Abstract
We propose a system for the EEG-EOG-EMG recording in stroke subjects during robotic rehabilitation task. This system was designed for obtaining safe recording conditions, high-quality data, triggering signals to track the task and to align EEG segments to motor performance, friendly visualization and management of the data during the signal acquisition and subsequent analysis.
We recorded EEG data from a stroke subject during resting state and robotic rehabilitation task before and after a program of 30 sessions.
Results showed high-quality EEG data recorded in the 4 patients with about 80% of artifact-free EEG epochs during robotic performance.
Globally, the relatively high percentage of artifact-free EEG epochs represents a good first index of the quality of the EEG recordings. Furthermore, the analysis of EEG power density spectrum revealed typical features of human cortical EEG oscillatory activity during resting state and engaging events.
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Sale, P. (2019). Use of EEG Signal Information to Optimize Training and Promote Plasticity. In: Masia, L., Micera, S., Akay, M., Pons, J. (eds) Converging Clinical and Engineering Research on Neurorehabilitation III. ICNR 2018. Biosystems & Biorobotics, vol 21. Springer, Cham. https://doi.org/10.1007/978-3-030-01845-0_43
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DOI: https://doi.org/10.1007/978-3-030-01845-0_43
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