Traditional Chinese medicine auscultation and diagnosis intelligent health management system based on AI large model

Abstract

The invention discloses a traditional Chinese medicine auscultation and diagnosis intelligent health management system based on an AI large model. Relates to the technical field of traditional Chinese medicine five-tone auditory function modules of healthy traditional Chinese medicine auscultation and diagnosis data. Health data is normalized by comprehensively analyzing the recent transmission state of healthy traditional Chinese medicine five-tone data transmitted to an AI traditional Chinese medicine large model server and the AI traditional Chinese medicine large model server to process the healthy traditional Chinese medicine five-tone data; calculating to obtain an available evaluation coefficient of AI traditional Chinese medicine large model service health traditional Chinese medicine five-tone value data; comparing characteristic value scores of Mel frequency cepstral coefficients, pitches, volumes, rhythms, frequencies, tones and timbres of five voices of the traditional Chinese medicine of the AI traditional Chinese medicine large model service health data; a method in the technical field of health data traditional Chinese medicine five-tone auditory function modules is put forward and combined with AI traditional Chinese medicine large model analysis; according to the system, the advanced AI technology and the traditional Chinese medicine theory are integrated, and evaluation of the health state of the user and traditional Chinese medicine health management service are achieved.

Description

Technical Field

[0001] The present invention relates to the field of auditory function data modules of the five tones of traditional Chinese medicine, and more specifically, to an intelligent management system for health management data based on personalized calculation of traditional Chinese medicine olfactory diagnosis based on an AI big model. Background Art

[0002] Health data is raw, unprocessed medical and health information, while health management data is data that has been processed, analyzed, and managed to achieve more specific goals; health TCM Five Tone Filling Management data usually involves the use of technologies such as the AI ​​TCM Five Tone Big Model to provide better individual health management support and decision-making through the health TCM Five Tone Filling Value Management data; There is currently real-time monitoring of healthy TCM five tones through human audio. The auditory function data module of TCM five tones includes the Mel-frequency cepstral coefficient (MFCC) module of the five-tone audio signal and the pitch module; volume module; rhythm module; frequency module, tone feature (such as pitch, scale) module, timbre feature (such as sound quality, timbre type) module. After the auditory function data module of the healthy TCM five tones monitored by the health monitoring audio device is sent to the AI ​​TCM big model for TCM five-tone analysis and evaluation of health management data by the AI ​​big model, the personalized health management data is stored on the server, and the health monitoring device or other user terminals connected to the TCM five-tone server of the AI ​​big model can push individual healthy TCM five-tone filling value management data in real time based on the data of the TCM five-tone server of the AI ​​big model, so that users can understand the physical health TCM five-tone filling value evaluation data in real time and obtain life, exercise and psychological adjustment methods.

[0003] The prior art has the following deficiencies: There may be failure problems in the data transmission between the health audio monitoring device and the AI ​​large model of Traditional Chinese Medicine Five Tone Server. At present, the alarm of the failure of the health monitoring device and the AI ​​large model of Traditional Chinese Medicine Five Tone Server is usually after the health monitoring device has failed with the AI ​​large model of Traditional Chinese Medicine Five Tone Server. There is no advance prompt of the status of the data transmission between the health audio monitoring device and the AI ​​large model of Traditional Chinese Medicine Five Tone Server, which will result in the failure to switch to the backup AI large model of Traditional Chinese Medicine Five Tone Server in time. As a result, when the data transmission between the health audio monitoring device and the AI ​​large model of Traditional Chinese Medicine Five Tone Server fails, the user's health data cannot be processed in time by the AI ​​large model of Traditional Chinese Medicine Server to generate health management data, resulting in untimely health audio monitoring of the user, which in turn causes the user to be unable to understand their health status in time and miss early signs of health problems, which may lead to untimely adjustment of life, exercise, and psychology.

[0004] In order to solve the above problems, a technical solution is now provided; Invention content In order to overcome the above defects of the prior art, the embodiments of the present invention provide a Chinese medicine five-tone filling health intelligent management system based on an AI big model to solve the problems raised in the above background technology; To achieve the above purposes, the present invention provides the following. Summary of the invention

