Abstract
Real-time monitoring of human movements can be easily envisaged as a useful tool for many purposes and future applications. This paper presents the implementation of a real-time classification system for some basic human movements using a conventional mobile phone equipped with an accelerometer. The aim of this study was to check the present capacity of conventional mobile phones to execute in real-time all the necessary pattern recognition algorithms to classify the corresponding human movements. No server processing data is involved in this approach, so the human monitoring is completely decentralized and only an additional software will be required to remotely report the human monitoring. The feasibility of this approach opens a new range of opportunities to develop new applications at a reasonable low-cost.
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Brezmes, T., Gorricho, JL., Cotrina, J. (2009). Activity Recognition from Accelerometer Data on a Mobile Phone. In: Omatu, S., et al. Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. IWANN 2009. Lecture Notes in Computer Science, vol 5518. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02481-8_120
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DOI: https://doi.org/10.1007/978-3-642-02481-8_120
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02480-1
Online ISBN: 978-3-642-02481-8
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