title: Off-the-shelf mobile handset environments for deploying accelerometer based gait and activity analysis algorithms.
abstract: Over the last decade, there has been substantial research interest in the application of accelerometry data for many forms of automated gait and activity analysis algorithms. This paper introduces a summary of new "of-the-shelf" mobile phone handset platforms containing embedded accelerometers which support the development of custom software to implement real time analysis of the accelerometer data. An overview of the main software programming environments which support the development of such software, including Java ME based JSR 256 API, C++ based Motion Sensor API and the Python based "aXYZ" module, is provided. Finally, a sample application is introduced and its performance evaluated in order to illustrate how a standard mobile phone can be used to detect gait activity using such a non-intrusive and easily accepted sensing platform.
authors: Communication and Signal Processing Research Unit, School of Engineering and Informatics, Uational University of Ireland, Galway. mhynes@unigalway.ie
authors: Martin
authors: M
authors: Hynes
authors: Han
authors: H
authors: Wang
authors: Liam
authors: L
authors: Kilmartin
mesh_terms: D000054:Acceleration; D000465:Algorithms; D040421:Cell Phone; D005684:Gait / Q000502:physiology*; D006801:Humans; D009043:Motor Activity / Q000502:physiology*