Human–machine interaction for motorized wheelchair based on single-channel electroencephalogram headband

Abstract

Human machine interaction (HMI) allows persons to control and interact with devices. Starting from elementary apparatus which acquires input bio-signals to controlling various applications. Medical applications are amongst the very important applications of HMI. One of these medical applications is assisting fully/partially paralyzed patients to restore movements or freely move using exoskeletons or motorized wheelchairs. Helping patients with spinal cord injury or serious neurological diseases to restore their movements is a key role objective for most researchers in this field. In this paper, an EEG-based HMI system is proposed to assist patients with tetraplegia/quadriplegia to mentally control a motorized wheelchair so they can move freely and independently. EEG power spectrum (α, β, δ, θ, and γ) from the frontal lobe of brain is recorded, filtered and wirelessly sent to the wheelchair to control directions and engine status. Four different experiments were conducted using the proposed system in order to validate the performance. Two different GUIs scenarios (cross-shaped and horizontal bar) were used with the experiments. Results showed that the horizontal bar scenario considered more user friendly while the cross-shaped is the more suitable for navigation. The implemented system can be equipped with modules and sensors such as GPS, ultrasound and accelerometer that improve the system performance and reliability.