The tracking of eye gesture movements using wearable technologies can undoubtedly improve quality of life for people with mobility and physical impairments by using spintronic sensors based on the tunnel magnetoresistance (TMR) effect in a human-machine interface. Our design involves integrating three TMR sensors on an eyeglass frame for detecting relative movement between the sensor and tiny magnets embedded in an in-house fabricated contact lens. Using TMR sensors with the sensitivity of 11mV/V/Oe and ten <1 mm 3 embedded magnets within a lens, an eye gesture system was implemented with a sampling frequency of up to 28 Hz. Three discrete eye movements were successfully classified when a participant looked up, right or left using a threshold-based classifier. Moreover, our proof-ofconcept real-time interaction system was tested on 13 participants, who played a simplified Tetris game using their eye movements. Our results show that all participants were successful in completing the game with an average accuracy of 90.8%.