Indirect Control of an Autonomous Wheelchair Using SSVEP BCI
Danny Wee-Kiat Ng and Sing Yau Goh
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman
Jalan Sungai Long, Bandar Sungai Long, Kajang, Selangor 43000, Malaysia
Having the capability to control a wheelchair using brain signals would be a major benefit to patients suffering from motor disabling diseases. However, one major challenge such systems are facing is the amount of input needed over time by the patient for control. Such a navigation control system results in a significant mental burden for the patient. The objective of this study is to develop a BCI system that requires a low number of inputs from a subject to operate. We propose an autonomous wheelchair that uses steady-state visual evoked potential based brain computer interfaces to achieve the objective. A dual mode system was implemented in this study to allow the autonomous wheelchair to work in both unknown and known environments. Robot operating system is used as the middleware in this study for the development of the algorithm to operate the wheelchair. The mental task for the subject using this wheelchair is reduced by relegating the responsibility of navigation control from the subject to the navigation software.
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