Classification of finger extension and flexion of EMG and Cyberglove data with modified ICA weight matrix

Ganesh R. Naik; Amit Acharyya; Hung T. Nguyen

doi:10.1109/EMBC.2014.6944458

Classification of finger extension and flexion of EMG and Cyberglove data with modified ICA weight matrix

Ganesh R. Naik, Amit Acharyya, Hung T. Nguyen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

25 Citations (Scopus)

Abstract

This paper reports the classification of finger flexion and extension of surface Electromyography (EMG) and Cyberglove data using the modified Independent Component Analysis (ICA) weight matrix. The finger flexion and extension data are processed through Principal Component Analysis (PCA), and next separated using modified ICA for each individual with customized weight matrix. The extension and flexion features of sEMG and Cyberglove (extracted from modified ICA) were classified using Linear Discriminant Analysis (LDA) with near 90% classification accuracy. The applications of this study include Human Computer Interface (HCI), virtual reality and neural prosthetics.

Original language	English
Title of host publication	2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3829-3832
Number of pages	4
ISBN (Electronic)	9781424479290
DOIs	https://doi.org/10.1109/EMBC.2014.6944458
Publication status	Published - 2 Nov 2014
Externally published	Yes
Event	2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 - Chicago, United States Duration: 26 Aug 2014 → 30 Aug 2014

Publication series

Name	2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014

Conference

Conference	2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Country/Territory	United States
City	Chicago
Period	26/08/14 → 30/08/14

Access to Document

10.1109/EMBC.2014.6944458

Cite this

Naik, G. R., Acharyya, A., & Nguyen, H. T. (2014). Classification of finger extension and flexion of EMG and Cyberglove data with modified ICA weight matrix. In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 (pp. 3829-3832). Article 6944458 (2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2014.6944458

Naik, Ganesh R. ; Acharyya, Amit ; Nguyen, Hung T. / Classification of finger extension and flexion of EMG and Cyberglove data with modified ICA weight matrix. 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 3829-3832 (2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014).

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title = "Classification of finger extension and flexion of EMG and Cyberglove data with modified ICA weight matrix",

abstract = "This paper reports the classification of finger flexion and extension of surface Electromyography (EMG) and Cyberglove data using the modified Independent Component Analysis (ICA) weight matrix. The finger flexion and extension data are processed through Principal Component Analysis (PCA), and next separated using modified ICA for each individual with customized weight matrix. The extension and flexion features of sEMG and Cyberglove (extracted from modified ICA) were classified using Linear Discriminant Analysis (LDA) with near 90% classification accuracy. The applications of this study include Human Computer Interface (HCI), virtual reality and neural prosthetics.",

author = "Naik, {Ganesh R.} and Amit Acharyya and Nguyen, {Hung T.}",

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doi = "10.1109/EMBC.2014.6944458",

language = "English",

series = "2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014",

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Naik, GR, Acharyya, A & Nguyen, HT 2014, Classification of finger extension and flexion of EMG and Cyberglove data with modified ICA weight matrix. in 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014., 6944458, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014, Institute of Electrical and Electronics Engineers Inc., pp. 3829-3832, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014, Chicago, United States, 26/08/14. https://doi.org/10.1109/EMBC.2014.6944458

Classification of finger extension and flexion of EMG and Cyberglove data with modified ICA weight matrix. / Naik, Ganesh R.; Acharyya, Amit; Nguyen, Hung T.
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 3829-3832 6944458 (2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - This paper reports the classification of finger flexion and extension of surface Electromyography (EMG) and Cyberglove data using the modified Independent Component Analysis (ICA) weight matrix. The finger flexion and extension data are processed through Principal Component Analysis (PCA), and next separated using modified ICA for each individual with customized weight matrix. The extension and flexion features of sEMG and Cyberglove (extracted from modified ICA) were classified using Linear Discriminant Analysis (LDA) with near 90% classification accuracy. The applications of this study include Human Computer Interface (HCI), virtual reality and neural prosthetics.

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Naik GR, Acharyya A, Nguyen HT. Classification of finger extension and flexion of EMG and Cyberglove data with modified ICA weight matrix. In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 3829-3832. 6944458. (2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014). doi: 10.1109/EMBC.2014.6944458

Classification of finger extension and flexion of EMG and Cyberglove data with modified ICA weight matrix

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