Rui Zhang, Qihong Wang and Kai Li present a BCI-based environmental control system that integrates household electrical appliances, a nursing bed, and an intelligent wheelchair with automated navigation function. Synchronous and asynchronous control modes are employed in different situations to provide more natural and practical control. Specifically, the asynchronous mode, which can infer from the ongoing EEG whether the user intends to execute his/her control through the BCI, is for switching the environmental control system on or off or for selecting a device (e.g., a TV) to control.
Furthermore, a verification mechanism and several pseudo-keys are introduced into our paradigm to effectively reduce false operations in the asynchronous mode. Once a device is switched on, the synchronous mode, generally with a higher BCI detection performance of accuracy and speed than the asynchronous mode, is used for function selection, such as channel selection for a TV. Two experiments involving six paralyzed patients with severe spinal cord injuries (SCIs) were separately carried out in a nursing bed and a wheelchair. Experimental results indicated that all the SCI patients could operate the household electrical appliances, the nursing bed and the intelligent wheelchair by using the BCI with satisfactory. The proposed environmental control system can thus be used to assist severely paralyzed people with SCIs in their daily life and improve their self-care abilities.
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