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- W4283726916 abstract "Disability limits an individual's ability to participate in everyday activities. Rehabilitation is specialized healthcare to improve, maintain or restore physical strength, cognition, and mobility. Exoskeletons are the external devices used to aid the disabled in performing daily life activities and restoring their strength and capability. Brain-computer interface (BCI) is a technique to use brain signals in controlling external devices directly. In this paper, BCI-based control of the lower limb exoskeleton is proposed using functional near-infrared spectroscopy (fNIRS). Brain signals for waking nine healthy subjects on a treadmill are recorded and pre-processed, followed by channel selection and feature extraction. Linear discriminant analysis is used to classify walking and rest signals and achieved significantly (p < 0.05) higher accuracy of 75.5 ± 13.0%. Furthermore, the proposed system showed better performance as compared to using all channels for classification. The better performance of the proposed methodology is a step forward to achieve intuitive control of BCI-based exoskeletons." @default.
- W4283726916 created "2022-07-01" @default.
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- W4283726916 date "2022-05-17" @default.
- W4283726916 modified "2023-09-23" @default.
- W4283726916 title "Brain-Controlled Lower-Limb Exoskeleton to Assist Elderly and Disabled" @default.
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- W4283726916 doi "https://doi.org/10.1109/codit55151.2022.9804050" @default.
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