The grasp detected: Time domain classification of grasp and hold tasks

Andreas Schwarz, Patrick Ofner, Joana Pereira, Gernot Müller-Putz

Research output: Contribution to conferencePosterpeer-review


Brain-Computer Interfaces (BCIs) enable its users to interact with their environment only by thought. Earlier studies indicated [1, 2] that
BCI might be a suitable method for controlling a neuroprostheses, which could assist people with spinal cord injuries (SCI) in their daily life. One
drawback for the end user is that only simple motor imaginations (MI) are available for control e.g. MI of both feet to control ones arm is abstract
and in contradiction to an associated natural movement. Therefore we are looking for means to design a more natural control modality. One
promising scenario would be to use MI of different grasps to actually control different grasps of the neuroprosthesis. In this study we
attempt to classify the execution of different grasp types in low-frequency time-domain EEG signals.
Original languageEnglish
Publication statusPublished - 1 Jun 2016
Event6th International BCI Meeting - Pacific Grove, CA, Asilomar, United States
Duration: 30 May 20163 Jun 2016


Conference6th International BCI Meeting
Country/TerritoryUnited States


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