[0005] Based on the AI ​​big model, the TCM five-tone auditory function module includes the Mel-frequency cepstral coefficient (MFCC) module of the five-tone audio signal and the pitch module; volume module; rhythm module; frequency module, tone feature (such as pitch, scale) module, timbre feature (such as sound quality, timbre type) module, The auditory function data module technology of the five tones of traditional Chinese medicine is as follows: 1. The Mel Frequency Cepstral Coefficient (MFCC) module of the five-tone audio signal has a close relationship with the timbre, emotion and health of the audio signal of the five tones of traditional Chinese medicine (gong, shang, jiao, zhi and yu). MFCC can help us extract the features of these audio signals and analyze their corresponding relationship with the five tones; Timbre characteristics: MFCC can capture the timbre characteristics of audio signals, which is very important for identifying different sound types; The different timbres of the five tones of traditional Chinese medicine can be distinguished by MFCC; Emotional analysis: By analyzing MFCC features, we can study the impact of different five tones on emotions; Demonstrate how to use the librosa library to extract MFCC features of audio signals and associate them with the five tones of traditional Chinese medicine; import numpy as np import librosa import matplotlib.pyplot as plt import librosa.display # Load audio file file_path = 'your_audio_file.wav' # Replace with your audio file path y, sr = librosa.load(file_path, sr=None) # Extract MFCC features mfccs = librosa.feature.mfcc(y=y, sr=sr, n_mfcc=13) # Calculate the average value of MFCC mean_mfccs = np.mean(mfccs, axis = 1) # Plot MFCC features plt.figure(figsize=(12, 6)) librosa.display.specshow(mfccs, sr = sr, x_axis='time', y_axis='mel', fmax = 8000) plt.colorbar() plt.title('MFCC') plt.tight_layout() plt.show() # MFCC features of the five traditional Chinese medicine tones (example) five_sounds = { "Gong tone": {"Timbre features": "Warm, bright"}, "Shang tone": {"Timbre features": "Soft, mellow"}, "Jue tone": {"Timbre features": "激昂, clear"}, "Zhi tone": {"Timbre features": "Bright, clear"}, "Yu tone": {"Timbre features": "Deep, rich"} } # Print the timbre features of the five tones for sound, features in five_sounds.items(): print(f"{sound}: {features['Timbre features']}") # Print the MFCC mean value print("Mean MFCCs:", mean_mfccs) Mel-frequency cepstral coefficients (MFCCs) are a powerful feature extraction tool in audio signal processing, capable of effectively capturing the timbre and sound quality features of audio signals; in the theory of the five traditional Chinese medicine tones, MFCCs can help us analyze the characteristics of different audio signals and understand their effects on emotions and health. Through the extraction and analysis of MFCCs; Based on the results output by the AI-based five-tone model of traditional Chinese medicine, the fullness range of the five traditional Chinese medicine tones is obtained, the state of the fullness value of healthy traditional Chinese medicine tones is judged, possible conditioning suggestions are provided, the fullness value of the five traditional Chinese medicine tones is determined, and the comprehensive fullness value of the five traditional Chinese medicine tones is evaluated to formulate personalized health indicators for the five traditional Chinese medicine tones.

[0006] 2. The pitch module's method for the auditory function data module of the five traditional Chinese tones includes the following steps: Obtain the intelligent human body audio data of the five traditional Chinese tones being full; According to the obtained data, compile a function to evaluate the range of the five traditional Chinese tones being full for the state of the auditory function module of the five traditional Chinese tones and judge the state function of the healthy value of the five traditional Chinese tones being full: How to use the matplotlib library to plot the pitch corresponding to the five tones; import numpy as np import matplotlib.pyplot as plt # Define the five tones and their corresponding frequencies notes = ['Gong tone (Do)', 'Shang tone (Re)', 'Jue tone (Mi)', 'Zhi tone (Fa)', 'Yu tone (Sol)'] frequencies = [261.63, 293.66, 329.63, 349.23, 392.00] # Hz # Plot the pitch plt.figure(figsize=(10, 6)) plt.bar(notes, frequencies, color=['#FF9999', '#66B3FF', '#99FF99','#FFCC99', '#FFD700']) plt.title('Pitch Corresponding to the Five Tones') plt.xlabel('Tone') plt.ylabel('Frequency (Hz)') plt.ylim(0, 400) plt.grid(axis='y') # Display the frequency values for i, freq in enumerate(frequencies): plt.text(i, freq + 5, f'{freq:.2f} Hz', ha='center') plt.show() The five tones are closely related to pitch, emotions, and the five elements in traditional Chinese medicine theory; help understand their applications in traditional Chinese medicine; According to the results output by the AI ​​TCM Five Tones model, the TCM Five Tones filling range is obtained and the healthy TCM Five Tones filling value status is evaluated, possible conditioning suggestions are provided, the TCM Five Tones filling value is determined, and the comprehensive TCM Five Tones filling value is evaluated to develop personalized TCM Five Tones health indicators.

[0007] 3. The volume module is used for the auditory function data module of the five tones of traditional Chinese medicine, and comprises the following steps: obtaining the intelligent human body audio five tones of traditional Chinese medicine filling data; Volume measurement and analysis Loudness: Using decibels (dB) to measure volume, loudness can be calculated from the amplitude information of the audio signal; Dynamic Range: Dynamic range refers to the difference between the loudest and softest parts of an audio signal; changes in dynamic range can reflect an individual's mood swings and health status; Volume Analysis Use librosa library to extract volume features of audio signals, and combine with TCM five-tone method to analyze health status; import numpy as np import librosa import matplotlib.pyplot as plt # Load audio file file_path = 'your_audio_file.wav' # Replace with your audio file path y, sr = librosa.load(file_path, sr=None) # Calculate volume (loudness) # Use short-time energy to calculate volume frame_length = 2048 hop_length = 512 energy = np.array([ np.sum(np.abs(y[i:i + frame_length]**2)) for i in range(0, len(y), hop_length) ]) # Convert energy to decibels volume_db = 10 * np.log10(energy + 1e-10) # Add a small constant to avoid negative infinity in logarithm # Plot the volume change plt.figure(figsize=(12, 6)) plt.plot(volume_db, label='Volume (dB)') plt.title('Volume Tracking') plt.xlabel('Frame') plt.ylabel('Volume (dB)') plt.legend() plt.grid() plt.show() # Assume we have a simple rule to judge the health status def analyze_health(volume_db): avg_volume = np.mean(volume_db) if avg_volume < -30: return "There may be health problems. It is recommended to consult a doctor." elif avg_volume < -10: return "The mood may be low. It is recommended to relax." else: return "The health status is good." # Health status analysis health_status = analyze_health(volume_db) print("Health status analysis:", health_status) # Volume characteristics of the five traditional Chinese music tones (example) five_sounds = { "Gong tone": {"Volume characteristic": "Soft"}, "Shang tone": {"Volume characteristic": "Moderate"}, "Jue tone": {"Volume characteristic": "Exciting"}, "Zhi tone": {"Volume characteristic": "Clear"}, "Feather sound": {"Volume characteristics": "Deep"} } # Print five-tone volume characteristics for sound, features in five_sounds.items(): print(f"{sound}: {features['volume features']}") Through the volume module of human pronunciation combined with the theory of five tones in traditional Chinese medicine, a certain analysis and judgment can be made on the health status of an individual; changes in volume can reflect the physiological and psychological state of the individual. According to the results output by the AI ​​TCM five-tone model, the filling range of the five tones in traditional Chinese medicine can be obtained and the healthy TCM five-tone filling value status assessment can be judged, possible conditioning suggestions can be provided, the TCM five-tone filling value can be determined, and the comprehensive TCM five-tone filling value can be evaluated to formulate personalized health indicators of the five tones in traditional Chinese medicine.

