Literature DB >> 28813949

Monitoring brain potentials to guide neurorehabilitation of tracking impairments.

Boris Yazmir, Miriam Reiner.   

Abstract

Motor impairments come in different forms. One class of motor impairments, relates to accuracy of tracking a moving object, as, for instance, when chasing in an attempt to catch it. Here we look at neural signals associated with errors in tracking, and the implications for brain-computer-interfaces that target impairment-tailored rehabilitation. As a starting point, we characterized EEG signals evoked by tracking errors during continuous natural motion, in healthy participants. Participants played a virtual 3D, ecologically valid haptic tennis game, and had to track a moving tennis ball in order to hit and send the ball towards the opponent's court. Sudden changes in the motion of the tennis ball elicited error related potentials. These were characterized by a negative peak at 135 msec and two positive peaks at 211 and 336 msec. The negative peak had a parietal scalp distribution, and the positive had a centro-frontal distribution. sLORETA source estimation for the peaks suggested brain activity in the somatosensory, motor, visual and anterior cingulate cortex. Implications are double: changes in the error potential characteristics provide an assessment strategy for rehabilitation; and the identified error potential can be used in the Brain computer interface feedback loop for tailored rehabilitation. Taken together, these results provide a methodology of rehabilitation systems specifically tailored to the unique impairment.

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Year:  2017        PMID: 28813949     DOI: 10.1109/ICORR.2017.8009377

Source DB:  PubMed          Journal:  IEEE Int Conf Rehabil Robot        ISSN: 1945-7898


  2 in total

1.  Effect of Virtual Reality on Balance Function in Children With Cerebral Palsy: A Systematic Review and Meta-analysis.

Authors:  Wei Liu; Yuanyan Hu; Junfeng Li; Jindong Chang
Journal:  Front Public Health       Date:  2022-04-25

2.  Characterizing and Removing Artifacts Using Dual-Layer EEG during Table Tennis.

Authors:  Amanda Studnicki; Ryan J Downey; Daniel P Ferris
Journal:  Sensors (Basel)       Date:  2022-08-05       Impact factor: 3.847

  2 in total

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