Pulse Condition Prediction Model for TCM Diagnosis
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Solution Overview
Problem
Traditional Chinese medicine practitioners face challenges in making efficient and accurate diagnoses due to the vast number of possible variations in pulse data, despite the use of pulse diagnosis machines, which complicates the interpretation of pulse information from meridians.
Innovation Solution
A pulse condition prediction method and system that includes a pressure sensing module to obtain arterial waveforms and a processing module to generate predicted data, which is input into a pulse condition prediction model to produce probability values for various pulse conditions, enhancing diagnostic accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If pulse diagnosis machines are used to collect comprehensive pulse data from multiple meridians, then the quantity and completeness of diagnostic data is improved, but the complexity of data interpretation and diagnostic efficiency deteriorates
Solution Approach 1:
The patent introduces an AI prediction model as an intermediary between the pulse diagnosis machine and the practitioner. The machine collects comprehensive pulse data from multiple meridians, the AI model processes this data to generate predicted probability values for various pulse conditions, and the practitioner receives simplified diagnostic suggestions. This intermediary handles the complex data interpretation task, resolving the contradiction between data completeness and diagnostic efficiency.
2Ease of operation
If traditional practitioners rely solely on manual pulse feeling and qualitative assessment, then the simplicity of the diagnostic process is maintained, but the measurement precision and accuracy of pulse condition identification deteriorates
Solution Approach 1:
The patent replaces the manual mechanical process of pulse feeling and qualitative assessment with an automated electronic system. The pulse diagnosis machine mechanically senses arterial waveforms, and the AI model algorithmically processes the data to provide precise diagnostic predictions. This substitution maintains operational simplicity for the practitioner while dramatically improving measurement precision through automated data collection and analysis.
3Adaptability or versatility
If the pulse diagnosis system analyzes all 2048×2048×2048×2048 possible variations of pulse data, then the comprehensiveness of diagnostic coverage is improved, but the device complexity and computational requirements deteriorates
Solution Approach 1:
The patent transforms the diagnostic approach by changing the parameters used for analysis. Instead of evaluating all possible pulse variations directly, the system uses the AI prediction model to identify key predictive features and parameters from the pulse data. The model processes the comprehensive data set but outputs results based on a reduced set of critical parameters, maintaining diagnostic comprehensiveness while reducing computational complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enables traditional Chinese medicine practitioners to make more accurate and efficient diagnoses by providing predicted probability values, reducing the likelihood of misdiagnosis and improving the precision of experienced practitioners.
Implementation Method 1
sensing, by a pressure sensing module, an artery of a first subject and a first arterial waveform being obtained by the artery of the first subject
Data Source
AI summary
A pulse condition prediction method and system. The pulse condition prediction system includes a pressure sensing module and a processing module. The pulse condition prediction method includes: sensing, by a pressure sensing module, an artery of a first subject to obtain a first arterial waveform, generating, by a processing module, to-be-predicted data basing on the first arterial waveform, wherein the to-be-predicted data includes pieces of first pulse wave data of meridians, and inputting, by the processing module, into a pulse condition prediction model, and predicted probability values of pulse conditions being generated by the pulse condition prediction model. Accordingly, pulse condition prediction result with high accuracy may be generated. Chinese medicine practitioner may perform more accurate and efficient diagnosis on the subject's health condition according to predicted probability values of the pulse conditions generated by the pulse condition prediction model and other determination results of look, listen, question and/or feel.