Literature DB >> 19964383

Off-the-shelf mobile handset environments for deploying accelerometer based gait and activity analysis algorithms.

Martin Hynes1, Han Wang, Liam Kilmartin.   

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.

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Year:  2009        PMID: 19964383     DOI: 10.1109/IEMBS.2009.5333715

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  3 in total

1.  Objective measurement of sociability and activity: mobile sensing in the community.

Authors:  Ethan M Berke; Tanzeem Choudhury; Shahid Ali; Mashfiqui Rabbi
Journal:  Ann Fam Med       Date:  2011 Jul-Aug       Impact factor: 5.166

Review 2.  Health behavior models in the age of mobile interventions: are our theories up to the task?

Authors:  William T Riley; Daniel E Rivera; Audie A Atienza; Wendy Nilsen; Susannah M Allison; Robin Mermelstein
Journal:  Transl Behav Med       Date:  2011-03       Impact factor: 3.046

3.  Evaluation of the Accuracy of a Triaxial Accelerometer Embedded into a Cell Phone Platform for Measuring Physical Activity.

Authors:  C U Manohar; S K McCrady; Y Fujiki; I T Pavlidis; J A Levine
Journal:  J Obes Weight Loss Ther       Date:  2011-12-20
  3 in total

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