Publication: Exploring the Application of Hybrid Evolutionary Computation Techniques to Physical Activity Recognition
Loading...
Identifiers
Publication date
2016-07
Defense date
Advisors
Tutors
Journal Title
Journal ISSN
Volume Title
Publisher
Association for Computing Machinery
Impact
Export
Abstract
This paper focuses on the problem of physical activity recognition, i.e., the development of a system which is able to learn patterns from data in order to be able to detect which physical activity (e.g. running, walking, ascending stairs, etc.) a certain user is performing.While this field is broadly explored in the literature, there are few works that face the problem with evolutionary computation techniques. In this case, we propose a hybrid system which combines particle swarm optimization for clustering features and genetic programming combined with evolutionary strategies for evolving a population of classifiers, shaped in the form of decision trees. This system would run the segmentation, feature extraction and classification stages of the activity recognition chain.For this paper, we have used the PAMAP2 dataset with a basic preprocessing. This dataset is publicly available at UCI ML repository. Then, we have evaluated the proposed system using three different modes: a user-independent, a user-specific and a combined one. The results in terms of classification accuracy were poor for the first and the last mode, but it performed significantly well for the user-specific case. This paper aims to describe work in progress, to share early results an discuss them. There are many things that could be improved in this proposed system, but overall results were interesting especially because no manual data transformation took place.
Description
This paper has been presented at: GECCO '16 Companion Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion.
Keywords
Physical activity, Activity recognition, Hybrid evolutionary computation, Particle swarm optimization, Genetic programming, Metaheuristics, Classification
Bibliographic citation
Baldominos,A., Barrio, C. del, y Saez, Y. (2016). Exploring the Application of Hybrid Evolutionary Computation Techniques to Physical Activity Recognition. In Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion, pp. 1377-1384.