Nonlinear Processing of Wrist Pulse Signals to Distinguish Diabetic and Non-Diabetic Subjects
S Hema Priyadarshini1, D Narayana Dutt2, Anand Prem Rajan3

1S. Hema Priyadarshini*, Department of Medical Electronics, Dayananda Sagar College of Engineering, Bangalore, India.
2D. Narayana Dutt, Department of Medical Electronics, Dayananda Sagar College of Engineering, Bangalore, India.
3Anand Prem Rajan, School of Biosciences and Biotechnology, VIT University, Vellore, India.
Manuscript received on September 23, 2019. | Revised Manuscript received on October 15, 2019. | Manuscript published on October 30, 2019. | PP: 7105-7110 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1854109119/2019©BEIESP| DOI: 10.35940/ijeat.A1854.109119
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Abstract: In pulse diagnosis, the pulse signals obtained at wrist have been used for analysis of certain diseases in ancient systems of medicine in which the practitioner feels the pulse of the subject by placing his three fingers on the subject’s wrist at three distinct radial pulse point locations. The preliminary studies show that there are many conventional linear techniques applied to analyze the wrist pulse signals and less focus on non-linear techniques. Hence, the main aim of this research is to apply Recurrence Plot and Recurrence Quantification Analysis (RQA), a nonlinear technique to analyze the wrist pulse signals for distinguishing between diabetic and non-diabetic subjects. Wrist pulse signals from 32 subjects were recorded during the morning hours and were analyzed using RQA techniques. The results show significant differences in the RQA parameters of the wrist pulse signals as they are obtained from the recurrences occurring in the phase space plots of the wrist pulse signals. It was found that parameters like entropy, divergence and average diagonal line length showed significant variations for diabetic and non diabetic subjects. Therefore, it can be concluded that RQA parameters can be used effectively to identify diabetic and non diabetic subjects and thus may be applied on the wrist pulse signals for early detection of various diseases.
Keywords: Non-linear technique, Pulse diagnosis, Recurrence plots, RQA, Wrist pulse signals.