Continuous decoding of intention to move from contralesional hemisphere brain oscillations in severely affected chronic stroke patients

Javier M. Antelis, Luis Montesano, Ander Ramos-Murguialday, Niels Birbaumer, Javier Minguez

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Decoding motor information directly from brain activity is essential in robot-assisted rehabilitation systems to promote motor relearning. However, patients who suffered a stroke in the motor cortex have lost brain activity in the injured area, and consequently, mobility in contralateral limbs. Such a loss eliminates the possibility of extracting motor information from brain activity while the patient is undergoing therapy for the affected limb. This work proposes to decode motor information from EEG activity of the contralesional hemisphere in patients who suffered a hemiparetic stroke. Four stroke patients participated in this study and the results proved the feasibility of decoding motor information while patients attempted to move the affected limb.

Original languageEnglish
Title of host publicationProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Pages4099-4103
Number of pages5
DOIs
Publication statusPublished - 2012
Event34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States
Duration: Aug 28 2012Sep 1 2012

Other

Other34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
CountryUnited States
CitySan Diego, CA
Period8/28/129/1/12

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Fingerprint Dive into the research topics of 'Continuous decoding of intention to move from contralesional hemisphere brain oscillations in severely affected chronic stroke patients'. Together they form a unique fingerprint.

Cite this