Exploring the Addition of Audio Input to Wearable Punch Recognition

Juan Quintero Ovalle, Katarzyna Stawarz, Asier Marzo

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

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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.
Original languageEnglish
Title of host publicationProceedings of the 22nd International Conference on Human-Computer Interaction, INTERACCION 2019
Subtitle of host publicationXX International Conference on Human Computer Interaction
PublisherAssociation for Computing Machinery (ACM)
Number of pages4
ISBN (Electronic)9781450371766
ISBN (Print)978-1-4503-7176-6
DOIs
Publication statusPublished - 25 Jun 2019
Event22nd International Conference on Human-Computer Interaction, INTERACCION 2019 - Donostia-San Sebastian, Spain
Duration: 25 Jun 201928 Jun 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference22nd International Conference on Human-Computer Interaction, INTERACCION 2019
CountrySpain
CityDonostia-San Sebastian
Period25/06/1928/06/19

Keywords

  • martial arts
  • inertial sensors
  • machine learning
  • wearables
  • gesture recognition
  • punch recognition

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