Graphene Smart Textile-Based Wearable Eye Movement Sensor for Electro-Ocular Control and Interaction with Objects

Abstract

Wearable graphene textile embedded smart headband and its feasibility in electrooculography (EOG) applications is demonstrated by benchmarking against clinical Ag/AgCl wet electrodes; where the recorded biopotentials displayed excellent correlation of 91.3% over durations up to hundred seconds. Automatic eye movement (EM) detection is implemented and performance of the graphene-embedded “all-textile” eye movement sensor and its application as a control element toward human-computer interaction (HCI) and human-machine interfaces (HMI) is experimentally demonstrated by: 1) generating digital clock transitions directly from eye blinks for facilitating switching requirements in HCI/HMI applications, 2) controlling and sequentially lighting up a single LED in a 5 × 5 LED array in four directions to draw a pattern of “8”, 3) evaluating the limits of the entire system in an hour-long EOG recording session which includes several activities like checking a phone, watching a video, reading, and performing several EMs including blinks, saccades, and fixations. The excellent success rate ranging from 85% up to 100% for eleven different EM patterns demonstrates the applicability of the proposed algorithm in wearable EOG-based sensing and HCI/HMI applications with graphene textiles. The system-level integration and the holistic design approach presented herein which starts from fundamental materials level up to the architecture and algorithm stage is highlighted and will be instrumental to advance the state-of-the-art in wearable electronic devices.