ORCID Profile
0000-0002-5029-1892
Current Organisation
Università degli Studi di Padova
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Publisher: Elsevier BV
Date: 11-2015
Publisher: IEEE
Date: 09-2015
Publisher: IEEE
Date: 11-2009
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2017
Publisher: Informa UK Limited
Date: 23-11-2018
DOI: 10.1080/10255842.2018.1522532
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.
Publisher: IEEE
Date: 11-2013
Publisher: Elsevier BV
Date: 2016
DOI: 10.1016/J.JBIOMECH.2015.11.006
Abstract: A challenging aspect of subject specific musculoskeletal modeling is the estimation of muscle parameters, especially optimal fiber length and tendon slack length. In this study, the method for scaling musculotendon parameters published by Winby et al. (2008), J. Biomech. 41, 1682-1688, has been reformulated, generalized and applied to two cases of practical interest: 1) the adjustment of muscle parameters in the entire lower limb following linear scaling of a generic model and 2) their estimation "from scratch" in a subject specific model of the hip joint created from medical images. In the first case, the procedure maintained the muscles׳ operating range between models with mean errors below 2.3% of the reference model normalized fiber length value. In the second case, a subject specific model of the hip joint was created using segmented bone geometries and muscle volumes publicly available for a cadaveric specimen from the Living Human Digital Library (LHDL). Estimated optimal fiber lengths were found to be consistent with those of a previously published dataset for all 27 considered muscle bundles except gracilis. However, computed tendon slack lengths differed from tendon lengths measured in the LHDL cadaver, suggesting that tendon slack length should be determined via optimization in subject-specific applications. Overall, the presented methodology could adjust the parameters of a scaled model and enabled the estimation of muscle parameters in newly created subject specific models. All data used in the analyses are of public domain and a tool implementing the algorithm is available at ome/opt_muscle_par.
Publisher: IEEE
Date: 09-2010
Publisher: Springer International Publishing
Date: 03-09-2015
Publisher: IEEE
Date: 05-2013
Publisher: IEEE
Date: 05-2010
Publisher: IEEE
Date: 08-2015
Publisher: Elsevier BV
Date: 02-2012
Publisher: Informa UK Limited
Date: 10-10-2016
Publisher: American Physiological Society
Date: 10-2015
Abstract: This work presents an electrophysiologically and dynamically consistent musculoskeletal model to predict stiffness in the human ankle and knee joints as derived from the joints constituent biological tissues (i.e., the spanning musculotendon units). The modeling method we propose uses electromyography (EMG) recordings from 13 muscle groups to drive forward dynamic simulations of the human leg in five healthy subjects during overground walking and running. The EMG-driven musculoskeletal model estimates musculotendon and resulting joint stiffness that is consistent with experimental EMG data as well as with the experimental joint moments. This provides a framework that allows for the first time observing 1) the elastic interplay between the knee and ankle joints, 2) the in idual muscle contribution to joint stiffness, and 3) the underlying co-contraction strategies. It provides a theoretical description of how stiffness modulates as a function of muscle activation, fiber contraction, and interacting tendon dynamics. Furthermore, it describes how this differs from currently available stiffness definitions, including quasi-stiffness and short-range stiffness. This work offers a theoretical and computational basis for describing and investigating the neuromuscular mechanisms underlying human locomotion.
Publisher: Public Library of Science (PLoS)
Date: 26-12-2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2012
Publisher: Springer Science and Business Media LLC
Date: 16-11-2015
Publisher: IEEE
Date: 06-2011
Publisher: Springer International Publishing
Date: 2014
No related grants have been discovered for Monica Reggiani.