[0008] 4. The method of the auditory function data module of the rhythm module for the five tones of traditional Chinese medicine includes the following steps: obtaining the intelligent human body audio five tones of traditional Chinese medicine filling data; Measuring and analyzing rhythm Beat: Beat is the basic unit of speech, usually expressed in beats per minute (BPM); beat information can be extracted through time domain analysis of audio signals; Rhythm Pattern: Rhythmic patterns refer to the arrangement and intensity of speech sounds. Rhythmic patterns can be identified by analyzing the volume and duration of audio signals. Implementing rhythm analysis: Use librosa library to extract the rhythm features of audio signals, and combine them with the five tones of traditional Chinese medicine to analyze health status; import numpy as np import librosa import matplotlib.pyplot as plt # Load audio file file_path = 'your_audio_file.wav' # Replace with your audio file path y, sr = librosa.load(file_path, sr=None) # Extract the beats tempo, _ = librosa.beat.beat_track(y=y, sr=sr) # Print tempo information print(f"Estimated Tempo: {tempo} BPM") # Plot the audio signal waveform plt.figure(figsize=(12, 6)) librosa.display.waveshow(y, sr=sr) plt.title('Audio Waveform') plt.xlabel('Time (s)') plt.ylabel('Amplitude') plt.grid() plt.show() # Assume we have a simple rule to judge the health status def analyze_health(tempo): if tempo < 60: return "The tempo is too slow, possibly indicating signs of fatigue or depression;" elif 60 <= tempo <= 100: return "The tempo is moderate, and the health status is good." else: return "The tempo is too fast, possibly indicating signs of anxiety or excessive stress;" # Health status analysis health_status = analyze_health(tempo) print("Health status analysis:", health_status) # Rhythm characteristics of the five traditional Chinese musical notes (example) five_sounds = { "Gongyin": {"Rhythm characteristic": "Steady"}, "Shangyin": {"Rhythm characteristic": "Moderate"}, "Jiaoyin": {"Rhythm characteristic": "Exciting"}, "Zhiyin": {"Rhythm characteristic": "Clear"}, "Yuyin": {"Rhythm characteristic": "Deep"} } # Print the rhythm characteristics of the five musical notes for sound, features in five_sounds.items(): print(f"{sound}: {features['rhythm features']}") By combining the rhythm module of human pronunciation with the theory of five tones in traditional Chinese medicine, we can analyze and judge the health status of an individual. According to the results output by the AI ​​five-tone model, we can obtain the filling range of the five tones in traditional Chinese medicine and judge the healthy filling value status of the five tones in traditional Chinese medicine, provide possible conditioning suggestions, determine the filling value of the five tones in traditional Chinese medicine, and conduct an assessment based on the comprehensive filling value of the five tones in traditional Chinese medicine to develop personalized health indicators for the five tones in traditional Chinese medicine.

[0009] 5. The method of the auditory function data module of the frequency module to the five tones of traditional Chinese medicine includes the following steps: obtaining the intelligent human body audio five tones of traditional Chinese medicine filling data; Frequency Measurement and Analysis Spectrum Analysis: The audio signal can be converted into the frequency domain through Fourier transform (FFT), and the amplitude and phase information of each frequency component can be extracted; Fundamental Frequency: The fundamental frequency is the most important frequency component in an audio signal, usually related to the pitch. It can be obtained through spectrum analysis; Implement frequency analysis: Use librosa library to extract the frequency characteristics of audio signals, and combine them with the five tones of traditional Chinese medicine to analyze health status; import numpy as np import librosa import matplotlib.pyplot as plt # Load audio file file_path = 'your_audio_file.wav' # Replace with your audio file path y, sr = librosa.load(file_path, sr=None) # Calculate the spectrum D = np.abs(librosa.stft(y)) frequencies = librosa.fft_frequencies(sr=sr) # Calculate fundamental frequency pitches, magnitudes = librosa.piptrack(y=y, sr=sr) fundamental_frequencies = [np.max(pitches[:, t]) for t in range(pitches.shape[1])] # Plot spectrum plt.figure(figsize=(12, 6)) plt.semilogy(frequencies, np.mean(D, axis=1), label='Mean Spectrum') plt.title('Frequency Spectrum') plt.xlabel('Frequency (Hz)') plt.ylabel('Magnitude') plt.grid() plt.legend() plt.show() # Assume we have a simple rule to determine the health status def analyze_health(fundamental_frequencies): avg_freq = np.mean(fundamental_frequencies) if avg_freq < 250: return "The frequency is low, there may be health problems, it is recommended to consult a doctor;" elif 250 <= avg_freq <= 450: return "Frequency is normal and health is good." else: return "A high frequency may be a sign of anxiety or excessive stress;" # Health status analysis health_status = analyze_health(fundamental_frequencies) print("Health status analysis:", health_status) # Frequency characteristics of the five tones of traditional Chinese medicine (example) five_sounds = { "gong sound": {"frequency characteristics": "261.63 Hz"}, "Business tone": {"Frequency characteristics": "293.66 Hz"}, "Angular tone": {"Frequency characteristics": "329.63 Hz"}, "Sound": {"Frequency characteristics": "392.00 Hz"}, "Feather sound": {"Frequency characteristics": "440.00 Hz"} } # Print five-tone frequency characteristics for sound, features in five_sounds.items(): print(f"{sound}: {features['frequency features']}") By combining the frequency module of human pronunciation with the theory of five tones in traditional Chinese medicine, we can analyze and judge the health status of an individual. According to the results output by the AI ​​five-tone model, we can obtain the filling range of the five tones in traditional Chinese medicine and judge the healthy filling value status of the five tones in traditional Chinese medicine, provide possible conditioning suggestions, determine the filling value of the five tones in traditional Chinese medicine, and conduct an assessment based on the comprehensive filling value of the five tones in traditional Chinese medicine to develop personalized health indicators for the five tones in traditional Chinese medicine.

