The main goal of the ARCANE project is to propose a framework that may promote an augmented perception of team performance in sports. In this project, the football will be used as a task vehicle due to its undeniable worldwide popularity. The framework shall be used to provide an interpretation of athletes’ positional and physiological data during performance, proposing new methods to assess athletes on-the-fly and, to some extent, predict the health and performance outcomes.

The ARCANE project aims to advance current analysis frameworks, both technologically and scientifically, to improve the on-the-fly performance analysis of football players. The overall methodology shall benefit from both positional and physiological data of athletes retrieved during competitive performance, in real-time, thus calling for the development of novel wearable technologies. As such, this project comprises the development of a technological solution and novel mathematical methods, namely for position estimation, multi-sensor fusion, data mining, and performance analysis and prediction, thus being integrated into both academic and industrial settings. This research project aims to contribute towards an increasing understanding on human performance by proposing a novel framework that may provide decisive information and feedback for coaches, sports analysts, exercise physiologists and practitioners. The key objectives (KOs) of the ARCANE project are as follows:

Wearable Tracking System

Development of a novel technological solution to estimate the position of wearable mobile devices within a field, by benefiting from multilateration techniques and wireless propagation measures, such as the received signal strength indication (RSSI) and the round-trip time (RTT);

Multi-Sensor Fusion

Design of a multi-sensor fusion algorithm to provide real-time and fault-tolerant information about an athlete’s postural state (i.e., position and orientation), integrating wireless propagation measures with data coming from an inertial measurement unit (IMU);

Biosignal Monitoring

Integration of physiological sensors (e.g., heart rate monitors) within the wearable device for non-invasive monitoring of the athlete's performance and design of a data mining procedure to improve the reliability of data from physiological sensors;

Macroscopic Modeling

Mathematical formulation of a framework for online match analysis and prediction based on players’ position and physiological data over time.