Time domain classification of grasp and hold tasks

Andreas Schwarz

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-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
Title of host publicationProceedings of the Sixth International Brain-Computer Interface Meeting: BCI Past, Present and Future
EditorsGernot R. Müller-Putz, Jane E. Huggins, David Steyrl
PublisherVerlag der Technischen Universität Graz
Number of pages1
ISBN (Print)978-3-85125-467-9
Publication statusPublished - 1 Jun 2016
Event6th International Brain-Computer Interface Meeting 2016 - Pacific Grove, California, Asilomar Conference Center, United States
Duration: 30 May 20163 Jun 2016


Conference6th International Brain-Computer Interface Meeting 2016
Country/TerritoryUnited States
CityAsilomar Conference Center

Fields of Expertise

  • Human- & Biotechnology

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