Abstract
Various typical wave shapes of the radial artery pulse accumulated from experience have been artificially classified in graphical spectra which are used as initial training samples to train a microcomputer in establishing basic structural classes by modelling identification. A feature space of the classes is then created. A discriminant function is also automatically generated to form decision bounds for the pulse recognition. Self-learning approach has been employed for recreating the new decision boudns or re-designing the basic structural classes to approach the precise pulse recognition. A microcomputer-based real-time method for analysing and recognizing the pulse waves in radial artery is now presented, and it has been tested and will be applied to the diagnosis for the traditional chinese medical services.
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