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

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.