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PhD student for the development of a communicating embedded system allowing the quantification of an athlete's workload.

This offer is available in the following languages:
Français - Anglais

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General information

Reference : UMR8029-FLORAZ-001
Workplace : BRUZ
Date of publication : Thursday, July 23, 2020
Scientific Responsible name : Florence Razan
Type of Contract : PhD Student contract / Thesis offer
Contract Period : 36 months
Start date of the thesis : 1 October 2020
Proportion of work : Full time
Remuneration : 2 135,00 € gross monthly

Description of the thesis topic

Performances of high-level athletes are nowadays played out to hundredths of a second. In order to optimize performance, it is necessary to combine sport and technology. This thesis consists in quantifying the workload of athletes by developing an embedded system through a multidisciplinary approach. The data will be used to build predictive models of injury.
The objective is to design an embedded system to measure the workload. The network of sensors should monitor physical, physiological and biological parameters, to recognize and quantify the motor activity of mainly handball players and volleyball players in training and competition conditions, while remaining as minimally invasive as possible to limit the athlete's discomfort and embarrassment. All data will be available for consultation during or after a training session or match. The final system will have to integrate a software and an adapted interface allowing players, coaches, trainers, physical trainers, doctors and physiotherapists a very fast and efficient access to data directly and easily usable.
A first step will consist in translating the specifications of the sports teams into constraints, then the placement of sensors and components will result from an overall optimization of the information-energy system. Tests on a laboratory scale and then on athletes will provide data necessary for the development of the system, in particular the training of artificial intelligence algorithms merging the measurements of different sensors to extract the information useful for modelling the workload.

Work Context

This work will be carried out at the SATIE laboratory, whose scientific fields focus on the study and development of complex systems combining information and energy. It will be located at the interface of the two poles, SIAME and CSEE, in order to have a vision of the system and to gathered instrumentation and energy aspects. The thesis will be carried out in co-supervision with the M2S laboratory specialized in the optimization of sportsmen's training processes and in collaboration with the GEMTEX laboratory, expert in the design and implementation of textile structures with functional properties.

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