Tomás Vega Gálvez, Shardul Sapkota, Alexandru Dancu, Pattie Maes, CHI Conference on Human Factors in Computing Systems Extended Abstracts (CHI’19 Extended Abstracts), May 4–9, 2019, Glasgow, Scotland UK, ACM, New York, NY, USA, 6 pages, https://doi.org/10.1145/3290607.3312925

Abstract

Byte.it is an exploration of the feasibility of using miniaturized, discreet hardware for teeth-clicking as hands-free input for wearable computing. Prior work has been able to identify teeth-clicking of different teeth groups. Byte.it expands on this work by exploring the use of a smaller and more discreetly positioned sensor suite (accelerometer and gyroscope) for detecting four different teeth- clicks for everyday human-computer interaction. Initial results show that an unobtrusive position on the lower mastoid and mandibular condyle can be used to classify teeth-clicking of four different teeth groups with an accuracy of 89%.