Human movement analysis technology, including stereophotogrammetric motion capture, 2D and 3D video camera reconstruction, global navigation satellite and local positioning systems (GNSS, and LPS), and magneto-inertial sensors (MIMUs) has revolutionized the field of sports by providing scientists, coaches, and athletes with invaluable insights into athletes’ movement patterns. Thanks to movement analysis, feedback on biomechanical inefficiencies may be obtained to optimize sports techniques and prevent the risk of injuries, and athletes’ performances may be compared among peers or over time, aiding in the evaluation of training interventions and performance progression. This chapter spans from describing laboratory assessments, performed with motion capture in controlled conditions, to in-field assessments, performed in ecological conditions by 2D/3D video analysis, positioning systems and MIMU technologies allowing the digital reconstruction of the movement. Due to their massive spread in the sports context, particular attention is devoted to MIMUs integrating accelerometers, gyroscopes, and magnetic sensors. Their working principles and a battery of tests useful for their metrological characterization, as well as their calibration refinement process, are given. Sensor characteristics and good-practice procedures of relevance in the sport context are also detailed. General indications on how to extract the main biomechanical kinematic parameters contributing to objective performance monitoring/evaluation or to musculoskeletal injury assessment are provided either using sensor signals directly (temporal parameters, phase segmentation and angular velocity or linear acceleration) or through computation/modelling (3D absolute or relative orientation, namely joint kinematics, or the linear velocity or position). Thereafter, a detailed analysis of joint angles, body positions, and biomechanical patterns during sporting activities is enabled, allowing the definition of key performance indicators according to ad hoc technical analyses. Finally, running, being the sports activity that has undergone the most extensive research and enjoys the highest level of popularity, has been selected as the prime example for in-field analysis of signal processing and feature extraction. The attention is focused on the identification and the biomechanical comparison of different foot strike patterns due to their possible close relationship with running-related injuries.
Elena Bergamini, V.C. (2023). Measurement and extraction of motion-related quantities in sport. Bologna : Patron.
Measurement and extraction of motion-related quantities in sport
Silvia FantozziPenultimo
;
2023
Abstract
Human movement analysis technology, including stereophotogrammetric motion capture, 2D and 3D video camera reconstruction, global navigation satellite and local positioning systems (GNSS, and LPS), and magneto-inertial sensors (MIMUs) has revolutionized the field of sports by providing scientists, coaches, and athletes with invaluable insights into athletes’ movement patterns. Thanks to movement analysis, feedback on biomechanical inefficiencies may be obtained to optimize sports techniques and prevent the risk of injuries, and athletes’ performances may be compared among peers or over time, aiding in the evaluation of training interventions and performance progression. This chapter spans from describing laboratory assessments, performed with motion capture in controlled conditions, to in-field assessments, performed in ecological conditions by 2D/3D video analysis, positioning systems and MIMU technologies allowing the digital reconstruction of the movement. Due to their massive spread in the sports context, particular attention is devoted to MIMUs integrating accelerometers, gyroscopes, and magnetic sensors. Their working principles and a battery of tests useful for their metrological characterization, as well as their calibration refinement process, are given. Sensor characteristics and good-practice procedures of relevance in the sport context are also detailed. General indications on how to extract the main biomechanical kinematic parameters contributing to objective performance monitoring/evaluation or to musculoskeletal injury assessment are provided either using sensor signals directly (temporal parameters, phase segmentation and angular velocity or linear acceleration) or through computation/modelling (3D absolute or relative orientation, namely joint kinematics, or the linear velocity or position). Thereafter, a detailed analysis of joint angles, body positions, and biomechanical patterns during sporting activities is enabled, allowing the definition of key performance indicators according to ad hoc technical analyses. Finally, running, being the sports activity that has undergone the most extensive research and enjoys the highest level of popularity, has been selected as the prime example for in-field analysis of signal processing and feature extraction. The attention is focused on the identification and the biomechanical comparison of different foot strike patterns due to their possible close relationship with running-related injuries.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.