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Monitoring Neuro-Motor Recovery From Stroke With High-Resolution EEG, Robotics and Virtual Reality: A Proof of Concept.

Authors :
Comani, Silvia
Velluto, Lucia
Schinaia, Lorenzo
Cerroni, Gianluigi
Serio, Antonio
Buzzelli, Sandro
Sorbi, Sandro
Guarnieri, Biancamaria
Source :
IEEE Transactions on Neural Systems & Rehabilitation Engineering; Nov2015, Vol. 23 Issue 6, p1106-1116, 11p
Publication Year :
2015

Abstract

A novel system for the neuro-motor rehabilitation of upper limbs was validated in three sub-acute post-stroke patients. The system permits synchronized cortical and kinematic measures by integrating high-resolution EEG, passive robotic device and Virtual Reality. The brain functional re-organization was monitored in association with motor patterns replicating activities of daily living (ADL). Patients underwent 13 rehabilitation sessions. At sessions 1, 7 and 13, clinical tests were administered to assess the level of motor impairment, and EEG was recorded during rehabilitation task execution. For each session and rehabilitation task, four kinematic indices of motor performance were calculated and compared with the outcome of clinical tests. Functional source maps were obtained from EEG data and projected on the real patients' anatomy (MRI data). Laterality indices were calculated for hemispheric dominance assessment. All patients showed increased participation in the rehabilitation process. Cortical activation changes during recovery were detected in relation to different motor patterns, hence verifying the system's suitability to add quantitative measures of motor performance and neural recovery to classical tests. We conclude that this system seems a promising tool for novel robot-based rehabilitation paradigms tailored to individual needs and neuro-motor responses of the patients. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15344320
Volume :
23
Issue :
6
Database :
Complementary Index
Journal :
IEEE Transactions on Neural Systems & Rehabilitation Engineering
Publication Type :
Academic Journal
Accession number :
110901784
Full Text :
https://doi.org/10.1109/TNSRE.2015.2425474