Abstract:
We analyzed the sensitivity of Non-negative Matrix Factorization (NMF) of dynamic surface electromyograms (EMG) to muscle shortening. We first identified Motor unit actio...Show MoreMetadata
Abstract:
We analyzed the sensitivity of Non-negative Matrix Factorization (NMF) of dynamic surface electromyograms (EMG) to muscle shortening. We first identified Motor unit action potentials (MUAPs) by decomposing experimentally recorded EMG signals during slow shortening of biceps brachii muscle in five young healthy males. We then used these MUAPs to generate different synthetic EMG signals with different muscle shortening and excitation profiles. Afterwards, we applied NMF to the synthetic EMG signals and calculated Pearson correlation coefficient (CC) between the extracted NMF components and a) muscle shortening and b) muscle excitation profiles. The results demonstrated good match between NMF components and muscle excitation profiles, but only when the muscle excitation level changed for at least 10 % during the muscle shortening. During constant muscle excitation, the resulting NMF components correlated significantly with the muscle shortening profiles. These results demonstrate that NMF components reflect not only the muscle excitation profiles but also muscle shortening profiles. Therefore, the results of NMF analysis of dynamic EMG signals need to be interpreted with caution.
Published in: 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Date of Conference: 18-21 July 2018
Date Added to IEEE Xplore: 28 October 2018
ISBN Information:
ISSN Information:
PubMed ID: 30441696