Novel method for feature-set ranking applied to physical activity recognition

Authors:
Oresti Baños;Héctor Pomares;Ignacio Rojas
Affiliations:
Department of Computer Architecture and Computer Technology, University of Granada, Granada, Spain;Department of Computer Architecture and Computer Technology, University of Granada, Granada, Spain;Department of Computer Architecture and Computer Technology, University of Granada, Granada, Spain
Venue:
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
Year:
2010

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Abstract

Considerable attention is recently being paid in e-health and e-monitoring to the recognition of motion, postures and physical exercises from signal activity analysis. Most works are based on knowledge extraction using features which permit to make decisions about the activity realized, being feature selection the most critical stage. Feature selection procedures based on wrapper methods or 'branch and bound' are highly computationally expensive. In this paper, we propose an alternative filter method using a feature-set ranking via a couple of two statistical criteria, which achieves remarkable accuracy rates in the classification process.