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Qualitative activity recognition of weight lifting exercises

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published

Standard

Qualitative activity recognition of weight lifting exercises. / Velloso, Eduardo; Bulling, Andreas; Gellersen, Hans et al.
Proceedings of the 4th Augmented Human International Conference. New York, NY, USA: ACM, 2013. p. 116-123.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Velloso, E, Bulling, A, Gellersen, H, Ugulino, W & Fuks, H 2013, Qualitative activity recognition of weight lifting exercises. in Proceedings of the 4th Augmented Human International Conference. ACM, New York, NY, USA, pp. 116-123, 4th Augmented Human International Conference, Stuttgart, Germany, 7/03/13. https://doi.org/10.1145/2459236.2459256

APA

Velloso, E., Bulling, A., Gellersen, H., Ugulino, W., & Fuks, H. (2013). Qualitative activity recognition of weight lifting exercises. In Proceedings of the 4th Augmented Human International Conference (pp. 116-123). ACM. https://doi.org/10.1145/2459236.2459256

Vancouver

Velloso E, Bulling A, Gellersen H, Ugulino W, Fuks H. Qualitative activity recognition of weight lifting exercises. In Proceedings of the 4th Augmented Human International Conference. New York, NY, USA: ACM. 2013. p. 116-123 doi: 10.1145/2459236.2459256

Author

Velloso, Eduardo ; Bulling, Andreas ; Gellersen, Hans et al. / Qualitative activity recognition of weight lifting exercises. Proceedings of the 4th Augmented Human International Conference. New York, NY, USA : ACM, 2013. pp. 116-123

Bibtex

@inproceedings{7548adc119d147a280f30300bfcbafba,
title = "Qualitative activity recognition of weight lifting exercises",
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.",
keywords = "qualitative activity recognition, real-time user feedback , weight lifting",
author = "Eduardo Velloso and Andreas Bulling and Hans Gellersen and Wallace Ugulino and Hugo Fuks",
year = "2013",
doi = "10.1145/2459236.2459256",
language = "English",
isbn = "978-1-4503-1904-1",
pages = "116--123",
booktitle = "Proceedings of the 4th Augmented Human International Conference",
publisher = "ACM",
note = "4th Augmented Human International Conference ; Conference date: 07-03-2013 Through 08-03-2013",

}

RIS

TY - GEN

T1 - Qualitative activity recognition of weight lifting exercises

AU - Velloso, Eduardo

AU - Bulling, Andreas

AU - Gellersen, Hans

AU - Ugulino, Wallace

AU - Fuks, Hugo

PY - 2013

Y1 - 2013

N2 - 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.

AB - 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.

KW - qualitative activity recognition

KW - real-time user feedback

KW - weight lifting

U2 - 10.1145/2459236.2459256

DO - 10.1145/2459236.2459256

M3 - Conference contribution/Paper

SN - 978-1-4503-1904-1

SP - 116

EP - 123

BT - Proceedings of the 4th Augmented Human International Conference

PB - ACM

CY - New York, NY, USA

T2 - 4th Augmented Human International Conference

Y2 - 7 March 2013 through 8 March 2013

ER -