Literature DB >> 26795123

Estimating 3D L5/S1 moments and ground reaction forces during trunk bending using a full-body ambulatory inertial motion capture system.

G S Faber1, C C Chang2, I Kingma3, J T Dennerlein4, J H van Dieën3.   

Abstract

Inertial motion capture (IMC) systems have become increasingly popular for ambulatory movement analysis. However, few studies have attempted to use these measurement techniques to estimate kinetic variables, such as joint moments and ground reaction forces (GRFs). Therefore, we investigated the performance of a full-body ambulatory IMC system in estimating 3D L5/S1 moments and GRFs during symmetric, asymmetric and fast trunk bending, performed by nine male participants. Using an ambulatory IMC system (Xsens/MVN), L5/S1 moments were estimated based on the upper-body segment kinematics using a top-down inverse dynamics analysis, and GRFs were estimated based on full-body segment accelerations. As a reference, a laboratory measurement system was utilized: GRFs were measured with Kistler force plates (FPs), and L5/S1 moments were calculated using a bottom-up inverse dynamics model based on FP data and lower-body kinematics measured with an optical motion capture system (OMC). Correspondence between the OMC+FP and IMC systems was quantified by calculating root-mean-square errors (RMSerrors) of moment/force time series and the interclass correlation (ICC) of the absolute peak moments/forces. Averaged over subjects, L5/S1 moment RMSerrors remained below 10Nm (about 5% of the peak extension moment) and 3D GRF RMSerrors remained below 20N (about 2% of the peak vertical force). ICCs were high for the peak L5/S1 extension moment (0.971) and vertical GRF (0.998). Due to lower amplitudes, smaller ICCs were found for the peak asymmetric L5/S1 moments (0.690-0.781) and horizontal GRFs (0.559-0.948). In conclusion, close correspondence was found between the ambulatory IMC-based and laboratory-based estimates of back load.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Inertial measurement unit (IMU); Inertial sensors; Low back loading; Occupational biomechanics; Physical exposure

Mesh:

Year:  2015        PMID: 26795123     DOI: 10.1016/j.jbiomech.2015.11.042

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  21 in total

1.  Classifying hazardous movements and loads during manual materials handling using accelerometers and instrumented insoles.

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Review 2.  A Systematic Review on Evaluation Strategies for Field Assessment of Upper-Body Industrial Exoskeletons: Current Practices and Future Trends.

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Journal:  Ann Biomed Eng       Date:  2022-08-02       Impact factor: 4.219

3.  Recent Machine Learning Progress in Lower Limb Running Biomechanics With Wearable Technology: A Systematic Review.

Authors:  Liangliang Xiang; Alan Wang; Yaodong Gu; Liang Zhao; Vickie Shim; Justin Fernandez
Journal:  Front Neurorobot       Date:  2022-06-02       Impact factor: 3.493

4.  Ability of Wearable Accelerometers-Based Measures to Assess the Stability of Working Postures.

Authors:  Liangjie Guo; Junhui Kou; Mingyu Wu
Journal:  Int J Environ Res Public Health       Date:  2022-04-13       Impact factor: 4.614

5.  Barriers to the Adoption of Wearable Sensors in the Workplace: A Survey of Occupational Safety and Health Professionals.

Authors:  Mark C Schall; Richard F Sesek; Lora A Cavuoto
Journal:  Hum Factors       Date:  2018-01-10       Impact factor: 3.598

6.  Examination of Inertial Sensor-Based Estimation Methods of Lower Limb Joint Moments and Ground Reaction Force: Results for Squat and Sit-to-Stand Movements in the Sagittal Plane.

Authors:  Jun Kodama; Takashi Watanabe
Journal:  Sensors (Basel)       Date:  2016-08-01       Impact factor: 3.576

7.  Estimation of Ground Reaction Forces and Moments During Gait Using Only Inertial Motion Capture.

Authors:  Angelos Karatsidis; Giovanni Bellusci; H Martin Schepers; Mark de Zee; Michael S Andersen; Peter H Veltink
Journal:  Sensors (Basel)       Date:  2016-12-31       Impact factor: 3.576

8.  Estimation of Vertical Ground Reaction Forces and Sagittal Knee Kinematics During Running Using Three Inertial Sensors.

Authors:  Frank J Wouda; Matteo Giuberti; Giovanni Bellusci; Erik Maartens; Jasper Reenalda; Bert-Jan F van Beijnum; Peter H Veltink
Journal:  Front Physiol       Date:  2018-03-22       Impact factor: 4.566

9.  Accuracy of Base of Support Using an Inertial Sensor Based Motion Capture System.

Authors:  Liangjie Guo; Shuping Xiong
Journal:  Sensors (Basel)       Date:  2017-09-12       Impact factor: 3.576

Review 10.  Wearable technology for spine movement assessment: A systematic review.

Authors:  Enrica Papi; Woon Senn Koh; Alison H McGregor
Journal:  J Biomech       Date:  2017-10-07       Impact factor: 2.712

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