Real-Time Brain-Computer Interface Control of a Wheelchair Using Motor Imagery Commands

The Brain-Computer Interface (BCI) field is rapidly growing and offers a wide range of uses in different domains, such as healthcare and daily life. This paper discusses the development of a wheelchair operated by BCI using Motor Imagery (MI) mental commands for turning left and right and blinking for stopping and starting. The Emotiv Insight is used to collect raw electroencephalography (EEG) data, while a Linear Discriminant Analysis (LDA) algorithm is used to classify the mental commands. OpenViBE software is employed to process and classify brain signals. The system is evaluated on 5 subjects in real-time, and 3 experiments are conducted to test starting, stopping, and turning. The results showed that the subjects can command the wheelchair operated by BCI with a high degree of nrecision.