Intelligent Control Wheelchair Using a New Visual Joystick

Area of Science:

• Biomedical Engineering
• Artificial Intelligence
• Rehabilitation Technology

Background:

• Standard electric wheelchairs often require joystick manipulation, posing challenges for individuals with limited hand function.
• There is a need for intuitive and accessible control systems for patients with diverse physical disabilities.

Purpose of the Study:

• To develop and validate a novel hand gesture-controlled wheelchair (EWC) system.
• To provide an alternative mobility solution for patients unable to operate traditional wheelchairs.
• To enable real-time, variable-speed control of a wheelchair using hand gestures.

Main Methods:

• A camera-based system utilizing visual recognition algorithms and artificial intelligence software was implemented.
• A 3D environment simulator was used for initial safety and performance testing.
• The system was tested on real patients with various hand pathologies in a clinical setting.

Main Results:

• The hand gesture-controlled wheelchair (EWC) demonstrated successful real-time control based on recognized hand movements.
• The system allows for variable speed control, mimicking the functionality of a standard joystick.
• Low-cost implementation and positive results were observed during testing on patients.

Conclusions:

• The developed hand gesture-controlled wheelchair (EWC) system is a viable and effective solution for enhancing mobility in patients with hand impairments.
• The intelligent control system proved valid and reliable in clinical trials with diverse patient groups.
• This technology offers a promising, low-cost alternative for assistive mobility devices.