Capacitive eye tracker made of fractured carbon nanotube-paper composites for wearable applications

The uniqueness of eyes, facial geometry, and gaze direction makes eye tracking a very challenging technological pursuit. Although camera-based eye-tracking systems are popular, the obtrusiveness of their bulky equipment along with their high computational cost and power consumption is considered problematic for wearable applications. Noncontact gaze monitoring using capacitive sensing technique has been attempted but failed due to low sensitivity and parasitic capacitance. Here, we study the interaction between a novel capacitive sensor and eye movement for wearable eye-tracking. The capacitive sensors are made of a pair of asymmetric electrodes; one comprising carbon nanotube-paper composite fibers (CPC) and the other being a rectangular metal electrode. The interaction between the asymmetric sensor and a spherical object mimicking an eyeball is analyzed numerically. Using a face simulator, both single- and differential capacitive measurements are characterized with respect to proximity, geometry, and human body charge. Using a prototype eye tracker, multiple sensor locations are studied to determine the optimal configurations. The capacitive responses to vertical and horizontal gaze directions are analyzed in comparison to those of a commercial eye tracking system. The performance is demonstrated for sensitive eye-movement tracking, closed-eye monitoring, and human-machine interface. This research has important implications for the development of capacitive, wearable eye trackers, which can facilitate fields of human-machine interface, cognitive monitoring, neuroscience research, and rehabilitation.