[0010] 6. The method of the module of auditory function data of the five tones of traditional Chinese medicine by the module of the characteristics of the tone (such as pitch and scale) comprises the following steps: obtaining the filling data of the five tones of traditional Chinese medicine of the intelligent human body audio; Measurement and analysis of tone Pitch: Pitch refers to the highness of a sound, usually expressed in Hertz (Hz); pitch information can be extracted through spectral analysis of audio signals; Scale: The scale refers to the arrangement of pitches, usually including major and minor keys. The scale can be identified by the pitch changes of the audio signal; to achieve pitch analysis Use librosa library to extract the tone features of audio signals, and combine them with the five tones of traditional Chinese medicine to analyze health status; import numpy as np import librosa import matplotlib.pyplot as plt # Load audio file file_path = 'your_audio_file.wav' # Replace with your audio file path y, sr = librosa.load(file_path, sr=None) # Extract the pitch pitches, magnitudes = librosa.piptrack(y=y, sr=sr) # Calculate fundamental frequency fundamental_frequencies = [np.max(pitches[:, t]) for t in range(pitches.shape[1]) if np.max(pitches[:, t]) > 0] # Calculate the average pitch avg_pitch = np.mean(fundamental_frequencies) # Print average pitch print(f"Average Pitch: {avg_pitch:.2f} Hz") # Assume we have a simple rule to determine the health status def analyze_health(avg_pitch): if avg_pitch < 250: return "The pitch is low, which may indicate health problems. It is recommended that you consult a doctor." elif 250 <= avg_pitch <= 450: return "Normal pitch, good health." else: return "A high pitch voice may be a sign of anxiety or stress;" # Health status analysis health_status = analyze_health(avg_pitch) print("Health status analysis:", health_status) # Pitch characteristics of the five tones in traditional Chinese medicine (example) five_sounds = { "Gongyin": {"Pitch characteristics": "261.63 Hz"}, "Shangyin": {"Pitch feature": "293.66 Hz"}, "angular tone": {"pitch characteristics": "329.63 Hz"}, "Zhiyin": {"Pitch characteristics": "392.00 Hz"}, "Feather sound": {"Pitch characteristics": "440.00 Hz"} } # Print pentatonic pitch characteristics for sound, features in five_sounds.items(): print(f"{sound}: {features['pitch feature']}") By combining the tonal characteristics of human pronunciation with the theory of the five tones in traditional Chinese medicine, we can analyze and judge the individual's health status to a certain extent; based on the results output by the AI ​​TCM five-tone model, we can obtain the TCM five-tone filling range and judge the healthy TCM five-tone filling value status assessment, provide possible conditioning suggestions, determine the TCM five-tone filling value, and conduct an assessment based on the comprehensive TCM five-tone filling value to develop personalized health indicators for the TCM five-tones.

