Wheelchair control for disabled patients using EMG/EOG based human machine interface: a review.

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Human-Machine Interface

Background:

• Bio-signals like EMG and EOG are crucial for controlling assistive devices.
• Existing research focuses on improving wheelchair control for individuals with severe disabilities.

Purpose of the Study:

• To review electromyogram (EMG) or electrooculogram (EOG) signal-based control systems for electric wheelchairs.
• To analyze technologies for signal capture, filtering, characterization, and classification in wheelchair control.

Main Methods:

• Systematic review of 70 EMG and 25 EOG studies published between 2000 and 2019.
• Analysis of signal processing techniques and control commands for wheelchair navigation.

Main Results:

• EMG and EOG signals provide effective control for wheelchair movement (turns, speed, stop).
• EOG signals are particularly useful for paralyzed individuals using eye movements.
• EMG signal characteristics are vital for specific wheelchair motions in amputees.

Conclusions:

• EMG and EOG based wheelchair control systems significantly enhance autonomy for people with disabilities.
• Further research in signal processing and HMI integration can optimize wheelchair functionality.