Title: High-speed gesture modelling through boundary analysis of active signals from wearable data glove

Authors: Andrews Samraj; Ramesh Kumarasamy; Kalvina Rajendran; Karthik Selvaraj

Addresses: Mahendra Engineering College, Tamil Nadu, India ' Department of Computer Applications, Selvam College of Technology, Namakkal, Tamilnadu, India ' Enability Foundation for Rehabilitation, IIT Research Park, Chennai 600025, India ' Selvam College of Technology, Namakkal, Tamil Nadu, India

Abstract: Assistive technology utilises communication by means of gestures with high appreciation in the fields of rehabilitation engineering and security. The necessity for such technique is to extract the communications in terms of intentions from the disabled community. Such systems play a very crucial role during emergency as well as to perform regular communication during normal course of life. To interpret and communicate most distinctive requirements of the person with disability, the caregivers and medical support agents need a well- defined and distinguishable gesture paradigm with its recognition system. Conversion of such communicative gestures is to be made precise and easy. In this proposed work, the feature construction is made with a simple modelling of the gesture signals along the time zone considerations created during the gesture activity. The identification of most active channels for every subject involved in this experiment for different gestures contributes to reduction of complexity in processing and hardware cost.

Keywords: standard deviation; data glove; assistive technology; gesture modelling; wearable computing.

DOI: 10.1504/IJGUC.2019.10018232

International Journal of Grid and Utility Computing, 2019 Vol.10 No.1, pp.29 - 35

Received: 09 Dec 2017
Accepted: 04 Jul 2018

Published online: 24 Dec 2018 *

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