Review of Biomedical Signal-Based Control Systems for Electric Wheelchairs

Abstract

Mobility impairments significantly challenge independence and quality of life, especially for individuals who rely on wheelchairs. Recent advances in intelligent control systems for electric wheelchairs aim to address these challenges by enabling hands-free operation using biomedical signals. This review aims to provide a comprehensive overview of control strategies that utilize physiological and biological signals—such as head movements, voice commands, electroencephalogram, electrooculography, and electromyography—for wheelchair navigation. The study categorizes and compares these systems based on input modality, signal type, adaptability, and integration with soft computing techniques. Key findings highlight the strengths of multimodal approaches, the challenges posed by signal noise and user fatigue, and the need for improved real-world validation. By synthesizing the current research landscape, this review identifies future research directions focused on enhancing usability, safety, and accessibility in smart wheelchair technologies.