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Erschienen in: Cognitive Neurodynamics 5/2014

01.10.2014 | Research Article

An asynchronous wheelchair control by hybrid EEG–EOG brain–computer interface

verfasst von: Hongtao Wang, Yuanqing Li, Jinyi Long, Tianyou Yu, Zhenghui Gu

Erschienen in: Cognitive Neurodynamics | Ausgabe 5/2014

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Abstract

Wheelchair control requires multiple degrees of freedom and fast intention detection, which makes electroencephalography (EEG)-based wheelchair control a big challenge. In our previous study, we have achieved direction (turning left and right) and speed (acceleration and deceleration) control of a wheelchair using a hybrid brain–computer interface (BCI) combining motor imagery and P300 potentials. In this paper, we proposed hybrid EEG-EOG BCI, which combines motor imagery, P300 potentials, and eye blinking to implement forward, backward, and stop control of a wheelchair. By performing relevant activities, users (e.g., those with amyotrophic lateral sclerosis and locked-in syndrome) can navigate the wheelchair with seven steering behaviors. Experimental results on four healthy subjects not only demonstrate the efficiency and robustness of our brain-controlled wheelchair system but also indicate that all the four subjects could control the wheelchair spontaneously and efficiently without any other assistance (e.g., an automatic navigation system).

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Metadaten
Titel
An asynchronous wheelchair control by hybrid EEG–EOG brain–computer interface
verfasst von
Hongtao Wang
Yuanqing Li
Jinyi Long
Tianyou Yu
Zhenghui Gu
Publikationsdatum
01.10.2014
Verlag
Springer Netherlands
Erschienen in
Cognitive Neurodynamics / Ausgabe 5/2014
Print ISSN: 1871-4080
Elektronische ISSN: 1871-4099
DOI
https://doi.org/10.1007/s11571-014-9296-y

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