Smart Phone Monitoring and Swimming Visualisation Presentations, Monday Oct 29th

Higher degree candidates Jason Ride and Mitch McCarthy will present  progress on their work in Sport and Health Applications of Technology from 2:00pm on 29 October

Location: Room N25 0.06 (Science 1) at the Nathan Campus of Griffith University.

All are welcome!


Mr Mitch McCarthy

Title: Smart phone based activity monitoring for e-health applications

Brief Abstract
This project aims to examine the use of new technology such as smartphones in eHealth in order to provide more effective monitoring and feedback of day to day activity for maintaining a healthy lifestyle. In order to achieve this, a system is being developed to tie in with an existing website that will utilise smartphone technology to capture, collect and transfer activity data to a remote server for storage. This remote server contains dedicated analysis tools that will allow large quantities of information to be processed and mined so that meaningful results can be obtained and presented via the website. The prototype system has been developed and a pilot study run.


Mr Jim Ride

Title: Visualisation techniques for analysis of swimming

Brief Abstract

In elite-level sport, athletes and their coaches aim to maximise training proficiency to achieve rapid skill progression while maintaining optimal health and fitness. Optimising training often involves the employment of ancillary specialists to measure relevant characteristics and provide feedback to influence change. In recent years, various new technologies have been used experimentally to create new, more detailed measurements. Transforming this measured data into useful feedback is not straightforward.


Of the new measurement technologies being used in sport, MEMS-based sensors show significant potential as a complement or replacement to more traditional techniques of measuring athlete performance, particularly when used in multidimensional multisensory configurations. Therefore, the ability to represent multi-channel multi-sensor datasets in novel ways is of great importance to understanding and deconstructing the summative impact of the many biomechanical elements in an athlete’s technique. This project aims to expand upon existing inertial sensor research by developing a platform that facilitates the collection, storage, analysis and visualisation of multisensory data. It is envisaged that the employment of this more integrated approach to data processing will aid in the discovery of entirely new correlations and patterns that influence sporting performance.



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