Unobtrusive head gesture based directional control system for patient mobility cart

This work is based upon the design and development of novel technique which involves real-time identification of the head gestures using camera. The system incorporates a unique directional control system for maneuvering patient cart based upon the commands generated by head gestures. The work involved design and development of customized patient cart, camera arm attached along with camera, and tablet computer. The gesture detection was done by face alignment technique developed using regression based supervised learning method. The algorithm efficiently detects roll, and pitch under unconstraint conditions such as natural head movements and variable illuminations which avoid any loss of performance and sensitivity. The system is unobtrusive in nature as the patient cart is controlled by using normal head gestures only with a remotely fixed camera at a distance from the subject. Ultrasonic sensors based collision warning detection was also incorporated for safety purposes. The system is tested in laboratory environment and its performance was found to be excellent and most helpful for the effective empowerment of quadriplegic patients who want to maneuver their mobility cart themselves by head gestures only.