Quantification of soft tissue artifact in lower limb human motion analysis: A systematic review

Peters, Alana; Galna, Brook; Sangeux, Morgan; Morris, Meg E.; Baker, Richard

doi:10.1016/j.gaitpost.2009.09.004

Cited by 276 publications

(185 citation statements)

References 49 publications

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“…An intra-and inter-variability also appeared across the three subjects performing the running task although some similar patterns of force was observed. As STA is well known to be subject-and task-specific (Leardini et al, 2005;Peters et al, 2010), it was expected to obtain such differences.…”

Section: Discussionmentioning

confidence: 99%

“…It has been described, from a kinematics point of view, as the soft tissue artefact (STA). Indeed, this relative movement has a deleterious effect on the joint kinematics estimated from skin markers and motion capture systems (Leardini et al, 2005;Peters et al, 2010). At the same time, from a dynamics point of view, the soft tissue motion, modelled as wobbling masses connected to the rigid-body model of the lower limb, is also recognised to have an effect on the joint kinetics (i.e.…”

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confidence: 99%

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Stiffness of a wobbling mass models analysed by a smooth orthogonal decomposition of the skin movement relative to the underlying bone

Dumas

Jacquelin

2017

Journal of Biomechanics

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Please cite this article as: R. Dumas, E. Jacquelin, Stiffness of a wobbling mass models analysed by a smooth orthogonal decomposition of the skin movement relative to the underlying bone, Journal of Biomechanics (2017), doi: http://dx.doi.org/10. 1016/j.jbiomech.2017.06.002 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Stiffness of a wobbling mass models analysed by a smooth orthogonal decomposition of the skin movement relative to the underlying bone AbstractThe so-called soft tissue artefacts and wobbling masses have both been widely studied in biomechanics, however most of the time separately, from either a kinematics or a dynamics point of view. As such, the estimation of the stiffness of the springs connecting the wobbling masses to the rigid-body model of the lower limb, based on the in vivo displacements of the skin relative to the underling bone, has not been performed yet. For this estimation, the displacements of the skin markers in the bone-embedded coordinate systems are viewed as a proxy for the wobbling mass movement.The present study applied a structural vibration analysis method called smooth orthogonal decomposition to estimate this stiffness from retrospective simultaneous measurements of skin and intra-cortical pin markers during running, walking, cutting and hopping.For the translations about the three axes of the bone-embedded coordinate systems, the estimated stiffness coefficients (i.e. between 2.3 kN/m and 55.5 kN/m) as well as the corresponding forces representing the connection between bone and skin (i.e. up to 400 N) and corresponding frequencies (i.e. in the band 10-30 Hz) were in agreement with the literature. Consistently with the STA descriptions, the estimated stiffness coefficients were found subject-and task-specific.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

Stiffness of a wobbling mass models analysed by a smooth orthogonal decomposition of the skin movement relative to the underlying bone

Dumas

Jacquelin

2017

Journal of Biomechanics

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“…STA is caused by a combination of skin stretching and sliding, muscle contractions, gravity and inertial effects (Leardini et al, 2005;Peters et al, 2010). Commonly used bone pose estimators (BPEs) define an appropriate marker cluster model and match the model with the measured marker trajectories at each time step by solving a least squares (LS) minimization problem constraining the cluster transformation to a translation and a rotation, with or without uniform scaling (Cappello et al, 1996;Challis, 1995;Söderkvist and Wedin, 1993;Spoor and Veldpaus, 1980).…”

Section: Introductionmentioning

confidence: 99%

Bone orientation and position estimation errors using Cosserat point elements and least squares methods: Application to gait

Solav

Camomilla

Cereatti

et al. 2017

Journal of Biomechanics

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The aim of this study was to analyze the accuracy of bone pose estimation based on sub-clusters of three skinmarkers characterized by triangular Cosserat point elements (TCPEs) and to evaluate the capability of four instantaneous physical parameters, which can be measured non-invasively in-vivo, to identify the most accurate TCPEs. Moreover, TCPE pose estimations were compared with the estimations of two least squares minimization methods applied to the cluster of all markers, using rigid body (RBLS) and homogeneous deformation (HDLS) assumptions. Analysis was performed on previously collected in-vivo treadmill gait data composed of simultaneous measurements of the gold-standard bone pose by bi-plane fluoroscopy tracking the subjects' knee prosthesis and a stereophotogrammetric system tracking skin-markers affected by soft tissue artifact. Femur orientation and position errors estimated from skin-marker clusters were computed for 18 subjects using clusters of up to 35 markers. Results based on gold-standard data revealed that instantaneous subsets of TCPEs exist which estimate the femur pose with reasonable accuracy (median root mean square error during stance/swing: 1.4/2.8 deg for orientation, 1.5/4.2 mm for position). A non-invasive and instantaneous criteria to select accurate TCPEs for pose estimation (4.8/7.3 deg, 5.8/12.3 mm), was compared with RBLS (4.3/6.6 deg, 6.9/16.6 mm) and HDLS (4.6/7.6 deg, 6.7/12.5 mm). Accounting for homogeneous deformation, using HDLS or selected TCPEs, yielded more accurate position estimations than RBLS method, which, conversely, yielded more accurate orientation estimations. Further investigation is required to devise effective criteria for cluster selection that could represent a significant improvement in bone pose estimation accuracy.

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“…When non-invasive techniques such as stereophotogrammetry are used, the accurate estimation of the position and orientation (pose) of a rigid bony segment from the measured position of markers attached to the skin is limited mostly by the relative motion between the markers and the bone, which is known as the Soft Tissue Artifact (STA) 26 . In the literature, several methods have been proposed that employ clusters composed of a redundant number of skin markers (>3) and which exploit this redundancy to minimize the effect of the STA on the estimation of the underlying bone pose, but no satisfactory solution yet exists 26,29 .…”

Section: Introductionmentioning

confidence: 99%

Bone Pose Estimation in the Presence of Soft Tissue Artifact Using Triangular Cosserat Point Elements

Solav¹,

Rubin²,

Cereatti³

et al. 2017

Preprint

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Accurate estimation of the position and orientation (pose) of a bone from a cluster of skin markers is limited mostly by the relative motion between the bone and the markers, which is known as the Soft Tissue Artifact (STA). This work presents a method, based on continuum mechanics, to describe the kinematics of a cluster affected by STA. The cluster is characterized by Triangular Cosserat Point Elements (TCPEs) defined by all combinations of three markers.The effects of the STA on the TCPEs are quantified using three parameters describing the strain in each TCPE and the relative rotation and translation between TCPEs. The method was evaluated using previously collected ex-vivo kinematic data. Femur pose was estimated from 12 skin markers on the thigh, while its reference pose was measured using bone pins. Analysis revealed that instantaneous subsets of TCPEs exist which estimate bone position and orientation more accurately than the Procrustes Superimposition applied to the cluster of all markers. It has been shown that some of these parameters correlate well with femur pose errors, which suggests that they can be used to select, at each instant, subsets of TCPEs leading an improved estimation of the underlying bone pose.2

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Quantification of soft tissue artifact in lower limb human motion analysis: A systematic review

Cited by 276 publications

References 49 publications

Stiffness of a wobbling mass models analysed by a smooth orthogonal decomposition of the skin movement relative to the underlying bone

Stiffness of a wobbling mass models analysed by a smooth orthogonal decomposition of the skin movement relative to the underlying bone

Bone orientation and position estimation errors using Cosserat point elements and least squares methods: Application to gait

Bone Pose Estimation in the Presence of Soft Tissue Artifact Using Triangular Cosserat Point Elements

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