Development of methods for the evaluation of mobility and physical activity through wearable sensors

Instrumented human motion analysis provides valuable insights into mobility, physical activity, and motor performance in both clinical and sports applications. The most widespread technology for motion analysis in out-of-lab contexts involves magneto-inertial sensors, which can provide gait spatio-temporal parameters through ad hoc algorithms. However, these sensors face limitations, including speed-dependent signal morphologies and the intrinsic inability to accurately measure relative positions between body segments. This thesis addresses these limitations by focusing on mobility evaluation during walking and physical activity evaluation during running. First, the base of support during walking is informative in monitoring dynamic stability, but its estimation requires inter-foot distance, which cannot be extracted by inertial sensors alone. An original method based on inertial and distance sensors was implemented to estimate gait spatial parameters, including the base of support with errors below 3% across different walking speeds. Secondly, this thesis addressed the lack in the literature of a speed-robust inertial-based method to estimate running spatio-temporal parameters. An original template-based method using dynamic time warping was implemented to segment running phases, achieving high accuracy (errors equal to or below 30 ms) across very different running speeds (from 8 to 30 km/h). Furthermore, these methods were applied to investigate how footwear affects running biomechanics, showing that foot-mounted inertial sensors can effectively capture the runner’s response to footwear change, aiding in individual performance optimization and injury prevention. The overall findings of this thesis suggest that the proposed methods and wearable setups can overcome current limitations in the use of magneto-inertial sensors in gait analysis and enable gait characterization in ecological environments at variable speeds from slow walking to fast sprinting.