Control and Automation of AI Based Brain Controlled Wheelchair for Paralyzed Patients

Abstract

Smart Wheelchairs play an important role in assisting individuals with disabilities, particularly those with motor impairments due to conditions like strokes or multiple sclerosis. This research focuses on developing a Brain Controlled Wheelchair (BCW) system using non-invasive EEG technology to empower individuals with severe mobility impairments. The study emphasizes the use of the NeuroSky EEG, which offers advantages over traditional systems by being more compact, user-friendly, cost-effective, and providing real-time signal processing with enhanced accuracy and minimal setup. The objectives include designing a robust EEG signal acquisition system, classifying EEG signals into actionable commands, exploring advancements in EEG electrode technology, and evaluating a BCW prototype for performance metrics. This system provides natural control of the wheelchair according to the user's brainwave patterns, presenting an alternate method of navigation without intricate electronics, rendering it easier and more reliable. This research introduces the BCW as a novel solution for the disabled, enhancing mobility and autonomy while solving issues related to safety and comfort.