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Authors: Sebastian Baumbach and Andreas Dengel

Affiliation: German Research Center for Artificial Intelligence and University of Kaiserslautern, Germany

ISBN: 978-989-758-220-2

Keyword(s): Sensor Data, Spatial-temporal Data, Data Mining, Naive Bayes.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Data Manipulation ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Evolutionary Computing ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Symbolic Systems

Abstract: The trend of mobile activity monitoring using widely available technology is one of the most blooming concepts in the recent years. It supports many novel applications, such as fitness games or health monitoring. In these scenarios, activity recognition tries to distinguish between different types of activities. However, only little work has focused on qualitative recognition so far: How exactly is the activity carried out? In this paper, an approach for supervising activities, i.e. qualitative recognition, is proposed. The focus lied on push-ups as a proof of concept, for which sensor data of smartphones and smartwatches were collected. A user-dependent dataset with 4 participants and a user-independent dataset with 16 participants were created. The performance of Naive Bayes classifier was tested against normal, kernel and multivariate multinomial probability distributions. An accuracy of 90.5% was achieved on the user-dependent model, whereas the user-independent model sco red with an accuracy of 80.3%. (More)

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Paper citation in several formats:
Baumbach S. and Dengel A. (2017). Measuring the Performance of Push-ups - Qualitative Sport Activity Recognition.In Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-220-2, pages 374-381. DOI: 10.5220/0006114503740381

@conference{icaart17,
author={Sebastian Baumbach and Andreas Dengel},
title={Measuring the Performance of Push-ups - Qualitative Sport Activity Recognition},
booktitle={Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2017},
pages={374-381},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006114503740381},
isbn={978-989-758-220-2},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Measuring the Performance of Push-ups - Qualitative Sport Activity Recognition
SN - 978-989-758-220-2
AU - Baumbach S.
AU - Dengel A.
PY - 2017
SP - 374
EP - 381
DO - 10.5220/0006114503740381

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