Abstract
Brain–computer interfaces (BCIs) allow patients with paralysis to control external devices by mental commands. Recent advances in home automation and the Internet of things may extend the horizon of BCI applications into daily living environments at home. In this study, we developed an online BCI based on scalp electroencephalography (EEG) to control home appliances. The BCI users controlled TV channels, a digital door-lock system, and an electric light system in an unshielded environment. The BCI was designed to harness P300 and N200 components of event-related potentials (ERPs). On average, the BCI users could control TV channels with an accuracy of 83.0% ± 17.9%, the digital door-lock with 78.7% ± 16.2% accuracy, and the light with 80.0% ± 15.6% accuracy, respectively. Our study demonstrates a feasibility to control multiple home appliances using EEG-based BCIs.
Highlights
For the past decades, numerous attempts have been made to allow patients with paralysis, suffering from neurological disorders such as amyotrophic lateral sclerosis or spinal cord injury, to communicate with the external world using an electroencephalography (EEG)-based brain–computer interface (EEG-based Brain–computer interfaces (BCIs)) [1]
We examined the event-related potentials (ERPs) patterns generated during the BCI control of each home appliance
It is clearly shown that the target stimuli elicited large deflections with locally distributed
Summary
Numerous attempts have been made to allow patients with paralysis, suffering from neurological disorders such as amyotrophic lateral sclerosis or spinal cord injury, to communicate with the external world using an electroencephalography (EEG)-based brain–computer interface (EEG-based BCI) [1]. The proposed P300 BCI was extended further in terms of considering real-life scenarios, so it included an asynchronous mode to allow users to switch the environmental control system and selection of devices [22]. Another suggested arrangement of icons was a region-based paradigm (RBP) [23]. Considering the real-life situation of controlling home appliances, it is desirable that a user interface (UI) for BCIs shows both visual stimuli and the resulting operation of devices in a single screen. We evaluated the applicability of our online BCIs for controlling diverse home appliances in an unshielded environment
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