Third party funded individual grant
Acronym: Digital Twin
Start date : 01.12.2018
End date : 31.05.2021
Extension date: 31.12.2021
The aim of the project is to design and implement a system that is able to holistically assess athletes. Therefore, novel individualised digital services, products and tools to enable a holistic mental and physiological performance optimisation will be developed. This is an improvement compared to current state of the art methods, since these approaches only consider physiological data for optimising performance.
By applying modern computation methods (e.g. deep learning using Convolutional Neural Networks) common physiological- will be fused with cognitive-performance parameters (e.g. executive functions or perceptual-cognitive skills). As a result, a holistic digital representation will be derived. Additionally, behavioural data from alternative data sources like user patterns from social media will be used to facilitate a prediction of different performance aspects (e.g. motivation or development). In a final step an algorithm will be implemented, that assures autonomous self-improvement of the system beyond the duration of the project.
For determining relevant cognitive indicator, different sensor signals will be analysed (e.g. ECG, EEG, Eye-Tracking) and related to the physiological data. To do so standardised assessment environments will be created by developing innovative interaction concepts. Different approaches along the Reality-Virtuality spectrum will be explored to facilitate user friendly products and services.
The aim of the project is to design and implement a system that is able to holistically assess athletes. Therefore, novel individualised digital services, products and tools to enable a holistic mental and physiological performance optimisation will be developed. This is an improvement compared to current state of the art methods, since these approaches only consider physiological data for optimising performance.