Brain Controlled Wheelchair with Smart Feature
Noyon Kumar Sarkar, Moumita Roy, Md. Maniruzzaman

TL;DR
This paper presents a cost-effective, smart wheelchair controlled by EEG signals and eye blinks, integrating sensors for safety and automation to improve mobility for disabled individuals.
Contribution
It introduces an innovative EEG and eye-blink controlled wheelchair with integrated sensors for safety and automation, enhancing independence for users with disabilities.
Findings
Successful control of wheelchair via EEG and eye blinks
Integration of sensors for collision avoidance and hazard detection
Automatic alerts for fall detection and smoke hazards
Abstract
In Asia, many individuals with disabilities rely on wheelchairs for mobility. However, some people, such as those who are fully disabled or paralyzed, cannot use traditional wheelchairs despite having fully functioning cognitive abilities. To address this issue, we propose the development of an electric wheelchair that can be controlled using EEG signals and eye blinks. The project utilizes a MindWave Mobile device and Arduino to enable seamless control. Additionally, various sensors are incorporated to enhance the system's reliability. An ultrasonic sensor helps avoid unexpected collisions, while a smoke sensor detects hazardous smoke levels, triggering an automatic alert via a short message to a designated person. Similarly, if the passenger falls from the wheelchair, a notification will also be sent. The wheelchair's movement is controlled via an Android application, with eye-blink…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsGaze Tracking and Assistive Technology · EEG and Brain-Computer Interfaces
