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Qualitative Activity Recognition of Weight Lifting Exercises

Velloso, E.; Bulling, A.; Gellersen, H.; Ugulino, W.; Fuks, H. Qualitative Activity Recognition of Weight Lifting Exercises. Proceedings of 4th Augmented Human (AH) International Conference in cooperation with ACM SIGCHI (Augmented Human'13) . Stuttgart, Germany: ACM SIGCHI, 2013.
Cited by 61 (Google Scholar)

Temas: Sistemas Embarcados, Internet das coisas, Hardware, Estudo de Caso, Entrevista, Questionário, Prototipação

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Abstract: Research on activity recognition has traditionally focusedon discriminating between different activities, i.e. to predict "which" activity was performed at a specic 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.