Validation of a model-based inverse kinematics approach based on wearable inertial sensors. Issue 16 (10th December 2018)

• Record Type: Journal Article
• Authors: Tagliapietra, L.; Modenese, L.; Ceseracciu, E.; Mazzà, C.; Reggiani, M.
• Is Part Of: Computer methods in biomechanics and biomedical engineering. Volume 21:Issue 16(2018)
• Page Start: 834
• Page End: 844
• Publication Date: 2018-12-10
• Subjects: Inertial and magnetic measurement units -- IMU -- joint kinematics -- inverse kinematics -- global optimization -- OpenSim; Biomechanics -- Data processing -- Periodicals; Biomedical engineering -- Periodicals; Biomechanics -- Periodicals; Biomedical Engineering -- methods -- Periodicals; Computing Methodologies -- Periodicals; 612.7
• DOI: 10.1080/10255842.2018.1522532
• Languages: English
• ISSNs: 1025-5842

Abstract

Abstract: Wearable inertial measurement units (IMUs) are a promising solution to human motion estimation. Using IMUs 3D orientations, a model-driven inverse kinematics methodology to estimate joint angles is presented. Estimated joint angles were validated against encoder-measured kinematics (robot) and against marker-based kinematics (passive mechanism). Results are promising, with RMS angular errors respectively lower than 3 and 6 deg over a minimum range of motion of 50 deg (robot) and 160 deg (passive mechanism). Moreover, a noise robustness analysis revealed that the model-driven approach reduces the effects of experimental noises, making the proposed technique particularly suitable for application in human motion analysis.