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Data fusion of relative movement in fast, repetitive-action sports using body wireless area networks

Armstrong, Helen Sian 2013. Data fusion of relative movement in fast, repetitive-action sports using body wireless area networks. PhD Thesis, Cardiff University.
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Rowing is an intensive, all-body sport, where bad technique can lead to injury. Crew cohesion, particularly timing, is vital to the performance of the boat. The coaching process, and injury prevention, could be enhanced if data relating to the movement of the oarsmen could be collected, without hindrance to the oarsmen, during on-water training. Literature until recently has concentrated upon boat-centric measurement. Advances in wireless technology have made feasible the collection of data from multiple physically separate sites, including on-body. After analysis of candidate radio standards, a Zigbee wireless Body Sensor Network (BSN) was designed and developed to synchronously collect data from several sensors across the wireless BSN. By synchronising sensor nodes via scheduled synchronising messages from the central coordinating node, synchronisation within 0.79msec ±0.39ms was achieved. Minimisation of the on-time of the sensor node radios currently extends the battery life by a factor of 5. Acceleration and muscle activity data collected using the wireless BSN was compared to data synchronously collected using proven motion analysis techniques to validate the system. Synchronous muscle activity data was collected via the wireless BSN from several muscles during both land-based and on-water rowing and the results compared. The system was proven to facilitate the identification of bad rowing technique, as well as differences in muscle recruitment between land- and water-based rowing. Data collection from a rowing crew was also demonstrated, and their muscle activity and inter-crew timing analysed. With an additional sensor node upon the boat, it is possible to correlate acceleration and muscle activity from the oarsman with acceleration of the boat itself. A novel, power-optimised wireless sensor network has been designed and demonstrated to facilitate on-water rowing monitoring that can be extended beyond single oarsman measurements to analyse the interaction and cohesion of a crew and their impact upon boat performance.

Item Type: Thesis (PhD)
Status: Unpublished
Schools: Engineering
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Uncontrolled Keywords: body sensor networks(BSN; wireless sensor networks (WSN; rowing; electromyography (EMG; accelerometry.
Date of First Compliant Deposit: 30 March 2016
Last Modified: 31 Jan 2020 03:29

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