TY - GEN
T1 - Muscle activity onset detection using energy detectors
AU - Rasoo, Ghulam
AU - Iqbal, Kamran
PY - 2012/12/14
Y1 - 2012/12/14
N2 - Muscle activity detection is important for clinical investigations leading to the identification of neuromuscular disorders. Myoelectric signal recorded via electrodes placed at skin surface can reveal important muscle excitation information about underlying limb movement. However, a primary difficulty in the detection of muscle activity period from myoelectric signals lies in the inherent variability of these signals and the noise added during the collection process. In the literature, the double threshold detector has been commonly used for detection of the muscle activity periods from myoelectric signals. In this study, we propose a new scheme based on the log-likelihood ratio test to detect muscle activity periods accurately. This scheme uses energy information contained in the myoelectric signal, which increases with the start of the activity. We demonstrate the viability of energy detection scheme via successful detection performed on synthetic as well as clinical myoelectric signals.
AB - Muscle activity detection is important for clinical investigations leading to the identification of neuromuscular disorders. Myoelectric signal recorded via electrodes placed at skin surface can reveal important muscle excitation information about underlying limb movement. However, a primary difficulty in the detection of muscle activity period from myoelectric signals lies in the inherent variability of these signals and the noise added during the collection process. In the literature, the double threshold detector has been commonly used for detection of the muscle activity periods from myoelectric signals. In this study, we propose a new scheme based on the log-likelihood ratio test to detect muscle activity periods accurately. This scheme uses energy information contained in the myoelectric signal, which increases with the start of the activity. We demonstrate the viability of energy detection scheme via successful detection performed on synthetic as well as clinical myoelectric signals.
UR - http://www.scopus.com/inward/record.url?scp=84882980095&partnerID=8YFLogxK
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U2 - 10.1109/EMBC.2012.6346618
DO - 10.1109/EMBC.2012.6346618
M3 - Conference contribution
C2 - 23366579
AN - SCOPUS:84882980095
SN - 9781424441198
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 3094
EP - 3097
BT - 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012
T2 - 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
Y2 - 28 August 2012 through 1 September 2012
ER -