@inproceedings{b0a6f1b9e94d48b4807cef00e149fb13,
title = "Exploring the Addition of Audio Input to Wearable Punch Recognition",
abstract = "Martial arts can promote healthy lifestyles, improve self- confidence and provide self-defence skills. Previous work has demonstrated that inertial sensors can be used to recognise movements such as punches in boxing and support self-directed training. However, many martial arts do not use gloves which means that punches can be performed with different parts of the hand, and therefore produce a different sound on impact. We investigate if it is possible to recognise different punches executed with a bare hand, and if the recognition rate improves by combining audio input with the traditional inertial sensors. We conducted a pilot study collecting a total of 600 punches, using a wearable wristband to capture inertial data and a stand-alone microphone for audio input. The results showed that it was possible to distinguish five types of punches with 94.4% accuracy when using only inertial data, and that adding audio input did not improve the accuracy. These findings can guide the design of future wearables for punch recognition.",
keywords = "martial arts, inertial sensors, machine learning, wearables, gesture recognition, punch recognition",
author = "{Quintero Ovalle}, Juan and Katarzyna Stawarz and Asier Marzo",
year = "2019",
month = jun,
day = "25",
doi = "10.1145/3335595.3335641",
language = "English",
isbn = "978-1-4503-7176-6 ",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery (ACM)",
booktitle = "Proceedings of the 22nd International Conference on Human-Computer Interaction, INTERACCION 2019",
address = "United States",
note = "22nd International Conference on Human-Computer Interaction, INTERACCION 2019 ; Conference date: 25-06-2019 Through 28-06-2019",
}