Qualitative activity recognition of weight lifting exercises

E. Velloso, A. Bulling, H. Gellersen, W. Ugulino, H. Fuks

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

68 Citations (Scopus)

Abstract

Research on activity recognition has traditionally focused on discriminating between different activities, i.e. to predict which activity was performed at a specific point in time. The quality of executing an activity, the how (well), has only received little attention so far, even though it potentially provides useful information for a large variety of applications. In this work we define quality of execution and investigate three aspects that pertain to qualitative activity recognition: specifying correct execution, detecting execution mistakes, providing feedback on the to the user. We illustrate our approach on the example problem of qualitatively assessing and providing feedback on weight lifting exercises. In two user studies we try out a sensor- and a model-based approach to qualitative activity recognition. Our results underline the potential of model-based assessment and the positive impact of real-time user feedback on the quality of execution.
Original languageEnglish
Title of host publicationAH '13: Proceedings of the 4th Augmented Human International Conference
PublisherACM Publishing
Pages116-123
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event4th Augmented Human International Conference, AH 2013 - Stuttgart, Germany
Duration: 7 Mar 20138 Mar 2013
Conference number: 4

Conference

Conference4th Augmented Human International Conference, AH 2013
Abbreviated titleAH 2013
CountryGermany
CityStuttgart
Period7/03/138/03/13

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