Title :
Estimation of recruitment and firing rate in EMG signals
Author :
McGill, Kevin C. ; Kermani, Mahyar Zardoshti ; Lateva, Zoia C.
Author_Institution :
Rehabilitation R&D Center, Palo Alto VA Health Care Syst., CA, USA
fDate :
30 Oct-2 Nov 1997
Abstract :
We present a method for estimating the number of active motor units and the mean motor-unit firing rate for an intramuscularly recorded EMG signal. First, the motor-unit action potentials (MUAPs) are detected by high-pass filtering the signal and detecting all the spikes that exceed a threshold. Then the number of motor units, the mean number of spikes per MUAP, and the mean firing rate are computed using the autocorrelation of interspike intervals. Results from ten moderate-force EMG signals agree well with results obtained by computer-aided decomposition
Keywords :
electromyography; medical signal detection; medical signal processing; neurophysiology; parameter estimation; signal sampling; EMG signals; autocorrelation of interspike intervals; computer-aided decomposition; firing rate estimation; high-pass filtering; intramuscularly recorded signal; mean motor-unit firing rate; mean number of spikes; moderate-force signals; motor-unit action potentials; number of active motor units; parameter estimation; recruitment rate estimation; spikes detection; Autocorrelation; Electrodes; Electromyography; Filtering; Medical services; Needles; Quantum computing; Recruitment; Research and development; Signal detection;
Conference_Titel :
Engineering in Medicine and Biology Society, 1997. Proceedings of the 19th Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-4262-3
DOI :
10.1109/IEMBS.1997.756594
