Influence of Temporal and Frequency Selective Patterns Combined with CSP Layers on Performance in Exoskeleton-Assisted Motor Imagery Tasks.

Autor:	Guerrero-Mendez CD; Postgraduate Program in Electrical Engineering, Federal University of Espírito Santo (UFES), Vitoria 29075-910, Brazil; cblanco88@uan.edu.co (C.F.B.-D.); hamriver@gmail.com (H.R.-F.); pedro.ulhoa@edu.ufes.br (P.H.F.-U.); teodiano.bastos@ufes.br (T.F.B.-F.)., Blanco-Diaz CF; Postgraduate Program in Electrical Engineering, Federal University of Espírito Santo (UFES), Vitoria 29075-910, Brazil; cblanco88@uan.edu.co (C.F.B.-D.); hamriver@gmail.com (H.R.-F.); pedro.ulhoa@edu.ufes.br (P.H.F.-U.); teodiano.bastos@ufes.br (T.F.B.-F.)., Rivera-Flor H; Postgraduate Program in Electrical Engineering, Federal University of Espírito Santo (UFES), Vitoria 29075-910, Brazil; cblanco88@uan.edu.co (C.F.B.-D.); hamriver@gmail.com (H.R.-F.); pedro.ulhoa@edu.ufes.br (P.H.F.-U.); teodiano.bastos@ufes.br (T.F.B.-F.)., Fabriz-Ulhoa PH; Postgraduate Program in Electrical Engineering, Federal University of Espírito Santo (UFES), Vitoria 29075-910, Brazil; cblanco88@uan.edu.co (C.F.B.-D.); hamriver@gmail.com (H.R.-F.); pedro.ulhoa@edu.ufes.br (P.H.F.-U.); teodiano.bastos@ufes.br (T.F.B.-F.)., Fragoso-Dias EA; Graduate Program in Mechanical Engineering, Federal University of Espírito Santo (UFES), Vitoria 29075-910, Brazil; eduardo.a.dias@edu.ufes.br (E.A.F.-D.); rafhael.andrade@ufes.br (R.M.d.A.)., de Andrade RM; Graduate Program in Mechanical Engineering, Federal University of Espírito Santo (UFES), Vitoria 29075-910, Brazil; eduardo.a.dias@edu.ufes.br (E.A.F.-D.); rafhael.andrade@ufes.br (R.M.d.A.)., Delisle-Rodriguez D; Postgraduate Program in Neuroengineering, Santos Dumont Institute, Macaiba 59280-000, Brazil; denis.rodriguez@isd.org.br., Bastos-Filho TF; Postgraduate Program in Electrical Engineering, Federal University of Espírito Santo (UFES), Vitoria 29075-910, Brazil; cblanco88@uan.edu.co (C.F.B.-D.); hamriver@gmail.com (H.R.-F.); pedro.ulhoa@edu.ufes.br (P.H.F.-U.); teodiano.bastos@ufes.br (T.F.B.-F.).
Jazyk:	angličtina
Zdroj:	NeuroSci [NeuroSci] 2024 May 11; Vol. 5 (2), pp. 169-183. Date of Electronic Publication: 2024 May 11 (Print Publication: 2024).
DOI:	10.3390/neurosci5020012
Abstrakt:	Common Spatial Pattern (CSP) has been recognized as a standard and powerful method for the identification of Electroencephalography (EEG)-based Motor Imagery (MI) tasks when implementing brain-computer interface (BCI) systems towards the motor rehabilitation of lost movements. The combination of BCI systems with robotic systems, such as upper limb exoskeletons, has proven to be a reliable tool for neuromotor rehabilitation. Therefore, in this study, the effects of temporal and frequency segmentation combined with layer increase for spatial filtering were evaluated, using three variations of the CSP method for the identification of passive movement vs. MI+passive movement. The passive movements were generated using a left upper-limb exoskeleton to assist flexion/extension tasks at two speeds (high-85 rpm and low-30 rpm). Ten healthy subjects were evaluated in two recording sessions using Linear Discriminant Analysis (LDA) as a classifier, and accuracy (ACC) and False Positive Rate (FPR) as metrics. The results allow concluding that the use of temporal, frequency or spatial selective information does not significantly ( p < 0.05) improve task identification performance. Furthermore, dynamic temporal segmentation strategies may perform better than static segmentation tasks. The findings of this study are a starting point for the exploration of complex MI tasks and their application to neurorehabilitation, as well as the study of brain effects during exoskeleton-assisted MI tasks. Competing Interests: Conflicts of InterestThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (© 2024 by the authors.)
Databáze:	MEDLINE
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