record, and formulate personalized treatment plans based on the results of imaging analysis, ultimately improving the accuracy and effectiveness of remote diagnosis and treatment and improving the patient's health management level.

[0192] In summary, the present invention receives pulse simulation signal data through a high-fidelity pulse simulator, and dynamically adjusts the pulse simulation signal data parameters using a high-frequency vibrator and a biosensor, thereby realizing the simulation reproduction of a real pulse. The high-frequency vibrator accurately controls the pulse characteristics, including pulse rate, pulse amplitude, pulse width, etc., while the biosensor collects finger pressure and position data in real time, and removes noise through Kalman filtering to ensure data accuracy. This design not only reproduces the physical characteristics of the pulse, but also dynamically reflects its changes, enabling doctors to accurately perform pulse diagnosis and analysis. In a remote environment, doctors can feel the real pulse, which improves the accuracy and experience of diagnosis, enhances the standardization and popularization of traditional Chinese medicine diagnosis, and provides solid technical support for telemedicine.

[0193] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A pulse diagnosis device for real-time remote restoration of traditional Chinese medicine pulse, characterized in that: include, The collecting module is used for synchronously collecting pulse analog signal data through multiple channels, inputting the pulse analog signal data into the pulse processor for processing and converting into digital pulse signal data; The transmission module is used to compress and encrypt the digital pulse signal data, and transmit the encrypted and compressed digital pulse signal data to the remote diagnosis equipment in real time using an adaptive algorithm; A conversion module, used for remote diagnosis equipment to receive and decrypt digital pulse signal data, and convert the digital pulse signal data back to pulse analog signal data; A building module is used to build a high-fidelity pulse simulator, receive pulse simulation signal data, dynamically adjust pulse parameters using a high-frequency vibrator and a biosensor, and generate a real pulse; The diagnosis module is used to select a linear regression model to further adaptively calibrate the pulse simulation signal data, and to diagnose and propose a treatment plan based on the restored real pulse.

2. The pulse diagnosis device for real-time remote restoration of TCM pulse according to claim 1, characterized in that: The multiple channels include Cun pulse, Guan pulse and Chi pulse.

3. The pulse diagnosis device for real-time remote restoration of TCM pulse according to claim 2, characterized in that: The pulse simulation signal data includes pulse rate, pulse amplitude, pulse width, pulse type, pulse pressure, pulse position, pulse variation value and pulse spectrum.

4. The pulse diagnosis device for real-time remote restoration of TCM pulse according to claim 3, characterized in that: The pulse analog signal data is input to the pulse processor for processing and converted into digital pulse signal data, and the specific steps are: The collected pulse analog signal data is input into the pulse processor and amplified by a low noise amplifier; The amplified pulse analog signal data is filtered through an analog filter; The pulse condition analog signal data after filtering is divided into low-frequency signal data, medium-frequency signal data and high-frequency signal data; The low-frequency signal data, the intermediate-frequency signal data and the high-frequency signal data are enhanced by a multi-band gain control algorithm; Performing baseline drift compensation on the enhanced low-frequency signal data; Performing characteristic amplitude compensation on the enhanced intermediate frequency signal data; Performing noise compensation on the enhanced high-frequency signal data; Correcting the error in the pulse simulation signal data according to the compensated multi-band signal data; Select a high-precision analog-to-digital converter, input the pulse analog signal after multi-band compensation into the high-precision analog-to-digital converter, and convert it into digital pulse signal data. The expression is: Where D is the converted digital pulse signal data, V in is the input pulse analog signal voltage value, in is the input symbol, V ref+ is the positive terminal value of the reference voltage, V ref- is the negative terminal value of the reference voltage, ref is the reference value, n is the resolution of the high-precision analog-to-digital converter, and V is the voltage.

5. The pulse diagnosis device for real-time remote restoration of TCM pulse according to claim 4, characterized in that: The digital pulse signal data is compressed and encrypted, and the encrypted and compressed digital pulse signal data is transmitted to the remote diagnosis equipment in real time using an adaptive algorithm. The specific steps are: The converted digital pulse signal data is divided into a plurality of digital pulse signal data segments according to size; Add sequence sorting to each digital pulse signal data segment, and compress the sorted digital pulse signal data segment through LZ77 algorithm to generate a digital pulse signal data packet; The compressed digital pulse signal data packet is encrypted by AES, and the network environment is monitored by an adaptive transmission algorithm, and the sending rate of the digital pulse signal data packet is adjusted according to the real-time network bandwidth; Sending the encrypted and compressed digital pulse signal data packet to the remote diagnosis equipment via a wireless network; During the transmission of the digital pulse signal data packet, a CRC check is used to detect whether the digital pulse signal data packet is correct; If a digital pulse signal data packet error is detected, the adaptive transmission algorithm triggers a retransmission mechanism to retransmit the erroneous digital pulse signal data packet until the transmission is successful.

