Brain-Controlled, AR-Based Home Automation System Using SSVEP-Based Brain-Computer Interface and EOG-Based Eye Tracker: A Feasibility Study for the Elderly End User

Abstract

Over the past decades, brain-computer interfaces (BCIs) have been developed to provide individuals with an alternative communication channel toward external environment. Although the primary target users of BCI technologies include the disabled or the elderly, most newly developed BCI applications have been tested with young, healthy people. In the present study, we developed an online home appliance control system using a steady-state visual evoked potential (SSVEP)-based BCI with visual stimulation presented in an augmented reality (AR) environment and electrooculogram (EOG)-based eye tracker. The performance and usability of the system were evaluated for individuals aged over 65. The participants turned on the AR-based home automation system using an eye-blink-based switch, and selected devices to control with three different methods depending on the user's preference. In the online experiment, all 13 participants successfully completed the designated tasks to control five home appliances using the proposed system, and the system usability scale exceeded 70. Furthermore, the BCI performance of the proposed online home appliance control system surpassed the best results of previously reported BCI systems for the elderly.

An N400 identification method based on the combination of Soft-DTW and transformer

“…Many studies have existed to fuse data from EEG with EEG as a way to improve the accuracy of interaction intent recognition. For example, Park et al (2022) developed an online BCI appliance control system based on steady-state visual evoked potentials (SSVEP) and electrooculography (EOG); Karimi and Shamsollahi (2022) proposed a fiducial ensemble (Fpz-Cz, Pz-Oz, and EOG) based on latent structural influence models (LSIMs) that exhibited some degree of performance improvement. Therefore, we decided to use both EOG data for classification.…”

Effects of Background Music on Mental Fatigue in Steady-State Visually Evoked Potential-Based BCIs

“…A brain–computer interface is a communication system between a human and a computer [ 1 ] that allows one to send information or commands from the human brain to the outside world without the need for peripheral neural and muscular activity. Brain–computer interfaces (BCIs) help users express thoughts and control external devices by monitoring their brain activity [ 2 , 3 ]. A variety of methods for monitoring brain activity can be used to acquire brain signals in BCI systems, including electroencephalography (EEG), functional near-infrared spectroscopy [ 4 , 5 , 6 ], functional magnetic resonance imaging [ 7 ], and magnetoencephalography [ 8 ].…”