Off-the-Shelf Mobile Handset Environments for Deploying Accelerometer based Gait and Activity Analysis Algorithms

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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.
Original languageEnglish (Ireland)
Title of host publication2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20
PublisherIEEE
Number of pages3
ISBN (Electronic)1557-170X
ISBN (Print)1557-170X
Publication statusPublished - 1 Jan 2009

Authors (Note for portal: view the doc link for the full list of authors)

  • Authors
  • Hynes, M;Wang, H;Kilmartin, L

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