Limitations and applications of ICA for surface electromyogram

Ganesh R. Naik; Dinesh K. Kumar; Sridhar P. Arjunan; M. Palaniswami; Rezaul Begg

doi:10.1109/IEMBS.2006.259844

Limitations and applications of ICA for surface electromyogram

Ganesh R. Naik
, Dinesh K. Kumar
, Sridhar P. Arjunan
, M. Palaniswami
, Rezaul Begg

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

9 Citations (Scopus)

Abstract

This paper reports research conducted to evaluate the use of sparse ICA for the separation of muscle activity from SEMG. It discusses some of the conditions that could affect the reliability of the separation and evaluates Issues related to the properties of the signals and number of sources. The paper reports tests using Zibulevsky's method of temporal plotting to Identify number of Independent sources In SEMG recordings. The theoretical analysis and experimental results demonstrate that sparse ICA Is not suitable for SEMG signals. The results Identify that the technique Is unable to Identify finite number of active muscles. The work demonstrates that even at extremely low level of muscle contraction, and with filtering using wavelets and band pass filters, It Is not possible to get the data sparse enough to Identify number of Independent sources using Zibulevsky's sparse decomposition technique

Original language	English
Title of host publication	2006 International Conference of the IEEE Engineering in Medicine and Biology Society
Place of Publication	New York, NY
Publisher	Institute of Electrical and Electronics Engineers
Pages	5739-5742
Number of pages	4
ISBN (Print)	1424400325, 9781424400324
DOIs	https://doi.org/10.1109/IEMBS.2006.259844
Publication status	Published - 2006
Externally published	Yes
Event	28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06 - New York, NY, United States Duration: 30 Aug 2006 → 3 Sept 2006

Conference

Conference	28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
Country/Territory	United States
City	New York, NY
Period	30/08/06 → 3/09/06

Access to Document

10.1109/IEMBS.2006.259844Licence: In Copyright

Cite this

@inproceedings{6813798ab78e4cc59b70eab5062945b9,

title = "Limitations and applications of ICA for surface electromyogram",

abstract = "This paper reports research conducted to evaluate the use of sparse ICA for the separation of muscle activity from SEMG. It discusses some of the conditions that could affect the reliability of the separation and evaluates Issues related to the properties of the signals and number of sources. The paper reports tests using Zibulevsky's method of temporal plotting to Identify number of Independent sources In SEMG recordings. The theoretical analysis and experimental results demonstrate that sparse ICA Is not suitable for SEMG signals. The results Identify that the technique Is unable to Identify finite number of active muscles. The work demonstrates that even at extremely low level of muscle contraction, and with filtering using wavelets and band pass filters, It Is not possible to get the data sparse enough to Identify number of Independent sources using Zibulevsky's sparse decomposition technique",

author = "Naik, \{Ganesh R.\} and Kumar, \{Dinesh K.\} and Arjunan, \{Sridhar P.\} and M. Palaniswami and Rezaul Begg",

year = "2006",

doi = "10.1109/IEMBS.2006.259844",

language = "English",

isbn = "1424400325",

pages = "5739--5742",

booktitle = "2006 International Conference of the IEEE Engineering in Medicine and Biology Society",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06 ; Conference date: 30-08-2006 Through 03-09-2006",

}

Naik, GR, Kumar, DK, Arjunan, SP, Palaniswami, M & Begg, R 2006, Limitations and applications of ICA for surface electromyogram. in 2006 International Conference of the IEEE Engineering in Medicine and Biology Society., 4030002, Institute of Electrical and Electronics Engineers, New York, NY, pp. 5739-5742, 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06, New York, NY, United States, 30/08/06. https://doi.org/10.1109/IEMBS.2006.259844

Limitations and applications of ICA for surface electromyogram. / Naik, Ganesh R.; Kumar, Dinesh K.; Arjunan, Sridhar P. et al.
2006 International Conference of the IEEE Engineering in Medicine and Biology Society. New York, NY: Institute of Electrical and Electronics Engineers, 2006. p. 5739-5742 4030002.

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

TY - GEN

T1 - Limitations and applications of ICA for surface electromyogram

AU - Naik, Ganesh R.

AU - Kumar, Dinesh K.

AU - Arjunan, Sridhar P.

AU - Palaniswami, M.

AU - Begg, Rezaul

PY - 2006

Y1 - 2006

N2 - This paper reports research conducted to evaluate the use of sparse ICA for the separation of muscle activity from SEMG. It discusses some of the conditions that could affect the reliability of the separation and evaluates Issues related to the properties of the signals and number of sources. The paper reports tests using Zibulevsky's method of temporal plotting to Identify number of Independent sources In SEMG recordings. The theoretical analysis and experimental results demonstrate that sparse ICA Is not suitable for SEMG signals. The results Identify that the technique Is unable to Identify finite number of active muscles. The work demonstrates that even at extremely low level of muscle contraction, and with filtering using wavelets and band pass filters, It Is not possible to get the data sparse enough to Identify number of Independent sources using Zibulevsky's sparse decomposition technique

AB - This paper reports research conducted to evaluate the use of sparse ICA for the separation of muscle activity from SEMG. It discusses some of the conditions that could affect the reliability of the separation and evaluates Issues related to the properties of the signals and number of sources. The paper reports tests using Zibulevsky's method of temporal plotting to Identify number of Independent sources In SEMG recordings. The theoretical analysis and experimental results demonstrate that sparse ICA Is not suitable for SEMG signals. The results Identify that the technique Is unable to Identify finite number of active muscles. The work demonstrates that even at extremely low level of muscle contraction, and with filtering using wavelets and band pass filters, It Is not possible to get the data sparse enough to Identify number of Independent sources using Zibulevsky's sparse decomposition technique

UR - https://www.scopus.com/pages/publications/34047094883

U2 - 10.1109/IEMBS.2006.259844

DO - 10.1109/IEMBS.2006.259844

M3 - Conference contribution

C2 - 17946718

AN - SCOPUS:34047094883

SN - 1424400325

SN - 9781424400324

SP - 5739

EP - 5742

BT - 2006 International Conference of the IEEE Engineering in Medicine and Biology Society

PB - Institute of Electrical and Electronics Engineers

CY - New York, NY

T2 - 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06

Y2 - 30 August 2006 through 3 September 2006

ER -

Limitations and applications of ICA for surface electromyogram

Abstract

Conference

Access to Document

Other files and links

Fingerprint

Cite this