[0011] 7. The module method of auditory function data module of TCM five tones by the module of timbre characteristics (such as sound quality and timbre type) includes the following steps: obtaining TCM five tones filling data of intelligent human audio; Measurement and analysis of timbre Sound quality (Timbre): Sound quality refers to the characteristics of sound, which is usually determined by the shape of the spectrum and the harmonic content; sound quality information can be extracted through spectral analysis of audio signals; Timbre Type: There are many types of timbre, such as bright, warm, cold, and rich. The timbre type can be identified through feature extraction and classification algorithms of audio signals. To achieve timbre analysis: Use librosa library to extract the timbre characteristics of audio signals, and combine them with the five tones of traditional Chinese medicine to analyze health status; import numpy as np import librosa import matplotlib.pyplot as plt # Load audio file file_path = 'your_audio_file.wav' # Replace with your audio file path y, sr = librosa.load(file_path, sr=None) # Extract audio features # Calculate Mel-frequency cepstral coefficients (MFCCs) as timbre features mfccs = librosa.feature.mfcc(y=y, sr=sr, n_mfcc=13) # Calculate the mean and standard deviation of MFCC mfccs_mean = np.mean(mfccs, axis=1) mfccs_std = np.std(mfccs, axis=1) # Print MFCC features print("MFCC Mean:", mfccs_mean) print("MFCC Std:", mfccs_std) # Assume we have a simple rule to determine the health status def analyze_health(mfccs_mean): if np.mean(mfccs_mean) < -200: return "The tone is dark, which may indicate health problems. It is recommended to consult a doctor." elif -200 <= np.mean(mfccs_mean) <= -50: return "Normal tone, good health." else: return "A brighter tone may be a sign of anxiety or stress." # Health status analysis health_status = analyze_health(mfccs_mean) print("Health status analysis:", health_status) # Tone characteristics of the five tones in traditional Chinese medicine (example) five_sounds = { "Gongyin": {"Timbre characteristics": "soft, mellow"}, "Business tone": {"Tone characteristics": "clear, bright"}, "horn tone": {"tone characteristics": "passionate and expressive"}, "Zhēng sound": {"Timbre characteristics": "Crisp and loud"}, "Yǔ sound": {"Timbre characteristics": "Deep and melodious"} } # Print the timbre characteristics of the five sounds for sound, features in five_sounds.items(): print(f"{sound}: {features['Timbre characteristics']}") By combining the timbre characteristics of human pronunciation with the five - sound theory of traditional Chinese medicine, the health status of an individual can be analyzed and judged to a certain extent; according to the results output by the AI five - sound model of traditional Chinese medicine, the range of fullness of the five sounds of traditional Chinese medicine is obtained, the state of the fullness value of the healthy five sounds of traditional Chinese medicine is judged, possible conditioning suggestions are provided, the fullness value of the five sounds of traditional Chinese medicine is determined, and the comprehensive fullness value of the five sounds of traditional Chinese medicine is evaluated to formulate personalized health indicators of the five sounds of traditional Chinese medicine.

[0012] Intelligent health management system of traditional Chinese medicine auscultation based on the AI large - model; the auditory function module that converts the health voice audio monitoring data into the five sounds of traditional Chinese medicine transmits the fullness data of the healthy five sounds of traditional Chinese medicine to the AI five - sound model server of traditional Chinese medicine to evaluate the recent fullness state of the healthy five sounds of traditional Chinese medicine, and judges whether the recent transmission state of the auditory function module that transmits the healthy five - sound data of traditional Chinese medicine to the AI five - sound model server of traditional Chinese medicine is normal; When the state of the auditory function module that converts the fullness data of the five sounds of traditional Chinese medicine of the health monitoring sensor and transmits the health data to the AI five - sound model server of traditional Chinese medicine is normal: the auditory function module that transmits the sensor data and converts it into the five sounds of traditional Chinese medicine, the health monitoring device transmits the health data to the AI five - sound model server of traditional Chinese medicine for the analysis coefficient of the availability of the health data of the AI five - sound model service and its fullness value of the five sounds of traditional Chinese medicine; convert and verify the evaluation coefficient of the availability of the health data of the AI five - sound model service and its fullness value of the five sounds of traditional Chinese medicine to evaluate the performance of the AI large - model server of traditional Chinese medicine in processing the fullness data of the healthy five sounds of traditional Chinese medicine; The auditory function module of the five sounds of traditional Chinese medicine that synthesizes the fullness of the five sounds of traditional Chinese medicine, the set of seven fullness value modules of the five sounds of traditional Chinese medicine, transmits the overall recent health voice audio monitoring data to the AI five - sound model server of traditional Chinese medicine for the analysis of the fullness data of the healthy five sounds of traditional Chinese medicine, evaluates the coefficient of the availability of the fullness data of the healthy five sounds of traditional Chinese medicine and the proportion of its fullness value of the five sounds of traditional Chinese medicine, and discovers possible problems with the fullness of the healthy five sounds of traditional Chinese medicine in advance. Brief description of the drawings

[0013] Figure 1This is a structural schematic diagram of an embodiment of the present application, which provides a TCM health management plan based on the TCM five-tone filling value and improves the individual's health level by using a TCM auscultation intelligent health management system based on an AI large model for TCM five-tone filling value. DETAILED DESCRIPTION

[0014] Through the healthy voice audio TCM five-tone auditory function data module, including the Mel-frequency cepstral coefficient (MFCC) module of the five-tone audio signal and the pitch (Pitch) module; volume (Volume) module; rhythm (Rhythm) module; frequency module, tone feature (such as pitch, scale) module, timbre feature (such as sound quality, timbre type) module, and then transmit the recent healthy TCM five-tone filling data to the AI ​​TCM five-tone large model server to evaluate the health status to determine whether the recent transmission status of the healthy voice audio monitoring TCM five-tone auditory function data module transmitting the health data to the AI ​​TCM five-tone large model server is normal; when the healthy voice audio monitoring TCM five-tone filling data TCM five-tone auditory function data module transmitting the health data to the AI ​​TCM five-tone large model server is normal, the voice audio data conversion TCM five-tone auditory function data module is healthy. The monitoring equipment then transmits the health data to the AI ​​TCM Five Tones Big Model server to evaluate the available analysis coefficient of the health data of the AI ​​TCM Five Tones Big Model service and its baseline value and health value; at the same time, verify the available evaluation coefficient of the health data of the AI ​​TCM Five Tones Big Model service and its TCM Five Tones filling value, and evaluate the performance of the AI ​​TCM Five Tones Big Model server in processing healthy TCM Five Tones filling data; at the same time, the comprehensive TCM Five Tones filling TCM Five Tones auditory function data module includes a set of seven TCM Five Tones filling value modules to transmit the recent health voice audio monitoring data as a whole to the AI ​​TCM Big Model server for health data analysis, evaluate the available coefficient of health data and the proportion of its TCM Five Tones filling value, discover possible health TCM Five Tones filling problems in advance, take measures to prevent diseases, provide personalized health management services for TCM Five Tones, and improve the efficiency and availability of health TCM Five Tones filling data management for healthy people.