6. The pulse diagnosis device for real-time remote restoration of TCM pulse according to claim 5, characterized in that: The remote diagnosis equipment receives and decrypts the digital pulse signal data, and converts the digital pulse signal data back into pulse analog signal data; After receiving the digital pulse signal data packet, the remote diagnosis equipment reassembles it according to the sequence number; Perform AES decryption on the reorganized digital pulse signal data packet; The decrypted original compressed digital pulse signal data packet is decompressed by LZ77 algorithm; Input the decompressed digital pulse signal data into a high-precision digital-to-analog converter; The high-precision digital-to-analog converter converts the digital pulse signal data back to the pulse analog signal data, and the expression is: V out (t)=(V d (t)-∈·sin(ωt))×(1+α·e -γt ); Among them, V out (t) is the output pulse analog signal voltage data value that changes with time, out is the output symbol, V d (t) is the input digital pulse signal voltage data value that changes with time, d is the index of the digital pulse signal, ∈ is the noise correction term of the digital pulse signal, ω is the angular frequency of the digital pulse signal, α is the adaptive correction coefficient, γ is the time constant, e is the base of the natural logarithm, and t is the time variable.

7. The pulse diagnosis device for real-time remote restoration of TCM pulse according to claim 6, characterized in that: The high-fidelity pulse simulator is constructed to receive pulse simulation signal data, and the specific steps are: Select a high-frequency vibrator and install it in a high-fidelity pulse simulator; Connect the high-frequency vibrator to the control center of the high-fidelity pulse simulator; Select the STM32F7 control chip, write the control program, and test and debug the control center of the high-fidelity pulse simulator; Receiving pulse condition analog signal data, and using a low noise amplifier to preliminarily amplify the pulse condition analog signal data; The low-frequency interference signal in the pulse simulation signal data is removed by a high-pass filter; The high-frequency noise in the pulse simulation signal data is removed by a low-pass filter.

8. The pulse diagnosis device for real-time remote restoration of TCM pulse according to claim 7, characterized in that: The high-frequency vibrator and the biosensor are used to dynamically adjust the pulse parameters to generate a real pulse. The specific steps are: Select biosensors and install them in high-fidelity pulse simulators; Collect user's finger pressure data and position data through biosensors; The collected finger pressure data and position data are transmitted to the control center of the high-fidelity pulse simulator via a wireless network; After receiving the finger pressure data and position data, the control center of the high-fidelity pulse simulator performs denoising on the finger pressure data and position data through Kalman filtering to extract the pressure size characteristics and position change characteristics therein; According to the extracted pressure size characteristics and position change characteristics, the output power that needs to be adjusted for the high-frequency vibrator is calculated, and the expression is: Among them, P out is the output power of the high frequency vibrator, P in is the input power value, ΔP is the real-time feedback power error, P ref is the reference power, cos(θ) is the cosine value of the phase angle, and θ is the phase angle; Adjust the output power of the high-frequency vibrator in real time according to the calculation results; The high-frequency vibrator performs actual physical vibration output according to the adjusted power to generate a real pulse.

9. The pulse diagnosis device for real-time remote restoration of TCM pulse according to claim 8, characterized in that: The described selection linear regression model further self-adaptively calibrates the pulse simulation signal data, and the specific steps are: Select the linear regression model to extract pulse rate, pulse amplitude, pulse width and pulse type as key features from the pulse simulation signal data; The original pulse simulation signal data is divided into a training set and a validation set; Input the key features and the original pulse simulation signal data into the linear regression model for training; During the training process, cross validation and grid search were used to optimize the linear regression model parameters; Evaluate the performance of the linear regression model using the validation set; The trained linear regression model is used as the self-calibration of the high-fidelity pulse simulator to dynamically adjust the power parameters in the high-fidelity pulse simulator.

10. The pulse diagnosis device for real-time remote restoration of TCM pulse condition as claimed in claim 9, characterized in that: The specific steps of diagnosing and proposing a treatment plan based on the restored real pulse are as follows: According to the real pulse signal restored by the high-fidelity pulse simulator, the patient's pulse characteristic information is obtained; Record the patient's pulse characteristics in the medical record; Integrate the patient's pulse characteristic information to generate the patient's health record; Comprehensive analysis of patients through imaging analysis tools; Determine the patient's health status based on the analysis results; Based on the analysis results, medication, physical therapy, diet adjustment and lifestyle are formulated as personalized treatment plans for patients.

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