Byte.it

Tomás Vega Galvez, Shardul Sapkota, Alexandru Dancu, Pattie Maes

2019 · 15 citations · 7 references

Concepts

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%.

References

7