Improving EMG based classification of basic hand movements using EMD

Author

Sapsanis, Christos ; Georgoulas, George ; Tzes, Anthony ; Lymberopoulos, Dimitrios

Author_Institution

Dept. of Electr. & Comput. Eng., Univ. of Patras, Patras, Greece

fYear

2013

fDate

3-7 July 2013

Firstpage

5754

Lastpage

5757

Abstract

This paper presents a pattern recognition approach for the identification of basic hand movements using surface electromyographic (EMG) data. The EMG signal is decomposed using Empirical Mode Decomposition (EMD) into Intrinsic Mode Functions (IMFs) and subsequently a feature extraction stage takes place. Various combinations of feature subsets are tested using a simple linear classifier for the detection task. Our results suggest that the use of EMD can increase the discrimination ability of the conventional feature sets extracted from the raw EMG signal.

Keywords

electromyography; feature extraction; medical signal processing; signal classification; EMD approach; EMG based classification; Empirical Mode Decomposition; Intrinsic Mode Functions; basic hand movements; feature extraction; linear classifier; pattern recognition approach; surface electromyographic data; Biosensors; Electrodes; Electromyography; Empirical mode decomposition; Feature extraction; Muscles; Pattern recognition; Biomedical signal analysis; Empirical Mode Decomposition (EMD); electromyography (EMG); pattern classification;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE

Conference_Location

Osaka

ISSN

1557-170X

Type

conf

DOI

10.1109/EMBC.2013.6610858

Filename

6610858