Can optimal marker weightings improve thoracohumeral kinematics accuracy?

Begon, Mickaël; Maso, Fabien Dal; Arndt, Anton; Monnet, Tony

doi:10.1016/j.jbiomech.2015.03.023

Cited by 19 publications

(12 citation statements)

References 49 publications

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“…Although some studies (Begon et al, 2015;Hamming et al, 2012) assessed the effect of STA on shoulder and upper limb kinematics, to our knowledge, our study was the first one to describe the STA of the shoulder complex (clavicle, scapula and humerus) and may be a benchmark of larger scale study. Our study was performed in a modelling perspective.…”

Section: Resultsmentioning

confidence: 99%

“…Nevertheless, regardless the task and participant, some markers such as CL5 (lateral part of the clavicle) and EpM (medial epicondyle of the humerus) were always few affected by STA. Consequently as suggested by Begon et al (2015) these marker locations (lateral part of the clavicle and medial epicondyle of the humerus) may be relevant for a set using a limited number of markers or when the experimenter looks for a sensor location with small STA. Concerning the scapula, (Matsui et al, 2006) observed similar deviation for the two markers located near the acromion process, while the skin marker located on the inferior angle underwent the highest deviation.…”

Section: Individual Skin Marker Displacementsmentioning

confidence: 99%

“…Nevertheless, as for the lower limb, least squares bone pose estimators, that compensate only for the non-rigid transformations of the marker cluster, can hardly improve the estimation of joint kinematics, in particular for the shoulder joint (Begon et al, 2015). The large proportion of marker-cluster translation also suggests joint dislocation or inter-penetration if the joint displacements are computed from the skin markers.…”

Section: Marker-cluster Geometrical Transformationsmentioning

confidence: 99%

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Main component of soft tissue artifact of the upper-limbs with respect to different functional, daily life and sports movements

Blache

Dumas

Lundberg

et al. 2017

Journal of Biomechanics

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Soft tissue artifact (STA) is the main source of error in kinematic estimation of human movements based on skin markers. Our objective was to determine the components of marker displacements that best describe STA of the shoulder and arm (i.e. clavicle, scapula and humerus). Four participants performed arm flexion and rotation, a daily-life and a sports movement. Three pins with reflective markers were inserted into the clavicle, scapula and humerus. In addition, up to seven skin markers were stuck on each segment. STA was described with a modal approach: individual marker displacements or marker-cluster (i.e. translations, rotations, homotheties and stretches) relative to the local segment coordinate system defined by markers secured to the pins. The modes were then ranked according to the percentage of total STA energy that they explained. Both individual skin marker displacements and marker-cluster geometrical transformations were task-, location-, segment- and subject-specific. However, 85% of the total STA energy was systematically explained by the rigid transformations (i.e. translations and rotations of the marker-cluster). In conclusion, large joint dislocations and limited efficiency of least squares bone pose estimators are expected for the computation of upper limb joint kinematics from skin markers. Future developments shall consider the rigid transformations of marker-clusters in the implementation of an STA model to reduce its effects on kinematics estimation.

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Section: Resultsmentioning

confidence: 99%

Section: Individual Skin Marker Displacementsmentioning

confidence: 99%

Section: Marker-cluster Geometrical Transformationsmentioning

confidence: 99%

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Main component of soft tissue artifact of the upper-limbs with respect to different functional, daily life and sports movements

Blache

Dumas

Lundberg

et al. 2017

Journal of Biomechanics

View full text Add to dashboard Cite

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“…It is clear that sensors placed at different locations on the upper arm will detect different amounts of rotation, resulting in errors on the order of 20-50% of the axial rotation of the humerus [27][28][29]. Multiple methods have been developed to compensate for soft-tissue artifact [27,28,[30][31][32][33][34], but with the exception of [28], these methods were developed for optoelectric motion capture systems and cannot be directly applied to electromagnetic motion capture systems because the algorithms take advantage of the individual markers used in optoelectronic systems. The first step in developing soft-tissue artifact compensation methods for electromagnetic systems is to establish a self-consistent framework for calibration and inverse kinematics, which is the focus of this paper.…”

Section: Limitationsmentioning

confidence: 99%

Tracking Joint Angles During Whole-Arm Movements Using Electromagnetic Sensors

Clark

Dickinson

Loaiza

et al. 2020

Journal of Biomechanical Engineering

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Electromagnetic (EM) motion tracking systems are suitable for many research and clinical applications, including in vivo measurements of whole-arm movements. Unfortunately, the methodology for in vivo measurements of whole-arm movements using EM sensors is not well described in the literature, making it difficult to perform new measurements and all but impossible to make meaningful comparisons between studies. The recommendations of the International Society of Biomechanics (ISB) have provided a great service, but by necessity they do not provide clear guidance or standardization on all required steps. The goal of this paper was to provide a comprehensive methodology for using EM sensors to measure whole-arm movements in vivo. We selected methodological details from past studies that were compatible with the ISB recommendations and suitable for measuring whole-arm movements using EM sensors, filling in gaps with recommendations from our own past experiments. The presented methodology includes recommendations for defining coordinate systems (CSs) and joint angles, placing sensors, performing sensor-to-body calibration, calculating rotation matrices from sensor data, and extracting unique joint angles from rotation matrices. We present this process, including all equations, for both the right and left upper limbs, models with nine or seven degrees-of-freedom (DOF), and two different calibration methods. Providing a detailed methodology for the entire process in one location promotes replicability of studies by allowing researchers to clearly define their experimental methods. It is hoped that this paper will simplify new investigations of whole-arm movement using EM sensors and facilitate comparison between studies.

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“… Measurement limitations : The large axial rotation of the humerus results in significant soft tissue artefacts (STAs) [ 4 , 48 , 50 , 52 – 59 ], which presents measurement limitations. Recently, a study based on intra-cortical pins successfully quantified the effects of STA on humeral kinematics [ 60 ]. Additionally, a study by Naaim et al [ 61 ] compares various multibody optimisation models in STA compensation for different ST joint models.…”

Section: Challenges In Investigating Human Shoulder Kinematicsmentioning

confidence: 99%

A survey of human shoulder functional kinematic representations

Krishnan

Björsell

Gutierrez-Farewik

et al. 2018

Med Biol Eng Comput

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In this survey, we review the field of human shoulder functional kinematic representations. The central question of this review is to evaluate whether the current approaches in shoulder kinematics can meet the high-reliability computational challenge. This challenge is posed by applications such as robot-assisted rehabilitation. Currently, the role of kinematic representations in such applications has been mostly overlooked. Therefore, we have systematically searched and summarised the existing literature on shoulder kinematics. The shoulder is an important functional joint, and its large range of motion (ROM) poses several mathematical and practical challenges. Frequently, in kinematic analysis, the role of the shoulder articulation is approximated to a ball-and-socket joint. Following the high-reliability computational challenge, our review challenges this inappropriate use of reductionism. Therefore, we propose that this challenge could be met by kinematic representations, that are redundant, that use an active interpretation and that emphasise on functional understanding.

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Can optimal marker weightings improve thoracohumeral kinematics accuracy?

Cited by 19 publications

References 49 publications

Main component of soft tissue artifact of the upper-limbs with respect to different functional, daily life and sports movements

Main component of soft tissue artifact of the upper-limbs with respect to different functional, daily life and sports movements

Tracking Joint Angles During Whole-Arm Movements Using Electromagnetic Sensors

A survey of human shoulder functional kinematic representations

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