Title :
Adaptive approach for change detection in EMG recordings
Author :
El Falou, W. ; Khalil, M. ; Duchêne, J.
Author_Institution :
Fac. of Eng. I, Lebanese Univ., Tripoli, Lebanon
Abstract :
In this paper we present a new algorithm to detect abrupt changes in a signal when there is no a priori knowledge of the hypotheses on the process to be detected. This algorithm is based on the CUSUM algorithm. It can be applied in case of frequency and energy changes. This algorithm works when the samples are dependent and autoregressive modeling is needed. It is used to distinguish EMG segments from noise segments.
Keywords :
adaptive signal detection; autoregressive processes; electromyography; medical signal detection; noise; CUSUM algorithm; EMG recordings; EMG segments; a priori knowledge; adaptive approach; autoregressive modeling; change detection; energy changes; frequency changes; likelihood ratio; noise segments; Biomedical signal processing; Change detection algorithms; Electromyography; Event detection; Frequency; Knowledge engineering; Probability density function; Signal processing; Signal processing algorithms; Signal to noise ratio;
Conference_Titel :
Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE
Print_ISBN :
0-7803-7211-5
DOI :
10.1109/IEMBS.2001.1020591
