Detection of Attempted Stroke Hand Motions from Surface EMG

Authors :: Jochumsen, Mads Rovsing
Waris, Asim
Niazi, Imran Khan
Source :: Jochumsen, M R, Waris, A & Niazi, I K 2022, Detection of Attempted Stroke Hand Motions from Surface EMG . in Converging Clinical and Engineering Research on Neurorehabilitation IV : Proceedings of the 5th International Conference on Neurorehabilitation (ICNR2020), October 13–16, 2020 . Springer, Biosystems and Biorobotics, vol. 28, pp. 47-52, 5th International Conference on NeuroRehabilitation, Vigo, Spain, 13/10/2020 . https://doi.org/10.1007/978-3-030-70316-5_8
Publication Year :: 2022
Publisher :: Springer, 2022.
Abstract: Brain-Computer Interfaces have been proposed for stroke rehabilitation, but a potential problem with this technology is the dependence of high-quality brain signals. The aim of this study was to investigate if attempted hand open motions can be detected from the muscle activity instead. Ten stroke patients performed 63 ± 7 attempted movements while three channels of EMG were recorded. Hudgins time-domain features and linear discriminant analysis were used, and 92 ± 3% of the movement activity was correctly classified. The Spearman correlation between the upper limb Fugl-Meyer score and the classification accuracies was 0.58 (P = 0.08). In conclusion, attempted movements from stroke patients can be detected using EMG.

Language :: English
Database :: OpenAIRE
Journal :: Jochumsen, M R, Waris, A & Niazi, I K 2022, Detection of Attempted Stroke Hand Motions from Surface EMG . in Converging Clinical and Engineering Research on Neurorehabilitation IV : Proceedings of the 5th International Conference on Neurorehabilitation (ICNR2020), October 13–16, 2020 . Springer, Biosystems and Biorobotics, vol. 28, pp. 47-52, 5th International Conference on NeuroRehabilitation, Vigo, Spain, 13/10/2020 . https://doi.org/10.1007/978-3-030-70316-5_8
Accession number :: edsair.dedup.wf.001..46c992e49cae1d6282cda873c1b803a4
Full Text :: https://doi.org/10.1007/978-3-030-70316-5_8