Biopotential eye tracking detects the eye position or gaze direction using electro-oculographic bioelectrical signals called EOG from the human skin near eyes. The objective is to design and implement an inexpensive human machine interface using these EOG signals. The project involves research, design and implementation of the interface along with software and hardware based applications. This work integrates biological signal acquisition, analog circuit design, digital signal processing, software programming, and bio-electrical engineering; to form a product with a wide range of applications including, but not limited to, those for the disabled and the paralyzed. The output signal of our project can be used for a diverse and vast range of applications and functions, both in the software and the hardware domains. In the health sector, not only can it be used extensively for the disabled and paralyzed by interfacing with wheelchairs, but also for the detection of eye saccade related syndromes. This work is centered on a new researched method for EOG signal processing using correlations.