Abstract

Eye movement detection is widely applied to safety driving areas for reducing the traffic accidents, which is related with the acquisition of different kinds of electrophysiological signals. Soft multi-functional electronic skin (SMFES) is created to collect skin temperature, sweating, and electrooculogram (EOG) signals simultaneously for drivers’ eye movement monitoring, which is conformal contact with the surface of skin for more stable and accurate biological data. The feature signals are extracted with different eye movements by SMFES which is helpful to recognize drivers’ eye movements and to predict the fatigue driving behaviors. Adaptive neuro fuzzy inference system (ANFIS) model is built to classify and recognize the typical eye movements for devoting the relationship between the eye movements (‘Up’, ‘Down’, ‘Left’, and ‘Right’) and the physiological signals. This work demonstrates an intelligent recognition algorithm embedded into SMFES seamlessly with existing driving environment for eye motion detection, expanding the applications of SMFES in safety driving and wearable electronics.

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