Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Vol 1, No 2: June 2013

Artificial Neural Network based Body Posture Classification from EMG signal analysis

Rajesh Kumar Tripathy (NIT Rourkela,India)
Ashutosh Acharya (GIET,Bhubaneswar,India)
Sumit Kumar Choudhary (SIT,Bhubaneswar,India)
Santosh Kumar Sahoo (GITA,Bhubaneswar,India)

Article Info

Publish Date
11 Apr 2013

Abstract

 This paper deals with the body posture Classification from EMG signal analysis using artificial neural network (ANN). The various statistical features extracted from each EMG signal corresponding to different muscles associated with the different body postures are framed using LABVIEW software. Further-more, these features are taken as the input towards the ANN classifier and thus the corresponding output for the respective classifier predicts the postures like Bowing, Handshaking, and Hugging. The performance of the classifier is determined by the classification rate (CR). The outcome of result indicates that the CR of Multilayer Feed Forward Neural Network (MFNN) type of ANN is rounded up to a percentage of 71.02%.

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Journal Info
Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Website

Abbrev

IJEEI

Publisher

IAES Indonesia Section and Partners

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is a peer reviewed International Journal in English published four issues per year (March, June, September and December). The aim of Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is to publish high-quality ...