[0015] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application; therefore, the protection scope of the present application should be based on the protection scope of the claims; Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. The intelligent health management system of TCM diagnosis based on AI big model is characterized by: It includes the Mel Frequency Cepstral Coefficient (MFCC) module and the Pitch module of the five-tone audio signal; the Volume module; the Rhythm module; the Frequency module, the Tone feature (such as pitch, scale) module, and the Tone feature (such as sound quality, Tone type) module; The auditory function data module of the healthy TCM five-tone system transmits the recent healthy audio data to the AI ​​TCM big model server, and evaluates the healthy TCM five-tone value to determine whether the recent transmission status of the value data of the auditory function data module of the health monitoring audio data TCM five-tone system transmitted to the AI ​​TCM five-tone big model server is normal; When the auditory function data value data of the healthy audio data TCM five tones is transmitted to the AI ​​TCM big model server in a normal state, the health monitoring device of the audio data TCM five tones data module transmits the health data to the AI ​​TCM big model server to evaluate the TCM five tones data value of the available analysis coefficient of the AI ​​TCM big model service health data, and at the same time, verify the available evaluation coefficient of the AI ​​TCM big model service health data and its TCM five tones value, and evaluate the performance of the AI ​​TCM big model server in processing the health TCM five tones value data; The seven modules of auditory function data of the comprehensive TCM five-tone system are used to transmit the recent health monitoring data as a whole to the AI ​​TCM big model server for health TCM five-tone value data analysis, evaluate the available coefficients of health TCM five-tone data and the proportion of its TCM five-tone value, and discover possible health TCM five-tone value problems in advance.

2. The AI ​​big model-based TCM auscultation intelligent health management system according to claim 1 is characterized by: The auditory function data module of the healthy five tones of Chinese medicine transmits the auditory function data module data of the healthy five tones of Chinese medicine to the AI ​​large model server of Chinese medicine to evaluate the recent healthy five tones value status of Chinese medicine; set the auditory function data module set of the five tones of Chinese medicine, and transmit the healthy five tones data of multiple auditory function data modules of the five tones of Chinese medicine to the AI ​​large model server of Chinese medicine; obtain the number of data packets sent in the process of transmitting the healthy five tones data of the auditory function data module of the five tones of Chinese medicine to the AI ​​large model server of Chinese medicine, and obtain the data of the process of transmitting the healthy five tones data of multiple auditory function data modules of the five tones of Chinese medicine to the AI ​​large model server of Chinese medicine; Calculate each time the healthy TCM five-tone value data is transmitted to the AI ​​TCM big model server, analyze the available coefficient of the data health data and the proportion of its TCM five-tone value, and evaluate the data of health monitoring and AI TCM big model server; set the threshold, monitor the auditory function data module of TCM five-tone to generate a normal transmission signal; these features will help the system to evaluate and monitor the healthy TCM five-tone data and provide TCM health management services.

3. According to the AI ​​big model-based TCM auscultation intelligent health management system of claim 1 and claim 2, it is characterized by: The human audio signal is processed through audio recognition technology to determine the frequency, tone characteristics (such as pitch, scale), timbre characteristics (such as sound quality, timbre type), Mel-frequency cepstral coefficients (MFCC) and pitch (Pitch); volume (Volume); rhythm (Rhythm) of the audio signal, and then handed over to the AI ​​large model (the large model after fine-tuning by TCM) for comprehensive analysis, judgment, and processing of its audio physiological five-tone characteristics; the TCM five-tone values ​​are determined by data, and the TCM five-tones are evaluated comprehensively; after processing, the array is given physical, psychological, diet suggestions, skin and body beauty, and natural therapy suggestions; it is emphasized that most of a healthy life comes from life itself, 60% is related to life, and existing medical care is only an evidence-based medicine indicator, lacking personalized health indicators; it aims to determine the TCM five-tone values ​​based on data, and conduct a comprehensive evaluation of the TCM five-tones to develop TCM five-tone health indicators.

4. The technical features and applications of the system include integrating the auditory function data module of the healthy TCM five tones, combining the AI ​​TCM big model to analyze the human body's audio physiological characteristics and provide TCM five tones values, as well as comprehensive TCM five tones evaluation to develop personalized TCM five tones health indicators and other innovations.

