A pulse taking device for Persian medicine based on Convolutional Neural Network

Abstract

In Persian Medicine (PM), measuring the wrist pulse is one of the main method for determining a person's health status and temperament. One problem that can arise is the dependence of the diagnosis on the physician's interpretation of pulse wave features. Perhaps this is one reason why this method has yet to be combined with modern medical methods. This paper addresses this concern and outlines a system for measuring pulse signals based on PM. A system that uses data from a customized device that logs the pulse wave on the wrist was designed and clinically implemented based on PM. Seven Convolutional Neural Networks (CNN) have been used for classification. The pulse wave features of 34 participants was assessed by a specialist based on PM principles. Pulse taking was done on the wrist in the supine position (named Malmas in PM) under the supervision of the physician. Seven CNNs were implemented for participants’ classification based on seven PM classes. It appears that the design and construction of a customized device that can measure the pulse waves features according to PM, is possible and can increase the reliability of the diagnostic results based on PM.