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.
%0 Journal Article
%1 Kranz2013203
%A Kranz, Matthias
%A Möller, Andreas
%A Hammerla, Nils
%A Diewald, Stefan
%A Plötz, Thomas
%A Olivier, Patrick
%A Roalter, Luis
%D 2013
%J Pervasive and Mobile Computing
%K Activity HCI, Human-computer Mobile Pervasive Physical Skill Sports, Ubiquitous assessment, computing computing, exercising, interaction, recognition,
%N 2
%P 203--215
%R 10.1016/j.pmcj.2012.06.002
%T The mobile fitness coach: Towards individualized skill assessment
using personalized mobile devices
%U http://www.sciencedirect.com/science/article/pii/S1574119212000673
%V 9
%X 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.
@article{Kranz2013203,
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.},
added-at = {2013-04-09T16:42:04.000+0200},
author = {Kranz, Matthias and M\"{o}ller, Andreas and Hammerla, Nils and Diewald, Stefan and Pl\"{o}tz, Thomas and Olivier, Patrick and Roalter, Luis},
biburl = {https://www.bibsonomy.org/bibtex/2c54fc88212a2a756d347028507c5c395/stefan.diewald},
doi = {10.1016/j.pmcj.2012.06.002},
interhash = {38f4655324a7548f763fa30ccaa5e3d0},
intrahash = {c54fc88212a2a756d347028507c5c395},
issn = {1574-1192},
journal = {Pervasive and Mobile Computing},
keywords = {Activity HCI, Human-computer Mobile Pervasive Physical Skill Sports, Ubiquitous assessment, computing computing, exercising, interaction, recognition,},
month = apr,
note = {<ce:title>Special Section: Mobile Interactions with the Real World</ce:title>},
number = 2,
pages = {203--215},
timestamp = {2013-04-09T16:42:05.000+0200},
title = {The mobile fitness coach: Towards individualized skill assessment
using personalized mobile devices},
url = {http://www.sciencedirect.com/science/article/pii/S1574119212000673},
volume = 9,
year = 2013
}