Movement identification based on exoskeleton sensor data for event marking of the electroencephalogram
Nils Eckardt, Marc Tabie, Anett Seeland, Elsa Andrea Kirchner, P. Rostalski
In Student Conference Proceedings 2016: 5th Conference on Medical Engineering Science and 1st Conference on Medical Informatics, 09.3.-11.3.2016, Lübeck, Infinite Science Publishing, pages 151-154, Mar/2016. ISBN: 3945954185.
Abstract
:
In this paper, the development of an algorithm for movement identification based on exoskeleton sensor data is described.
The exoskeleton is part of a project on post stroke rehabilitation. The algorithm shall be used to mark movement events
in a simultaneously recorded electroencephalography stream as a replacement for external motion tracking. The angular
values for each joint of the exoskeleton are utilized by the algorithm to calculate a threshold and decide, if a movement
was done or not. The quality of the algorithm is evaluated with an experiment, where the subject has to do specific movements
while wearing the exoskeleton. During the experiment, data from exoskeleton sensors, electroencephalography
and motion tracking is recorded. The provisional results show, that the algorithm is able to detect the movements, but the
threshold needs to be adapted to the status of the bearer. Subsequently, the algorithm gets embedded in a signal processing
framework.
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