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Qualitative activity recognition of weight lifting exercises

Research output: Contribution in Book/Report/ProceedingsPaper

Published
Publication date2013
Host publicationProceedings of the 4th Augmented Human International Conference
Place of PublicationNew York, NY, USA
PublisherACM
Pages116-123
Number of pages8
ISBN (Print)978-1-4503-1904-1
<mark>Original language</mark>English

Conference

Conference4th Augmented Human International Conference
CountryGermany
CityStuttgart
Period7/03/138/03/13

Conference

Conference4th Augmented Human International Conference
CountryGermany
CityStuttgart
Period7/03/138/03/13

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.