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Title: Automatic identification of acute arthritis from ayurvedic wrist pulses

Authors: N. Arunkumar; P. Mohamed Shakeel; V. Venkatraman

Addresses: Department of Electronics and Instrumentation Engineering, SASTRA University, India ' Department of Computer Science and Engineering, NSN College of Engineering, India ' Department of Mathematics, SASTRA University, India

Abstract: Traditional ayurvedic doctors examine the state of the body by analysing the wrist pulse from the patient. Mysteriously, the characteristics of the pulses vary corresponding to the various changes in the body. The three pulses acquired from the wrist are named as vata, pitta and kapha. Ayurveda says that when there is imbalance in these three doshas, one will have disease. Two different diseases will have different patterns in their pulse characteristics. Thus, the wrist pulse signal serves as a tool to analyse the health status of a patient. In the earlier work, we have standardised the signals for normal persons and then classified the diabetic cases using approximate entropy (ApEn) (Arunkumar and Sirajudeen, 2011) and later enhanced the results using sample entropy. In the present work, sample entropy (SampEn) is being used to classify for the acute arthritis cases.

Keywords: vata; pitta; kapha; approximate entropy, ApEn; sample entropy; SampEn.

DOI: 10.1504/IJCAET.2020.103840

International Journal of Computer Aided Engineering and Technology, 2020 Vol.12 No.1, pp.68 - 73

Received: 05 Mar 2017
Accepted: 28 Jun 2017

Published online: 27 Nov 2019 *

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