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Content Provider | IEEE Xplore Digital Library |
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Author | Parsaei, H. Stashuk, D.W. |
Copyright Year | 2009 |
Description | Author affiliation: Systems Design Engineering Department University of Waterloo, ON, Canada (Parsaei, H.; Stashuk, D.W.) |
Abstract | A method using the gap statistic is proposed to evaluate the validity of a motor unit potential train (MUPT) in terms of motor unit potential (MUP) shape consistency. This algorithm determines whether the MUPs of a given MUPT are homogeneous in terms of their shapes or not. It also checks if there are gaps in the inter-discharge interval (IDI) train of the given MUPT. If the MUPs are not homogeneous or if there is a temporal gap in the MUPT, the given MUPT is split into valid trains. To overcome MUP shape variability caused by jitter or needle movement during signal detection, similar MUPTs are merged if the resulting merged train is a valid train. Experimental results using simulated EMG signals show that the accuracy of the developed method in determining valid MUPTs and invalid MUPTs correctly is 97.58% and 99.33% on average, respectively. This performance encourages the use of this method for automated validation of MUPTs. |
Starting Page | 2551 |
Ending Page | 2554 |
File Size | 431819 |
Page Count | 4 |
File Format | |
ISBN | 9781424432967 |
ISSN | 1557170X |
DOI | 10.1109/IEMBS.2009.5334758 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2009-09-03 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Electromyography Shape Signal resolution Electrodes Signal processing algorithms Signal detection Needles Data mining Neuromuscular USA Councils |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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