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

机译：基于卷积神经网络的波斯医学脉冲拍摄装置

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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.
机译：在波斯医学（PM）中，测量手腕脉冲是确定人的健康状况和气质的主要方法之一。可能出现的一个问题是诊断对医生对脉搏波特征的解释的依赖性。也许这是这种方法尚未与现代医疗方法结合的原因。本文解决了这一问题，并概述了一种用于基于PM测量脉冲信号的系统。使用来自定制设备的数据的系统，用于基于PM的PM设计和临床实现在手腕上记录脉冲波。七个卷积神经网络（CNN）已被用于分类。基于PM原则的专家评估了34名参与者的脉搏波特征。在医生的监督下，在仰卧位（PM中的名为Malmas）的手腕上进行了脉搏。根据七个PM课程为参与者分类实施了七个CNN。看来，可以根据PM的脉冲波特征的定制设备的设计和构造是可能的，并且可以基于PM增加基于PM的诊断结果的可靠性。

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