Estimating the limbs pose in a wearable way may benefit multiple areas such as rehabilitation, teleoperation, human-robot interaction, gaming, and many more. Several solutions are commercially available, but they are usually expensive or not wearable/portable. We present a wearable pose estimation system (WePosE), based on inertial measurements units (IMUs), for motion analysis and body tracking. Differently from camera-based approaches, the proposed system does not suffer from occlusion problems and lighting conditions, it is cost effective and it can be used in indoor and outdoor environments. Moreover, since only accelerometers and gyroscopes are used to estimate the orientation, the system can be used also in the presence of iron and magnetic disturbances. An experimental validation using a high precision optical tracker has been performed. Results confirmed the effectiveness of the proposed approach.

Lisini Baldi, T., Farina, F., Garulli, A., Giannitrapani, A., Prattichizzo, D. (2020). Upper Body Pose Estimation Using Wearable Inertial Sensors and Multiplicative Kalman Filter. IEEE SENSORS JOURNAL, 20(1), 492-500 [10.1109/JSEN.2019.2940612].

Upper Body Pose Estimation Using Wearable Inertial Sensors and Multiplicative Kalman Filter

Lisini Baldi, T.;Garulli, A.;Giannitrapani, A.;Prattichizzo, D.
2020-01-01

Abstract

Estimating the limbs pose in a wearable way may benefit multiple areas such as rehabilitation, teleoperation, human-robot interaction, gaming, and many more. Several solutions are commercially available, but they are usually expensive or not wearable/portable. We present a wearable pose estimation system (WePosE), based on inertial measurements units (IMUs), for motion analysis and body tracking. Differently from camera-based approaches, the proposed system does not suffer from occlusion problems and lighting conditions, it is cost effective and it can be used in indoor and outdoor environments. Moreover, since only accelerometers and gyroscopes are used to estimate the orientation, the system can be used also in the presence of iron and magnetic disturbances. An experimental validation using a high precision optical tracker has been performed. Results confirmed the effectiveness of the proposed approach.
2020
Lisini Baldi, T., Farina, F., Garulli, A., Giannitrapani, A., Prattichizzo, D. (2020). Upper Body Pose Estimation Using Wearable Inertial Sensors and Multiplicative Kalman Filter. IEEE SENSORS JOURNAL, 20(1), 492-500 [10.1109/JSEN.2019.2940612].
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Descrizione: Accepted Version. European Union (EU), Horizon 2020 programme. European project “Synergy-based Open-source Foundations and Technologies for Prosthetics and RehabilitatiOn” (SoftPro), H2020 Research & Innovation Action, Grant Agreement n. 688857. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Digital Object Identifier (DOI): 10.1109/JSEN.2019.2940612
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/1089916