Interactive visualisation of sports game analytical data (InVisAn)
The aim of the project is a cross-disciplinary collaboration to develop a set of methods and software prototypes to explore the visualisation approaches of bio-feedback data in sport analytics. The basic underlying problem can be considered as rather complex, as it requires analytical data methods and appropriate ways to turn data into valuable knowledge for trainers, managers, health personal, and sports people for self-reflection. The PhD project aims at a cross-disciplinary approach between health care practitioners, and computational visualisation experts to create an interactive visualisation software for bio-feedback data visualisation based on bio-feedback data collected during sport events. Body sensors recording information such as heart-rate, location data, neurological data, and eventually brain data act as core data source for the interactive visualisation prototype to be developed. The PhD student is required to:
- evaluate and investigate sensor data analytic methods typically utilised for on-body-sensors as (among others) GPS, accelerometer, gyroscope, or other methods typically used in the domain of time-series data evaluation, regression models, classification methods, or Markov models based on works conducted by the co-supervisor  or  ;
- conducting a user-study with stakeholders, as e.g. trainers, managers, sports people, and health care professionals to evaluate user-interfaces for data-visualisation that would be fitting to their needs;
- implementation of a performance optimised sensor data analysis pipeline based on an implementation in R (or MatLab) to feed the interactive visualisation software platform with analysis data;
- conceptualisation and implementation of an interactive visualisation software platform based on the Unity game engine, D3.js or libraries available in MatLab or R to allow easier knowledge discovery as based on the requirements gathered during user-studies in step (2);
The emphasise of this project is on the exploration of visualisation methods and techniques rather than purely focusing on the pure data analytics components. The project complements previous efforts undertaken by the team, and shall advance previously conducted research, as e.g. an exciting Curtin cooperation with Hockey Australia. A very basic demonstration prototype has been developed within the activities of Visualisation and Interactive Media (VisMedia). Bio-feedback data is readily available through the database that has been created through projects conducted at the Faculty of Health Sciences. Past work of the CI related to this project is e.g. the development of the open source platform Portable Personality (P2) for the analysis of personality data –; industrial cooperation projects with mobile phone companies in sensor data analytics; the software tool The LudoViCo UX-Machine, which is utilised for sensor data recording and analysis of human bio-feedback data ; efforts undertaken in the domain of emotional computation ; and human-computer interaction through smart environments . The project aims at an international cooperation with key-players in the domain of visualisation and sensor data analysis as e.g. QUT/Australia, University of Vienna/Austria, TUT Tampere/Finland, and the University of Ljubljana/Slovenia.
- the project is rather focused on sport analytics, and the investigation of visualisation methods. It builds upon existing activities conducted within the Faculty of Health Sciences, results (e.g. LudoViCo UX-Machine) of other projects, and leverages existing partnerships of Curtin’s University (e.g. links to Hockey Australia);
- the project will advance the state of the art by the development of an interactive visualisation prototype, and extends theoretical work that has been conducted e.g. in  or ;
- advancement of sport analytics e.g. to support trainers in drills and tactics, advance sport medicine, and gaining new insights in transferring the results to the general population within the scope of health informatics based on health care related Big Data;
The anticipated outcomes of the project are:
- extension and further development of the existing freely available software tool The LudoViCo UX-Machine with additional functionality and extension of theoretical methods developed e.g. in  and ;
- 2-3 journal articles, and 4 conference publications in ERA ranked publications – several publications should be only at highly ranked venues and publication outlines as e.g. IEEE Transactions;
- International network linked to a Curtin community of interest of scholars as part of the Curtin Institute for Computation (CIC);
- A practical dissemination of the efforts will be taking place through a tight collaboration with Hockey Australia;
- sport health data live recorded during matches, and video game live footage as well as the current state of the open source platform The LudoViCo UX-Machine will be provided to the project;
- access to the software platforms Unity, MatLab, R, open source tools as e.g. D3.JS, and the typical software development tools as Visual Studio;
- hardware such as sensors, Curtin’s HIVE visualisation equipment, and other tools required for visualisation as e.g. provided by MCCA;
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