A distributed architecture for storing and processing multi channel multi-sensor athlete performance data
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Over the last decade, inertial sensors have become a valuable tool for extracting quantitative data from athletes. Due to their small size, unobtrusive nature and relative affordability, there is considerable interest in using multi-channel multi-sensor configurations to gain further insight into sporting performance parameters. As the amount of raw information that can be recorded in a single training session increases, so too does the complexity of the data mining algorithms required to emphasise, extract and derive its performance metrics. This paper details a developed system that uses a distributed server-client architecture to collect and store large sets of athlete data as well as providing mechanisms for later analysis and visualisation for feedback. The server utilises MATLAB with the Athlete Data Processing Toolbox. A local SQL server handles data storage and PHP with AJAX/JSON is used to communicate with clients. Clients use a web browser interface to communicate with the server and provide relevant analysis and visualisation tools to the end user.
© 2012 The Authors. Published by Elsevier Ltd. Open access under the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) License which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited. You may not alter, transform, or build upon this work.