EMG based classification of basic hand movements based on time frequency features

Christos Sapsanis, George Georgoulas, Antonios Tzes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes an integrated approach for the identification of daily hand movements with a view to control prosthetic members. The raw EMG signal is decomposed into Intrinsic Mode Functions (IMFs) with the use of Empirical Mode Decomposition (EMD). A number of features are extracted in time and in frequency domain. Two different dimentionality methods are tested, namely the Principal Component Analysis (PCA) technique and the RELIEF feature selection algorithm. The outputs of the dimensionality reduction stage are then fed to a linear classifier to perform the detection task. The approach was tested on a group of young individuals and the results appear promising.

Original languageEnglish (US)
Title of host publication2013 21st Mediterranean Conference on Control and Automation, MED 2013 - Conference Proceedings
Pages716-722
Number of pages7
DOIs
StatePublished - Oct 15 2013
Event2013 21st Mediterranean Conference on Control and Automation, MED 2013 - Platanias-Chania, Crete, Greece
Duration: Jun 25 2013Jun 28 2013

Other

Other2013 21st Mediterranean Conference on Control and Automation, MED 2013
CountryGreece
CityPlatanias-Chania, Crete
Period6/25/136/28/13

Fingerprint

Prosthetics
Principal component analysis
Feature extraction
Classifiers
Decomposition

Keywords

  • Biomedical signal analysis
  • Electromyography
  • Empirical Mode Decomposition
  • Pattern classification
  • Principal Component analysis
  • RELIEF feature selection

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

Cite this

Sapsanis, C., Georgoulas, G., & Tzes, A. (2013). EMG based classification of basic hand movements based on time frequency features. In 2013 21st Mediterranean Conference on Control and Automation, MED 2013 - Conference Proceedings (pp. 716-722). [6608802] https://doi.org/10.1109/MED.2013.6608802

EMG based classification of basic hand movements based on time frequency features. / Sapsanis, Christos; Georgoulas, George; Tzes, Antonios.

2013 21st Mediterranean Conference on Control and Automation, MED 2013 - Conference Proceedings. 2013. p. 716-722 6608802.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Sapsanis, C, Georgoulas, G & Tzes, A 2013, EMG based classification of basic hand movements based on time frequency features. in 2013 21st Mediterranean Conference on Control and Automation, MED 2013 - Conference Proceedings., 6608802, pp. 716-722, 2013 21st Mediterranean Conference on Control and Automation, MED 2013, Platanias-Chania, Crete, Greece, 6/25/13. https://doi.org/10.1109/MED.2013.6608802
Sapsanis C, Georgoulas G, Tzes A. EMG based classification of basic hand movements based on time frequency features. In 2013 21st Mediterranean Conference on Control and Automation, MED 2013 - Conference Proceedings. 2013. p. 716-722. 6608802 https://doi.org/10.1109/MED.2013.6608802
Sapsanis, Christos ; Georgoulas, George ; Tzes, Antonios. / EMG based classification of basic hand movements based on time frequency features. 2013 21st Mediterranean Conference on Control and Automation, MED 2013 - Conference Proceedings. 2013. pp. 716-722
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