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.
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This work was funded by VELUX FONDEN (project no. 22357).
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Jochumsen, M., Waris, A., Niazi, I.K. (2022). Detection of Attempted Stroke Hand Motions from Surface EMG. In: Torricelli, D., Akay, M., Pons, J.L. (eds) Converging Clinical and Engineering Research on Neurorehabilitation IV. ICNR 2020. Biosystems & Biorobotics, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-030-70316-5_8
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DOI: https://doi.org/10.1007/978-3-030-70316-5_8
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