View Wearable Accelerometers Activity (public)

2013-07-30 04:38 by ugulino | Version 3 | Rating Empty StarEmpty StarEmpty StarEmpty StarEmpty StarEmpty Star
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Summary

A dataset with 5 classes (sitting-down, standing-up, standing, walking, and sitting) collected on 8 hours of activities of 4 healthy subjects.

License
CC0
Dependencies
Wearable Accelerometers Activity
Tags
Accelerometer action-recognition Activity-Recognition Classification PUC-Rio Scalar Wearable
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Data (first 10 data points)
    Format not HDF5, zip or tar archive. Will parse the following text: Please, cite this publication to refer this dataset and literature review Ugulino, W.; Cardador, D.; Vega, K.; Velloso, E.; Milidiu, R.; Fuks, H. Wearable Computing: Accelerometers' Data Classification of Body Postures and Movements. Proceedings of 21st Brazilian Symposium on Artificial Intelligence. Advances in Artificial Intelligence - SBIA 2012. In: Lecture Notes in Computer Science. pp.52-61. Curitiba, PR: Springer Berlin / Heidelberg, 2012. ISBN 978-3-642-34458-9. DOI: 10.1007/978-3-642-34459-6_6. Read more: http://groupware.les.inf.puc-rio.br/har#ixzz2PyRdbAfA Example data below... complete dataset available at the URL above
Description

Human Activity Recognition - HAR - has emerged as a key research area in the last years and is gaining increasing attention by the pervasive computing research community, especially for the development of context-aware systems. There are many potential applications for HAR, like: elderly monitoring, life log systems for monitoring energy expenditure and for supporting weight-loss programs, and digital assistants for weight lifting exercises.

Read more: http://groupware.les.inf.puc-rio.br/har#ixzz2aUaBROdz

HAR Dataset for benchmarking We propose a dataset with 5 classes (sitting-down, standing-up, standing, walking, and sitting) collected on 8 hours of activities of 4 healthy subjects. We also established a baseline performance index. You can download the dataset here (please, drop us a line (wugulino at inf dot puc-rio dot br) about your research and how we can contribute to your benchmarking).

This dataset is licensed under the Creative Commons (CC BY-SA)

Important: you are free to use this dataset for any purpose. This dataset is licensed under the Creative Commons license (CC BY-SA). The CC BY-SA license means you can remix, tweak, and build upon this work even for commercial purposes, as long as you credit the authors of the original work and you license your new creations under the identical terms we are licensing to you. This license is often compared to "copyleft" free and open source software licenses. All new works based on this dataset will carry the same license, so any derivatives will also allow commercial use.

URLs
http://groupware.les.inf.puc-rio.br/har
Publications
    Data Source
    http://groupware.les.inf.puc-rio.br/har#ixzz2aUaH8865 Ugulino, W.; Cardador, D.; Vega, K.; Velloso, E.; Milidiu, R.; Fuks, H. Wearable Computing: Accelerometers' Data Classification of Body Postures and Movements. Proceedings of 21st Brazilian Symposium on Artificial Intelligence. Advances in Artificial Intelligence - SBIA 2012. In: Lecture Notes in Computer Science. , pp. 52-61. Curitiba, PR: Springer Berlin / Heidelberg, 2012. ISBN 978-3-642-34458-9. DOI: 10.1007/978-3-642-34459-6_6.
    Measurement Details
    Usage Scenario
    revision 2
    by ugulino on 2013-07-30 04:35
    revision 3
    by ugulino on 2013-07-30 04:38

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    Acknowledgements

    This project is supported by PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning)
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