Single-Electrode Triboelectric Nanogenerator Device Framework for Wrist Pulse Signal (Nadi) Analysis and Disease Detection

Abstract

Since ancient times, traditional medical analysis has recorded the wrist pulse as an indication of physical health using the perception of three fingertips classified based on their unique characteristics. The analysis outcomes differ from physicians’ independent judgment, which shall be overcome by utilizing sophisticated sensing techniques and analytical methodologies in computational pulse diagnosis. This paper introduces a device made up of a screen-printed Single-Electrode Triboelectric Nanogenerator (SE-TENG) sensor to record the three pulses (Nadi Pariksha) on the radial artery to diagnose diabetes using wrist pulse analysis. Before time and frequency domain analysis, data from normal and diabetic individuals are pre-processed in MATLAB. Overall, 14-dimensional variables were calculated from each pulse: Vata, Pitta, and Kapha in time domain feature extraction and two variables in frequency domain extraction. Several pulse parameters are calculated and compared with the previous relevant works which confirm substantial changes in the pulse features between normal and diabetic people, assisting in disease detection via pulse pattern.

Keywords

• Disease detection
• feature extraction
• preprocessing
• single electrode
• triboelectric nanogenerator
• wrist pulse