Literature DB >> 27379397

Validation of inertial measurement units with an optoelectronic system for whole-body motion analysis.

Xavier Robert-Lachaine1, Hakim Mecheri2, Christian Larue2, André Plamondon2.   

Abstract

The potential of inertial measurement units (IMUs) for ergonomics applications appears promising. However, previous IMUs validation studies have been incomplete regarding aspects of joints analysed, complexity of movements and duration of trials. The objective was to determine the technological error and biomechanical model differences between IMUs and an optoelectronic system and evaluate the effect of task complexity and duration. Whole-body kinematics from 12 participants was recorded simultaneously with a full-body Xsens system where an Optotrak cluster was fixed on every IMU. Short functional movements and long manual material handling tasks were performed and joint angles were compared between the two systems. The differences attributed to the biomechanical model showed significantly greater (P ≤ .001) RMSE than the technological error. RMSE was systematically higher (P ≤ .001) for the long complex task with a mean on all joints of 2.8° compared to 1.2° during short functional movements. Definition of local coordinate systems based on anatomical landmarks or single posture was the most influent difference between the two systems. Additionally, IMUs accuracy was affected by the complexity and duration of the tasks. Nevertheless, technological error remained under 5° RMSE during handling tasks, which shows potential to track workers during their daily labour.

Entities:  

Keywords:  Evaluation; Inertial sensor; Performance; Task complexity; Validation

Mesh:

Year:  2016        PMID: 27379397     DOI: 10.1007/s11517-016-1537-2

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  28 in total

1.  New least squares solutions for estimating the average centre of rotation and the axis of rotation.

Authors:  Sahan S Hiniduma Udugama Gamage; Joan Lasenby
Journal:  J Biomech       Date:  2002-01       Impact factor: 2.712

2.  Evaluating the properties of the coefficient of multiple correlation (CMC) for kinematic gait data.

Authors:  J Røislien; O Skare; A Opheim; L Rennie
Journal:  J Biomech       Date:  2012-06-04       Impact factor: 2.712

3.  Accuracy of inertial motion sensors in static, quasistatic, and complex dynamic motion.

Authors:  Alison Godwin; Michael Agnew; Joan Stevenson
Journal:  J Biomech Eng       Date:  2009-11       Impact factor: 2.097

4.  Assessment of three-dimensional joint kinematics of the upper limb during simulated swimming using wearable inertial-magnetic measurement units.

Authors:  Silvia Fantozzi; Andrea Giovanardi; Fabrício Anício Magalhães; Rocco Di Michele; Matteo Cortesi; Giorgio Gatta
Journal:  J Sports Sci       Date:  2015-09-14       Impact factor: 3.337

5.  Magnetic distortion in motion labs, implications for validating inertial magnetic sensors.

Authors:  W H K de Vries; H E J Veeger; C T M Baten; F C T van der Helm
Journal:  Gait Posture       Date:  2009-01-15       Impact factor: 2.840

6.  Concurrent validation of Xsens MVN measurement of lower limb joint angular kinematics.

Authors:  Jun-Tian Zhang; Alison C Novak; Brenda Brouwer; Qingguo Li
Journal:  Physiol Meas       Date:  2013-07-26       Impact factor: 2.833

7.  First in vivo assessment of "Outwalk": a novel protocol for clinical gait analysis based on inertial and magnetic sensors.

Authors:  Alberto Ferrari; Andrea Giovanni Cutti; Pietro Garofalo; Michele Raggi; Monique Heijboer; Angelo Cappello; Angelo Davalli
Journal:  Med Biol Eng Comput       Date:  2009-11-13       Impact factor: 2.602

8.  Shoulder and elbow joint angle tracking with inertial sensors.

Authors:  Mahmoud El-Gohary; James McNames
Journal:  IEEE Trans Biomed Eng       Date:  2012-09       Impact factor: 4.538

9.  Prediction of the hip joint centre in adults, children, and patients with cerebral palsy based on magnetic resonance imaging.

Authors:  M E Harrington; A B Zavatsky; S E M Lawson; Z Yuan; T N Theologis
Journal:  J Biomech       Date:  2006-04-03       Impact factor: 2.712

10.  The use of inertial sensors system for human motion analysis.

Authors:  Antonio I Cuesta-Vargas; Alejandro Galán-Mercant; Jonathan M Williams
Journal:  Phys Ther Rev       Date:  2010-12
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  58 in total

1.  Prediction of lower limb joint angles and moments during gait using artificial neural networks.

Authors:  Marion Mundt; Wolf Thomsen; Tom Witter; Arnd Koeppe; Sina David; Franz Bamer; Wolfgang Potthast; Bernd Markert
Journal:  Med Biol Eng Comput       Date:  2019-12-11       Impact factor: 2.602

2.  IMU-based sensor-to-segment multiple calibration for upper limb joint angle measurement-a proof of concept.

Authors:  Mahdi Zabat; Amina Ababou; Noureddine Ababou; Raphaël Dumas
Journal:  Med Biol Eng Comput       Date:  2019-08-30       Impact factor: 2.602

3.  Development of a Smart Hallway for Marker-Less Human Foot Tracking and Stride Analysis.

Authors:  Vinod Gutta; Pascal Fallavollita; Natalie Baddour; Edward D Lemaire
Journal:  IEEE J Transl Eng Health Med       Date:  2021-03-29       Impact factor: 3.316

4.  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

5.  Motor Control Training for the Shoulder with Smart Garments.

Authors:  Qi Wang; Liesbet De Baets; Annick Timmermans; Wei Chen; Luca Giacolini; Thomas Matheve; Panos Markopoulos
Journal:  Sensors (Basel)       Date:  2017-07-22       Impact factor: 3.576

Review 6.  Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion.

Authors:  Alessandro Filippeschi; Norbert Schmitz; Markus Miezal; Gabriele Bleser; Emanuele Ruffaldi; Didier Stricker
Journal:  Sensors (Basel)       Date:  2017-06-01       Impact factor: 3.576

7.  Inertial measurement systems for segments and joints kinematics assessment: towards an understanding of the variations in sensors accuracy.

Authors:  Karina Lebel; Patrick Boissy; Hung Nguyen; Christian Duval
Journal:  Biomed Eng Online       Date:  2017-05-15       Impact factor: 2.819

8.  Inertial Measurement Units for Clinical Movement Analysis: Reliability and Concurrent Validity.

Authors:  Mohammad Al-Amri; Kevin Nicholas; Kate Button; Valerie Sparkes; Liba Sheeran; Jennifer L Davies
Journal:  Sensors (Basel)       Date:  2018-02-28       Impact factor: 3.576

9.  Combining Ergonomic Risk Assessment (RULA) with Inertial Motion Capture Technology in Dentistry-Using the Benefits from Two Worlds.

Authors:  Christian Maurer-Grubinger; Fabian Holzgreve; Laura Fraeulin; Werner Betz; Christina Erbe; Doerthe Brueggmann; Eileen M Wanke; Albert Nienhaus; David A Groneberg; Daniela Ohlendorf
Journal:  Sensors (Basel)       Date:  2021-06-13       Impact factor: 3.576

10.  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

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