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      Haptic Stimulation for Improving Training of a Motor Imagery BCI Developed for a Hand-Exoskeleton in Rehabilitation.

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          Abstract

          The use of robotic devices to provide active motor support and sensory feedback of ongoing motor intention, by means of a Brain Computer Interface (BCI), has received growing support by recent literature, with particular focus on neurorehabilitation therapies. At the same time, performance in the use of the BCI has become a more critical factor, since it directly influences congruency and consistency of the provided sensory feedback. As motor imagery is the mental simulation of a given movement without depending on residual function, training of patients in the use of motor imagery BCI can be extended beyond each rehabilitation session, and practiced by using simpler devices than rehabilitation robots available in the hospital. In this work, we investigated the use of haptic stimulation provided by vibrating electromagnetic motors to enhance BCI system training. The BCI is based on motor imagery of hand grasping and designed to operate a hand exoskeleton. We investigated whether haptic stimulation at fingerpads proves to be more effective than stimulation at wrist, already experimented in literature, due to the higher density of mechano-receptors. Our results did not show significant differences between the two body locations in BCI performance, yet a wider and more stable event-relateddesynchronization appeared for the finger-located stimulation. Future investigations will put in relation training with haptic feedback at fingerpads with BCI performance using the handexoskeleton, in grasping tasks that naturally involve haptic feedback at fingerpads.

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          Author and article information

          Journal
          IEEE Int Conf Rehabil Robot
          IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
          Institute of Electrical and Electronics Engineers (IEEE)
          1945-7901
          1945-7898
          June 2019
          : 2019
          Article
          10.1109/ICORR.2019.8779370
          31374781
          b84d52d3-4d08-40b3-81c5-2aea5e10b3f3
          History

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