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Study of Wrist Pulse Signals Using a Bi-Modal Gaussian Model

Rangaprakash, D and Dutt, Narayana D (2014) Study of Wrist Pulse Signals Using a Bi-Modal Gaussian Model. In: 3rd International Conference on Advances in Computing, Communications and Informatics (ICACCI), SEP 24-27, 2014, New Delhi, INDIA, pp. 2422-2425.

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Wrist pulse signals contain important information about the health of a person and hence diagnosis based on pulse signals has assumed great importance. In this paper we demonstrate the efficacy of a two term Gaussian model to extract information from pulse signals. Results have been obtained by conducting experiments on several subjects to record wrist pulse signals for the cases of before exercise and after exercise. Parameters have been extracted from the recorded signals using the model and a paired t-test is performed, which shows that the parameters are significantly different between the two groups. Further, a recursive cluster elimination based support vector machine is used to perform classification between the groups. An average classification accuracy of 99.46% is obtained, along with top classifiers. It is thus shown that the parameters of the Gaussian model show changes across groups and hence the model is effective in distinguishing the changes taking place due to the two different recording conditions. The study has potential applications in healthcare.

Item Type: Conference Proceedings
Publisher: IEEE
Additional Information: Copy right for this article belongs to the IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Keywords: Wrist pulse signal; Gaussian model; Support vector machine
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited: 11 Sep 2015 05:35
Last Modified: 11 Sep 2015 05:35
URI: http://eprints.iisc.ac.in/id/eprint/52348

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