WeSport: Utilising wrist-band sensing to detect player activities in basketball games

Lu Bai, Christos Efstratiou, Chee Siang Ang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)
5 Downloads (Pure)

Abstract

Wristbands have been traditionally designed to track the activities of a single person. However there is an opportunity to utilize the sensing capabilities of wristbands to offer activity tracking services within the domain of team-based sports games. In this paper we demonstrate the design of an activity tracking system capable of detecting the players' activities within a one-to-one basketball game. Relying on the inertial sensors of wristbands and smartphones, the system can capture the shooting attempts of each player and provide statistics about their performance. The system is based on a two-level classification architecture, combining data from both players in the game. We employ a technique for semi-automatic labeling of the ground truth that requires minimum manual input during a training game. Using a single game as a training dataset, and applying the classifier on future games we demonstrate that the system can achieve a good level of accuracy detecting the shooting attempts of both players in the game (precision 91.34%, recall 94.31%).

Original languageEnglish
Title of host publication2016 IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509019410
DOIs
Publication statusPublished - 19 Apr 2016
Event13th IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2016 - Sydney, Australia
Duration: 14 Mar 201618 Mar 2016

Conference

Conference13th IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2016
CountryAustralia
CitySydney
Period14/03/1618/03/16

Keywords

  • Accelerometer
  • Activity monitoring
  • Classification
  • Wearable Sensors

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