The mobile fitness coach: Towards individualized skill assessment using personalized mobile devices

Authors:
Matthias Kranz;Andreas MöLler;Nils Hammerla;Stefan Diewald;Thomas PlöTz;Patrick Olivier;Luis Roalter
Affiliations:
LuleåUniversity of Technology, Department of Computer Science, Electrical and Space Engineering, Luleå, Sweden;Technische Universität München, Distributed Multimodal Information Processing Group, Munich, Germany;Newcastle University, Culture Lab, School of Computing Science, Newcastle upon Tyne, United Kingdom;Technische Universität München, Distributed Multimodal Information Processing Group, Munich, Germany;Newcastle University, Culture Lab, School of Computing Science, Newcastle upon Tyne, United Kingdom;Newcastle University, Culture Lab, School of Computing Science, Newcastle upon Tyne, United Kingdom;Technische Universität München, Distributed Multimodal Information Processing Group, Munich, Germany
Venue:
Pervasive and Mobile Computing
Year:
2013

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Abstract

We report on our extended research on GymSkill, a smartphone system for comprehensive physical exercising support, from sensor data logging, activity recognition to on-top skill assessment, using the phone's built-in sensors. In two iterations, we used principal component breakdown analysis (PCBA) and criteria-based scores for individualized and personalized automated feedback on the phone, with the goal to track training quality and success and give feedback to the user, as well as to engage and motivate regular exercising. Qualitative feedback on the system was collected in a user study, and the system showed good evaluation results in an evaluation against manual expert assessments of video-recorded trainings.