TY - GEN
T1 - Identification of independent biological sensors-electromyogram example
AU - Naik, Ganesh R.
AU - Kumar, Dinesh K.
AU - Palaniswami, Marimuthu
PY - 2008
Y1 - 2008
N2 - To ensure that no biological event that may be important is missed, redundancy of sensors is provided. While this is useful, there are shortcomings when there is need to separate the signals from different sources using blind source separation techniques. An example of such a situation is over-complete surface electromyogram (sEMG) recording. Techniques such as principal component analysis (PCA) and entropy measures are used to identify the suitable channels. The shortcomings in these are the need for prior estimation of the number of channels. This paper has used the determinant of the global matrix of the mixtures to determine the number of independent sources in a mixture. The results indicate that the technique is able to distinguish between dependent and independent channels and this may be applied for determining the number of independent sources. The applications of this include data reduction by identifying redundant data, and for pre-processing of the data prior to use of any data classification techniques.
AB - To ensure that no biological event that may be important is missed, redundancy of sensors is provided. While this is useful, there are shortcomings when there is need to separate the signals from different sources using blind source separation techniques. An example of such a situation is over-complete surface electromyogram (sEMG) recording. Techniques such as principal component analysis (PCA) and entropy measures are used to identify the suitable channels. The shortcomings in these are the need for prior estimation of the number of channels. This paper has used the determinant of the global matrix of the mixtures to determine the number of independent sources in a mixture. The results indicate that the technique is able to distinguish between dependent and independent channels and this may be applied for determining the number of independent sources. The applications of this include data reduction by identifying redundant data, and for pre-processing of the data prior to use of any data classification techniques.
UR - http://www.scopus.com/inward/record.url?scp=61849147274&partnerID=8YFLogxK
U2 - 10.1109/iembs.2008.4649355
DO - 10.1109/iembs.2008.4649355
M3 - Conference contribution
C2 - 19162858
AN - SCOPUS:61849147274
SN - 9781424418152
T3 - Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"
SP - 1112
EP - 1115
BT - 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
PB - IEEE
CY - Vancouver, BC
T2 - 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Y2 - 20 August 2008 through 25 August 2008
ER -