Abstract
Describes two robotic prosthetic eye prototype models. The first model uses an external infrared sensor array mounted on a frame of a pair of eyeglasses to detect natural eye movement and to feed the control system to drive the artificial eye to move with the natural eye. The second model uses human brain EOG (electrooculography) signals picked up by electrodes placed on both sides of a person's head to carry out the same eye movement detection and control tasks as mentioned above. Theoretical issues on sensor failure detection and recovery, and signal processing techniques used in sensor data fusion are studied using statistical methods and artificial neural network based techniques. In addition, practical control system design and implementation using micro controllers are studied and implemented to carry out the natural eye movement detection and artificial robotic eye control tasks.
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