NDLI: EEG-based Brain-Computer Interface to support post-stroke motor rehabilitation of the upper limb

Content Provider	IEEE Xplore Digital Library
Author	Cincotti, F. Pichiorri, F. Arico, P. Aloise, F. Leotta, F. de Vico Fallani, F. del R. Millan, J. Molinari, M. Mattia, D.
Copyright Year	2012
Description	Author affiliation: Exp. Neurorehabilitation Lab., Fondazione Santa Lucia, Rome, Italy (Molinari, M.) \|\| Neuroelectrical Imaging & BCI Lab, Fondazione Santa Lucia, Rome, Italy (Cincotti, F.; Pichiorri, F.; Arico, P.; Aloise, F.; Leotta, F.; de Vico Fallani, F.; Mattia, D.) \|\| Ecole Polytech. Fed. de Lausanne, Lausanne, Switzerland (del R Millan, J.)
Abstract	Brain-Computer Interfaces (BCIs) process brain activity in real time, and mediate non-muscular interaction between and individual and the environment. The subserving algorithms can be used to provide a quantitative measurement of physiological or pathological cognitive processes - such as Motor Imagery (MI) - and feed it back the user. In this paper we propose the clinical application of a BCI-based rehabilitation device, to promote motor recovery after stroke. The BCI-based device and the therapy exploiting its use follow the same principles that drive classical neuromotor rehabilitation, and (i) provides the physical therapist with a monitoring instrument, to assess the patient's participation in the rehabilitative cognitive exercise; (ii) assists the patient in the practice of MI. The device was installed in the ward of a rehabilitation hospital and a group of 29 patients were involved in its testing. Among them, eight have already undergone a one month training with the device, as an add-on to the regular therapy. An improved system, which includes analysis of Electromyographic (EMG) patterns and Functional Electrical Stimulation (FES) of the arm muscles, is also under clinical evaluation. We found that the rehabilitation exercise based on BCI mediated neurofeedback mechanisms enables a better engagement of motor areas with respect to motor imagery alone and thus it can promote neuroplasticity in brain regions affected by a cerebrovascular accident. Preliminary results also suggest that the functional outcome of motor rehabilitation may be improved by the use of the proposed device.
Sponsorship	IEEE Eng. Medicine Biol. Soc.
Starting Page	4112
Ending Page	4115
File Size	1275051
Page Count	4
File Format	PDF
ISBN	9781424441198
ISSN	1557170X
e-ISBN	9781457717871
DOI	10.1109/EMBC.2012.6346871
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Electroencephalography Electromyography Visualization Brain computer interfaces Neuroplasticity
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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