5. Mel-frequency cepstral coefficient (MFCC) module: used to describe the characteristics of audio signals; The method for judging the health value status according to the five-tone value range of traditional Chinese medicine includes the following steps: Get audio data of TCM five tones; According to the acquired data, the auditory function data module of the five tones of traditional Chinese medicine is used; the audio signal is high-pass filtered to enhance the high-frequency part; Framing: Divide the audio signal into short time frames, usually 20-40 milliseconds long. Window function: Apply a window function (such as a Hamming window) to each frame to reduce edge effects; Fourier transform: Perform fast Fourier transform (FFT) on each frame to obtain the spectrum; Mel filter bank: The spectrum is passed through the Mel filter bank to simulate the human ear's perception of different frequencies; Logarithmic operation: take the logarithm of the Mel frequency energy; Discrete Cosine Transform (DCT): DCT is performed on the logarithmic Mel frequency energy to obtain MFCC coefficients; The five tones in traditional Chinese medicine (gong, shang, jiao, zhi, yu) are closely related to the timbre, emotion and health of audio signals; MFCC can help us extract the features of these audio signals and analyze their correspondence with the five tones; According to the results output by the AI ​​TCM big model, the Mel-frequency cepstral coefficient (MFCC) and the TCM five-tone filling range are obtained to judge the healthy TCM five-tone value status assessment, provide possible conditioning suggestions, determine the TCM five-tone filling value, and conduct an assessment based on the TCM five-tone filling value to develop TCM individual health indicators.

6. Pitch module method, The following steps are involved: Get intelligent audio pitch (Pitch) TCM five-tone data; According to the acquired data, compile the function of evaluating the pitch (Pitch) filling data of TCM five tones and the auditory function data of TCM five tones to judge the health status of TCM five tones; Set the TCM five-tone filling range to judge the healthy TCM five-tone filling value status from the perspective of human health; Input the acquired data into the AI ​​TCM big model and let the AI ​​TCM big model analyze and process it; The five tones (gong, shang, jue, zhi, yu) correspond to the five elements (wood, fire, earth, metal, water), and correspond to different pitches and emotions; the pitch and frequency range of each tone can be associated with a specific physiological and psychological state; the following is a detailed introduction to the five tones and their corresponding pitches; Basic Concepts Gong sound (Do): Corresponding pitch: C (approximately 261.63 Hz) Corresponding five elements: Earth Related emotions: Stability, peace Business Sound (Re): Corresponding pitch: D (approximately 293.66 Hz) Corresponding five elements: gold Associated emotions: clarity, rationality Corner sound (Mi): Corresponding pitch: E (approximately 329.63 Hz) Corresponding five elements: Wood Associated emotions: Growth, Vitality Zhengyin (Fa): Corresponding pitch: F (approximately 349.23 Hz) Corresponding five elements: Fire Related emotions: passion, enthusiasm Sol: Corresponding pitch: G (approximately 392.00 Hz) Corresponding five elements: water Related emotions: Soft, Flowing The five tones are believed to influence a person’s mood and health; Based on the results output by the AI ​​TCM big model, an assessment of the pitch status is obtained, possible conditioning suggestions are provided, the five TCM tone values ​​are determined, and an assessment is conducted based on the comprehensive five TCM tone values ​​to develop individual TCM health indicators.

7. Volume: The auditory function data module of the five tones of traditional Chinese medicine and the relationship between the five tones of traditional Chinese medicine and health status; The five sounds correspond to the five internal organs (heart, spleen, liver, lungs, and kidneys) and emotions; Gongyin (C) Corresponding organs: Heart Volume characteristics: usually high; Health status: If the volume is too low, it may indicate depression or poor heart function; if the volume is too high, it may indicate anxiety or excitement; Shangyin (D) Corresponding organs: spleen Volume characteristics: moderate; Health status: too low volume may indicate indigestion or unclear thinking; too high volume may indicate excessive thinking or stress; Horn (E) Corresponding organs: Liver Volume characteristics: can be quite exciting; Health status: Low volume may indicate depression or repression; high volume may indicate anger or loss of control. G Corresponding organs: Lung Volume characteristics: clear; Health status: Low volume may indicate respiratory problems or worries; high volume may indicate anxiety or tension; Yuyin (A) Corresponding organs: Kidney Volume characteristics: deep; Health status: Low volume may indicate fatigue or poor kidney function; high volume may indicate fear or anxiety; Loudness: Use decibels (dB) to measure volume. The loudness can be calculated from the amplitude information of the audio signal; Dynamic Range: Dynamic range refers to the difference between the loudest and softest parts of an audio signal; changes in dynamic range can reflect an individual's mood swings and health status.

8. The rhythm module is a module for the auditory function data of the five tones of traditional Chinese medicine, and the relationship between the five tones of traditional Chinese medicine and health status; it includes the following steps: Relationship of health status: Each sound corresponds to a specific emotion and organ; changes in rhythm can reflect an individual's physiological and psychological state; Gongyin (C) Corresponding organs: Heart Rhythmic characteristics: usually relatively steady, suitable for gentle melodies; Health status: If the pronunciation rhythm is irregular or too rapid, it may indicate emotional instability or poor heart function; Shangyin (D) Corresponding organs: spleen Rhythm characteristics: moderate rhythm, neither fast nor slow; Health status: A fast tempo may indicate excessive stress, while a slow tempo may indicate indigestion or unclear thinking; Horn (E) Corresponding organs: Liver Rhythm characteristics: can be relatively exciting, suitable for fast rhythms; Health status: An erratic or overly intense rhythm may indicate repressed or angry emotions; G Corresponding organs: Lung Rhythm characteristics: The rhythm is clear and suitable for expressing emotions; Health status: An irregular rhythm may indicate respiratory problems or anxiety; Yuyin (A) Corresponding organs: Kidney Rhythm characteristics: can be relatively deep, suitable for slow-tempo music; Health status: A slow and erratic rhythm may indicate fatigue or poor kidney function; Beat: Beat is the basic unit of music, usually expressed in beats per minute (BPM); beat information can be extracted through time domain analysis of audio signals; Rhythm Pattern: Rhythmic patterns refer to the arrangement and intensity of notes; rhythmic patterns can be identified by analyzing the volume and duration of audio signals; Based on the results of the model output, an assessment of the healthy TCM five-tone value status of rhythm and TCM five-tone fullness is obtained, possible conditioning suggestions are provided, TCM five-tone values ​​are determined, and an assessment is conducted based on the comprehensive TCM five-tone fullness values ​​to develop TCM individual health indicators.

