Beyond activity recognition: skill assessment from accelerometer data

Roisin McNaney, Aftab Khan, Sebastian Mellor, Eugen Berlin, Robin Thompson, Patrick Olivier, Thomas Ploetz

Research output: Contribution to conferenceConference Paperpeer-review

Abstract

The next generation of human activity recognition applications in ubiquitous computing scenarios focuses on assessing the quality of activities, which goes beyond mere identification of activities of interest. Objective quality assessments are often difficult to achieve, hard to quantify, and typically require domain specific background information that bias the overall judgement and limit generalisation. In this paper we propose a framework for skill assessment in activity recognition that enables automatic quality analysis of human activities. Our approach is based on a hierarchical rule induction technique that effectively abstracts from noise-prone activity data and assesses activity data at different temporal contexts. Our approach requires minimal domain specific knowledge about the activities of interest, which makes it largely generalisable. By means of an extensive case study we demonstrate the effectiveness of the …
Original languageEnglish
Pages1155
Number of pages1166
Publication statusPublished - 2015
EventProceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing -
Duration: 6 Jul 2015 → …

Conference

ConferenceProceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing
Abbreviated titleUbicomp
Period6/07/15 → …

Structured keywords

  • Digital Health

Keywords

  • Digital Health
  • Surgery

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