Virtual Booth

Nearly 10% of the global population—around 650 million people—live with physical disabilities and rely on wheelchairs. However, traditional wheelchairs often fail to accommodate users with limited upper limb mobility. This study proposes a gesture-controlled wheelchair using head movement recognition and machine learning-based hand gesture detection. Head gestures guide wheelchair direction, while hand gestures activate or deactivate the system. Built with Arduino Uno, DC motors, and an Osoyoo L293DD motor shield, the lightweight prototype supports up to 1kg. PyCharm handles gesture detection, while Arduino IDE manages motor control. The system improves accessibility and promotes greater independence for users with severe motor impairments.