  The integration of brain-computer interfaces (BCIs) into the realm of smart
wheelchair (SW) technology signifies a notable leap forward in enhancing the
mobility and autonomy of individuals with physical disabilities. BCIs are a
technology that enables direct communication between the brain and external
devices. While BCIs systems offer remarkable opportunities for enhancing
human-computer interaction and providing mobility solutions for individuals
with disabilities, they also raise significant concerns regarding security,
safety, and privacy that have not been thoroughly addressed by researchers on a
large scale. Our research aims to enhance wheelchair control for individuals
with physical disabilities by leveraging electroencephalography (EEG) signals
for BCIs. We introduce a non-invasive BCI system that utilizes a neuro-signal
acquisition headset to capture EEG signals. These signals are obtained from
specific brain activities that individuals have been trained to produce,
allowing for precise control of the wheelchair. EEG-based BCIs are instrumental
in capturing the brain's electrical activity and translating these signals into
actionable commands. The primary objective of our study is to demonstrate the
system's capability to interpret EEG signals and decode specific thought
patterns or mental commands issued by the user. By doing so, it aims to convert
these into accurate control commands for the wheelchair. This process includes
the recognition of navigational intentions, such as moving forward, backward,
or executing turns, specifically tailored for wheelchair operation. Through
this innovative approach, we aim to create a seamless interface between the
user's cognitive intentions and the wheelchair's movements, enhancing autonomy
and mobility for individuals with physical disabilities.
