This work presents the development and experimental validation of a low-cost inertial acquisition framework for postural stability analysis. The system consists of three custom inertial measurement units (IMU), positioned on pelvis, right thigh and right shank, and a dedicated processing pipeline that includes sensor fusion, sensor-to-segment calibration, and joint angle computation. The system was validated against stereophotogrammetry and a commercial IMU reference, achieving high accuracy in hip and knee flexion-extension (RMSE% < 4.8, r > 0.98). Integrated into a robotic dynamic posturography platform, the proposed framework demonstrated that IMU-derived parameters complement force-platform data, enhancing the interpretation of postural responses and enabling discrimination of perturbation intensity, application point, and patient visual condition.
A Low-Cost Inertial Framework for Dynamic Posturography: From Preliminary Validation to Kinematic Integration / Bottoni, E., Galletta, L., De Benedictis, C., Paterna, M., Pacheco Quiñones, D., Maffiodo, D., Roatta, S., Ferraresi, C.. - ELETTRONICO. - 212:(2027), pp. 185-193. (35th International Conference on Robotics in Alpe-Adria-Danube Region, RAAD 2026 Bratislava (Slovakia) June 17-19, 2026) [10.1007/978-3-032-29127-1_20].
A Low-Cost Inertial Framework for Dynamic Posturography: From Preliminary Validation to Kinematic Integration
De Benedictis, Carlo;Paterna, Maria;Maffiodo, Daniela;Ferraresi, Carlo
2027
Abstract
This work presents the development and experimental validation of a low-cost inertial acquisition framework for postural stability analysis. The system consists of three custom inertial measurement units (IMU), positioned on pelvis, right thigh and right shank, and a dedicated processing pipeline that includes sensor fusion, sensor-to-segment calibration, and joint angle computation. The system was validated against stereophotogrammetry and a commercial IMU reference, achieving high accuracy in hip and knee flexion-extension (RMSE% < 4.8, r > 0.98). Integrated into a robotic dynamic posturography platform, the proposed framework demonstrated that IMU-derived parameters complement force-platform data, enhancing the interpretation of postural responses and enabling discrimination of perturbation intensity, application point, and patient visual condition.| File | Dimensione | Formato | |
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978-3-032-29127-1_20.pdf
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https://hdl.handle.net/11583/3013787
