DocumentCode :
3421535
Title :
The relationship between human cortico-muscular coherence and rectified EMG
Author :
Myers, L.J. ; O´Malley, M.
Author_Institution :
Dept. of Electron. & Electr. Eng., Univ. Coll. Dublin, Ireland
fYear :
2003
fDate :
20-22 March 2003
Firstpage :
289
Lastpage :
292
Abstract :
Rectification of the electromyographic (EMG) signal is a commonly used pre-processing procedure that allows detection of significant coherence between EMG and measured cortical signals. It has been demonstrated that rectification enhances mean group firing rates. This paper develops an efficient algorithm that may be used to extract these relevant frequencies. This method assumes the EMG to be a realization of a randomly distributed stationary process. Therefore the ´true´ power spectrum of this process will not contain specific timing information. However the power spectrum of the actual rectified EMG does contain timing information which is detectable at frequencies where it exceeds the analytic power spectrum. Coherence of measured electroencephalographic (EEG) signals and rectified EMG show that significant coherence peaks occur at the same frequencies obtained using the algorithm. Cortical drive appears to synchronize motor unit firings to particular frequencies that may be extracted from the rectified EMG alone. These frequencies are not easily obtained from either the EEG or the non-rectified EMG.
Keywords :
convolution; electroencephalography; electromyography; medical signal processing; spectral analysis; time series; EEG; Gaussian distribution functions; cortical drive; efficient algorithm; human cortico-muscular coherence; mean group firing rates; power spectrum; preprocessing procedure; randomly distributed stationary process; rectified EMG; rectified time series data; scaled convolutions; zero mean stationary random process; Autocorrelation; Data mining; Educational institutions; Electric variables measurement; Electroencephalography; Electromyography; Frequency; Humans; Synchronous motors; Timing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Engineering, 2003. Conference Proceedings. First International IEEE EMBS Conference on
Print_ISBN :
0-7803-7579-3
Type :
conf
DOI :
10.1109/CNE.2003.1196817
Filename :
1196817
Link To Document :
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