Andreu, Javier and Dutta Baruah, Rashmi and Angelov, Plamen (2011) Real-time recognition of human activities from wearable sensors by evolving classifiers. In: 2011 IEEE International Conference on Fuzzy Systems (FUZZ). IEEE, pp. 2786-2793. ISBN 978-1-4244-7315-1
Full text not available from this repository.Abstract
A new approach to real-time human activity recognition (HAR) using evolving self-learning fuzzy rule-based classifier (eClass) will be described in this paper. A recursive version of the principle component analysis (PCA) and linear discriminant analysis (LDA) pre-processing methods is coupled with the eClass leading to a new approach for HAR which does not require computation and time consuming pre-training and data from many subjects. The proposed new method for evolving HAR (eHAR) takes into account the specifics of each user and possible evolution in time of her/his habits. Data streams from several wearable devices which make possible to develop a pervasive intelligence enabling them to personalize/tune to the specific user were used for the experimental part of the paper.
| Item Type: | Contribution in Book/Report/Proceedings |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Departments: | Faculty of Science and Technology > School of Computing & Communications |
| ID Code: | 53151 |
| Deposited By: | ep_importer_pure |
| Deposited On: | 09 Mar 2012 03:33 |
| Refereed?: | No |
| Published?: | Published |
| Last Modified: | 26 Jul 2012 23:10 |
| Identification Number: | |
| URI: | http://eprints.lancs.ac.uk/id/eprint/53151 |
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