Thesis Project Form

Outdoor endurance sports require efficient movement strategies that are difficult to assess with laboratory-only tools. This thesis explores the use of GESTUS to quantify running biomechanics in realistic sport conditions, supporting athlete monitoring, performance optimization, and return-to-sport assessment.

The thesis aims to assess the applicability of a novel motion capture platform (GESTUS) in a realistic outdoor running scenario involving competitive athletes. The participants will complete outdoor running sessions at varying speeds and intensities while wearing a full-body set of IMU and GNSS sensors. Using personalized musculoskeletal models, the student will estimate running performance and efficiency indicators, including step rate, step length, stride length, contact time, flight time, step height, pace, mechanical power, and, when available, respiration rate. Additional biomechanical descriptors such as foot-strike type, pronation excursion, maximum pronation velocity, stride angle, and spring stiffness will also be considered. Usability and acceptability will be assessed through the System Usability Scale.

The student will gain experience in outdoor sport biomechanics, wearable sensor acquisition, personalized musculoskeletal modeling, running gait analysis, extraction of performance and efficiency metrics, usability assessment with SUS, and interpretation of biomechanical data for athletic monitoring and rehabilitation contexts.