A Novel Pulse‑Taking Device for Persian Medicine Based on Convolutional Neural Networks
عنوان مقاله: A Novel Pulse‑Taking Device for Persian Medicine Based on Convolutional Neural Networks
شناسه ملی مقاله: JR_JMSI-12-4_003
منتشر شده در در سال 1401
شناسه ملی مقاله: JR_JMSI-12-4_003
منتشر شده در در سال 1401
مشخصات نویسندگان مقاله:
Vahid Reza Nafisi - Biomedical Engineering Group, Electrical and Information Technology Department, Iranian Research Organization for Science and Technology
Roshanak Ghods - Department of Traditional Medicine, Institute for Studies in Medical History, Persian and Complementary Medicine, School of Persian Medicine, Iran University of Medical Sciences, Tehran, Iran
Seyed Vahab Shojaedini - Biomedical Engineering Group, Electrical and Information Technology Department, Iranian Research Organization for Science and Technology
خلاصه مقاله:
Vahid Reza Nafisi - Biomedical Engineering Group, Electrical and Information Technology Department, Iranian Research Organization for Science and Technology
Roshanak Ghods - Department of Traditional Medicine, Institute for Studies in Medical History, Persian and Complementary Medicine, School of Persian Medicine, Iran University of Medical Sciences, Tehran, Iran
Seyed Vahab Shojaedini - Biomedical Engineering Group, Electrical and Information Technology Department, Iranian Research Organization for Science and Technology
Background: In Persian medicine (PM), measuring the wrist pulse is one of the main methods 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. Methods: 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 (CNNs) have been used
for classification. Results: The pulse wave features of ۳۴ participants were 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 each participant’s
pulse characteristic (pace, rate, vessel elasticity, strength, width, length, and height) assessment,
and then, each participant was classified into three classes. Conclusion: It appears that the design
and construction of a customized device combined with the deep learning algorithm can measure
the pulse wave features according to PM and it can increase the reliability and repeatability of the
diagnostic results based on PM.
کلمات کلیدی: Convolutional neural network, Persian medicine, pulse signal, pulse taking, temperament
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1700150/