IAES International Journal of Robotics and Automation (IJRA)
Vol 2, No 1: March 2013

Electromyographic Grasp Recognition for a Five Fingered Robotic Hand

Nayan M. Kakoty (Tezpur University)
Mantoo Kaiborta (Tezpur University)
Shyamanta M. Hazarika (Tezpur University)

Article Info

Publish Date
01 Mar 2013

Abstract

This paper presents classification of grasp types based on surface electromyographic signals. Classification is through radial basis function kernel support vector machine using sum of wavelet decomposition coefficients of the EMG signals. In a study involving six subjects, we achieved an average recognition rate of 86%. The electromyographic grasp recognition together with a 8-bit microcontroller has been employed to control a fivefingered robotic hand to emulate six grasp types used during 70% daily living activities.

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Journal Info
IAES International Journal of Robotics and Automation (IJRA)
Website

Abbrev

IJRA

Publisher

Institute of Advanced Engineering and Science

Subject

Automotive Engineering Electrical & Electronics Engineering

Description

Robots are becoming part of people's everyday social lives and will increasingly become so. In future years, robots may become caretaker assistants for the elderly, or academic tutors for our children, or medical assistants, day care assistants, or psychological counselors. Robots may become our ...