The BikeNet mobile sensing system for cyclist experience mapping
Proceedings of the 5th international conference on Embedded networked sensor systems
Channel analysis and dynamic adaptation for energy-efficient WBSNs
UCAmI'12 Proceedings of the 6th international conference on Ubiquitous Computing and Ambient Intelligence
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In high-performance cycling, there is a need for advanced technological means of assessing the cyclists' performance during training and competition, and the risk of overuse injuries. Existing techniques rely on off-line, laboratory-based analysis, as well as on outfitting the bike with various sensors and transducers that give an estimate of the performance during training and racing. We propose a radically different approach, with the aim of determining the actual status of the cyclist's body in real-time and real-life conditions. Our solution is based on body area wireless motion sensor nodes that can collaboratively process the sensory information and give immediate feedback to the cyclists. We study experimentally the accuracy of such a system with respect to the gold standard camera system. The biomechanics measures of interest are the knee and ankle angles of the cyclists, which give an indication of the correctness and efficiency of the cycling technique. The results obtained from a series of experiments with nine subjects show the accuracy of the motion sensor system compared with the reference given by the camera system. Furthermore, we analyse the wireless characteristics of our system, the energy expenditure and possible improvements.