Global indoor self-localization based on the ambient magnetic field
Robotics and Autonomous Systems
SwimMaster: a wearable assistant for swimmer
Proceedings of the 11th international conference on Ubiquitous computing
Ubiquitous mobile instrumentation
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
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Current methods of swim stroke learning rely on a combination of external observation by coaches and repetitive drills performed by swimmers. At elite levels, these may be augmented using complex and expensive augmented pool environments and video analysis, but these are not available to most non-professionals. In this paper, I argue that with the wide range of sensors and outputs on a current smartphone, and existing sports-targeted waterproofing, commodity mobile hardware may allow even un-coached amateur swimmers to access timely feedback on their stroke and to improve their swimming. An early prototype of a swim-sensing system demonstrates the potential of mobiles to sense aspects of the swimming stroke. By using commodity hardware it is open to many potential learners, who may in turn provide high quality data to feed back into the development of swim coaching techniques by sports researchers and practitioners.