9. Frequency module: The auditory function data module of the five tones of traditional Chinese medicine is about the relationship between the five tones of traditional Chinese medicine and health status; including the following steps: Each sound corresponds to a specific emotion and organ; changes in frequency can reflect an individual's physiological and psychological state; Gongyin (C) Corresponding organs: Heart Frequency characteristics: usually around 261.63 Hz (C4); Health status: If the pronunciation frequency is unstable or deviates from the normal range, it may indicate emotional instability or poor heart function; Shangyin (D) Corresponding organs: spleen Frequency characteristics: usually around 293.66 Hz (D4); Health status: too low a frequency may indicate indigestion or unclear thinking; too high a frequency may indicate excessive thinking or stress; Horn (E) Corresponding organs: Liver Frequency characteristics: usually around 329.63 Hz (E4); Health status: Erratic or overly intense frequencies may indicate repressed or angry emotions; G Corresponding organs: Lung Frequency characteristics: usually around 392.00 Hz (G4); Health status: Irregular frequency may indicate respiratory problems or anxiety; Yuyin (A) Corresponding organs: Kidney Frequency characteristics: usually around 440.00 Hz (A4); Health status: too low a frequency may indicate fatigue or poor kidney function; too high a frequency may indicate fear or anxiety; Spectrum Analysis: The audio signal can be converted into the frequency domain through Fourier transform (FFT), and the amplitude and phase information of each frequency component can be extracted; Fundamental Frequency: Provide possible conditioning suggestions, determine the TCM five-tone filling values, conduct comprehensive evaluation based on the TCM five-tone filling values, and develop TCM individual health indicators.

10. Tone feature (such as pitch, scale) module: The auditory function data module of the five tones of traditional Chinese medicine is about the relationship between the five tones of traditional Chinese medicine and health status; including the following steps: Each sound corresponds to a specific emotion and internal organ; changes in tone can reflect an individual's physiological and psychological state; Gongyin (C) Corresponding organs: Heart Pitch characteristics: usually around 261.63 Hz (C4); Health status: If the pitch of your voice is unstable or deviates from the normal range, it may indicate emotional instability or poor heart function; Shangyin (D) Corresponding organs: spleen Pitch characteristics: usually around 293.66 Hz (D4); Health status: A low pitch may indicate indigestion or unclear thinking; a high pitch may indicate excessive thinking or stress; Horn (E) Corresponding organs: Liver Pitch characteristics: usually around 329.63 Hz (E4); Health status: Unstable or overly intense pitch may indicate repressed or angry emotions; G Corresponding organs: Lung Pitch characteristics: usually around 392.00 Hz (G4); Health status: Irregular pitch may indicate respiratory problems or anxiety; Yuyin (A) Corresponding organs: Kidney Pitch characteristics: usually around 440.00 Hz (A4); Health status: A low pitch may indicate fatigue or poor kidney function; a high pitch may indicate fear or anxiety; Pitch: Pitch refers to the highness of a sound, usually expressed in Hertz (Hz); pitch information can be extracted through spectral analysis of audio signals; Provide possible conditioning suggestions, determine the TCM five-tone filling values, conduct comprehensive evaluation based on the TCM five-tone filling values, and develop TCM individual health indicators.

11. Tone characteristics (such as sound quality, tone type) module: The auditory function data module of the five tones of traditional Chinese medicine is about the relationship between the five tones of traditional Chinese medicine and health status; including the following steps: Each sound corresponds to a specific emotion and internal organ; changes in timbre can reflect an individual's physiological and psychological state; Gongyin (C) Corresponding organs: Heart Tone characteristics: soft and mellow; Health status: A voice that is too sharp or rough may indicate emotional instability or poor heart function; Shangyin (D) Corresponding organs: spleen Tone characteristics: clear and bright; Health status: A dull or fuzzy voice may indicate indigestion or unclear thinking; Horn (E) Corresponding organs: Liver Tone characteristics: passionate and expressive; Health status: A tone that is too monotonous or suppressed may indicate repressed or angry emotions; G Corresponding organs: Lung Tone characteristics: crisp and loud; Health status: A dull voice may indicate respiratory problems or anxiety; Yuyin (A) Corresponding organs: Kidney Tone characteristics: deep and melodious; Health status: A weak or feeble voice may indicate fatigue or poor kidney function; Sound quality (Timbre): Sound quality refers to the characteristics of sound, which is usually determined by the shape of the spectrum and the harmonic content; sound quality information can be extracted through spectral analysis of audio signals; Timbre Type There are many types of timbre, such as bright, warm, cold, and rich. The timbre type can be identified through feature extraction and classification algorithms of audio signals. According to the results output by the AI ​​TCM Five Tones model, the TCM Five Tones filling range is obtained and the healthy TCM Five Tones filling value status is evaluated, possible conditioning suggestions are provided, the TCM Five Tones filling value is determined, and the comprehensive TCM Five Tones filling value is evaluated to develop personalized TCM Five Tones health indicators.

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