Power Spectrum Analysis

Abstract

In the analysis of EMG signal during dynamic movement, we have proposed an estimation algorithm for the time varying parameters. The parameters correspond to less biased time varying reflection coefficients. We determine the less biased estimation using a locally quasi-stationary model and name these parameters “K-parameters”. We estimated K-parametes upto the fifth order for the surface EMG signals of masseter muscle during rapid open-close movement of the lower jaw, a ballistics contraction, and fatigue. According to the results, the time causes of the K- parameters displayed remarkable properties. In order to study the behaviour of K-parameters physiologically, we produce a muscle-structured stimulation model based on anatomical and physiological data. The stimulation results suggested that the behaviour of the third parameter is related to the number of active motor units (MU's) at the shallow layer of a muscle.

Additional information

Notes on contributors

S P Patil

S P Patil, received BE (Electronics) in 1987 and ME (Electronics) in 1993 from Shivaji University, Kolhapur (Maharashtra).

He has eleven years of teaching experience. Presently working as Assistant Professor in Electronics Engineering in Rajaratnbapu Institute of Technology, Rajaramnagar (Sangli) & Head of Electrical Department. He is doing his PhD in electronics Engg. The topic of research is, “Neural Network Architecture for Automated Classification of Electromyograms.” He has more than 20 technical papers on his credit presented/publiched in national level conferences/journals. His areas of interest are biomedical signal processing, neural networks, fuzzy logic and microprocessor applications.

He is life member of ISTE, BMESI & IE.

S A Patil

S A Patil, has obtained his BE (Electronics) degree in 1987 & ME (Electronics) in 1995 from Shivaji University, Kolhapur (Maharashtra). Presently, he is doing his PhD in Electronics Engineering. His research topic is “ANN for Analysis of EEG, K- Complex detection & Identification of EEG power Spectra”.

He is working as Assistant Professor & Head of Electronics Engg Department in Rajarambapu Institute of Technology, Rajaramnagar (Maharashtra) since 1987. He has published/ presented more than 20 technical papers in various national level conferences and journals. His areas of interest are neural network based biomedical signal processing, artificial intelligance, and computerised automated systems.

Hi is life member of ISTE, BMESI & IE.