Literature DB >> 33807832

Real-Time Musculoskeletal Kinematics and Dynamics Analysis Using Marker- and IMU-Based Solutions in Rehabilitation.

Dimitar Stanev1,2, Konstantinos Filip2, Dimitrios Bitzas2, Sokratis Zouras2, Georgios Giarmatzis2, Dimitrios Tsaopoulos3, Konstantinos Moustakas2.   

Abstract

This study aims to explore the possibility of estimating a multitude of kinematic and dynamic quantities using subject-specific musculoskeletal models in real-time. The framework was designed to operate with marker-based and inertial measurement units enabling extensions far beyond dedicated motion capture laboratories. We present the technical details for calculating the kinematics, generalized forces, muscle forces, joint reaction loads, and predicting ground reaction wrenches during walking. Emphasis was given to reduce computational latency while maintaining accuracy as compared to the offline counterpart. Notably, we highlight the influence of adequate filtering and differentiation under noisy conditions and its importance for consequent dynamic calculations. Real-time estimates of the joint moments, muscle forces, and reaction loads closely resemble OpenSim's offline analyses. Model-based estimation of ground reaction wrenches demonstrates that even a small error can negatively affect other estimated quantities. An application of the developed system is demonstrated in the context of rehabilitation and gait retraining. We expect that such a system will find numerous applications in laboratory settings and outdoor conditions with the advent of predicting or sensing environment interactions. Therefore, we hope that this open-source framework will be a significant milestone for solving this grand challenge.

Entities:  

Keywords:  dynamics; ground reactions; inertial measurement units; joint reactions; kinematics; muscle forces; musculoskeletal; real-time

Mesh:

Year:  2021        PMID: 33807832      PMCID: PMC7961635          DOI: 10.3390/s21051804

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  37 in total

1.  Gait retraining to reduce the knee adduction moment through real-time visual feedback of dynamic knee alignment.

Authors:  Joaquin A Barrios; Kay M Crossley; Irene S Davis
Journal:  J Biomech       Date:  2010-05-08       Impact factor: 2.712

2.  Compliant bipedal model with the center of pressure excursion associated with oscillatory behavior of the center of mass reproduces the human gait dynamics.

Authors:  Chang Keun Jung; Sukyung Park
Journal:  J Biomech       Date:  2013-10-08       Impact factor: 2.712

3.  Is my model good enough? Best practices for verification and validation of musculoskeletal models and simulations of movement.

Authors:  Jennifer L Hicks; Thomas K Uchida; Ajay Seth; Apoorva Rajagopal; Scott L Delp
Journal:  J Biomech Eng       Date:  2015-01-26       Impact factor: 2.097

4.  Prediction of ground reaction forces and moments during various activities of daily living.

Authors:  R Fluit; M S Andersen; S Kolk; N Verdonschot; H F J M Koopman
Journal:  J Biomech       Date:  2014-04-29       Impact factor: 2.712

5.  Ground reaction force estimation using an insole-type pressure mat and joint kinematics during walking.

Authors:  Yihwan Jung; Moonki Jung; Kunwoo Lee; Seungbum Koo
Journal:  J Biomech       Date:  2014-05-22       Impact factor: 2.712

6.  Real-time inverse kinematics and inverse dynamics for lower limb applications using OpenSim.

Authors:  C Pizzolato; M Reggiani; L Modenese; D G Lloyd
Journal:  Comput Methods Biomech Biomed Engin       Date:  2016-10-10       Impact factor: 1.763

7.  Gait retraining using real-time feedback in patients with medial knee osteoarthritis: Feasibility and effects of a six-week gait training program.

Authors:  R Richards; J C van den Noort; M van der Esch; M J Booij; J Harlaar
Journal:  Knee       Date:  2018-06-20       Impact factor: 2.199

8.  Gauging force by tapping tendons.

Authors:  Jack A Martin; Scott C E Brandon; Emily M Keuler; James R Hermus; Alexander C Ehlers; Daniel J Segalman; Matthew S Allen; Darryl G Thelen
Journal:  Nat Commun       Date:  2018-04-23       Impact factor: 14.919

9.  EMG-driven forward-dynamic estimation of muscle force and joint moment about multiple degrees of freedom in the human lower extremity.

Authors:  Massimo Sartori; Monica Reggiani; Dario Farina; David G Lloyd
Journal:  PLoS One       Date:  2012-12-26       Impact factor: 3.240

10.  Wearable sensors objectively measure gait parameters in Parkinson's disease.

Authors:  Johannes C M Schlachetzki; Jens Barth; Franz Marxreiter; Julia Gossler; Zacharias Kohl; Samuel Reinfelder; Heiko Gassner; Kamiar Aminian; Bjoern M Eskofier; Jürgen Winkler; Jochen Klucken
Journal:  PLoS One       Date:  2017-10-11       Impact factor: 3.240

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  1 in total

1.  Fusion of Wearable Kinetic and Kinematic Sensors to Estimate Triceps Surae Work during Outdoor Locomotion on Slopes.

Authors:  Sara E Harper; Dylan G Schmitz; Peter G Adamczyk; Darryl G Thelen
Journal:  Sensors (Basel)       Date:  2022-02-18       Impact factor: 3.576

  1 in total

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