Main component of soft tissue artifact of the upper-limbs with respect to different functional, daily life and sports movements
Introduction
The assessment of human body kinematics is essential in many research fields such as orthopedics, ergonomics and sport biomechanics. Accuracy of the skeleton pose estimate is dependent of the methods used to record body kinematics. Usually, trajectories of reflective markers stuck on the skin are recorded using stereophotogrammetry. Nevertheless, skin marker trajectories are affected by the soft tissue artifact (STA) defined as the relative movement between each skin marker and its underlying bone (Leardini et al., 2005, Peters et al., 2010). Since STA representations vary among literature, Dumas et al. (2014a) have proposed a generalized mathematical representation of the STA: individual marker displacements, marker-cluster geometrical transformations and skin envelope shape variations. Among these three representations, STA are more usually described either by individual marker displacements or marker-cluster geometrical transformations (Alexander and Andriacchi, 2001, Andriacchi et al., 1998, Benoit et al., 2015, Dumas and Cheze, 2009).
The ultimate purpose of STA assessment is to implement methods in order to improve kinematics estimation. These methods can be used either to define mathematical models that can be embedded in optimal bone pose estimator (Alexander and Andriacchi, 2001, Bonci et al., 2014, Camomilla et al., 2015, Camomilla et al., 2013), to implement functional algorithms for locating joint rotation center (De Rosario et al., 2013) or to assess the dynamic effects of the wobbling mass (Bélaise et al., 2016, Thouze et al., 2015). As STA may not be defined a priori because they are subject-, task- and segment-specific, a calibration (i.e. identification of the components that define the STA and of the parameters that model these components) is necessary for each studied movement. Consequently, some studies aimed at describing the components, among individual marker displacements or marker-cluster geometrical transformations that best describe STA. These studies have been performed exclusively concerning the lower-limb STA. Briefly, these investigations pointed out which skin markers located on the thigh and shank were the most subject to the STA (Akbarshahi et al., 2010, Dumas et al., 2014b, Kuo et al., 2011, Tsai et al., 2011). In addition, it was observed that STA of the lower limbs were mainly explained by rigid transformations (i.e. translations and rotations) and in a less manner by deformations (i.e. homotheties and stretches) of the marker-cluster (Andersen et al., 2012, Barre et al., 2015, Barre et al., 2013, Benoit et al., 2015, Benoit et al., 2006, de Rosario et al., 2012, Dumas et al., 2014b, Grimpampi et al., 2014). Although many studies give either qualitative or quantitative information about STA for the lower limbs, no data is available in the literature concerning the characterization of the STA for the upper-limb.
The objective of this study was to describe the main components that best represent the STA of the shoulder complex and arm during functional arm movements and daily-life or sports movements. Firstly, the description of the displacement of the individual skin markers was analyzed. Secondly, special consideration was given to the analysis of marker-cluster geometrical transformations. To that purpose, the trajectories of the skin markers relative to the bone were computed using reflective markers secured to intra-cortical pins. As STA has been shown to be task-specific, the analysis focused on movements with different amplitudes, degrees of freedom and velocities. To that aim, arm flexions and rotations as well as hair combing and hockey shooting were investigated. According the studies about the STA of the lower limb, it was hypothesized, that the STA energy was task-, location- segment- and subject-specific, while the rigid transformations of the marker-cluster explained the main part of the STA energy.
Section snippets
Participants
The raw data obtained by Dal Maso et al. (2014) have been used in this study. Four healthy male participants (age ranged between 27 and 41 years, mass ranged between 57 and 115 kg, height ranged between 1.65 and 1.82 m) volunteered to participate in this study. They signed an informed consent which was approved by the Karolinska Institute (Sweden) and the University of Montreal (Canada) ethics committees. None of the participants presented current or previous shoulder injuries.
Instrumentation
Four or five
Results
First of all, as the pin inserted into the scapula rotated a few degrees for two participants, the data concerning the scapula were given for only two remaining participants. The joint angles of each movement computed with the pin markers were presented in Fig. 2. The durations of the movements were 3.63±1.16 s, 1.57±0.31 s, 1.34±0.45 s and 0.94±0.54 s for the arm flexion/extension, arm rotation, combing mimic and hockey shooting mimic respectively.
Discussion
The purpose of this study was to describe the main components that best describe the STA of the shoulder complex and arm during functional arm movements and daily-life or sports movements. To that aim, the percentage of the total STA energy explained either by individual marker displacements or marker-cluster geometrical transformations was computed. Our hypotheses were confirmed since we firstly observed that the individual marker displacements were task- location- and subject-specific.
Conclusion
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. STA was found task-, location- and subject-specific when analyzing the individual skin marker displacements. Consequently considering individual
Conflict of interest
None of the authors are in conflict of interest with regards to this research.
Acknowledgement
This work was partially funded by NSERC, Canada discovery (#RGPIN-2014-03912) grant. The first author is scholar of the Méditis program (NSERC, CREATE).
References (31)
- et al.
Non-invasive assessment of soft-tissue artifact and its effect on knee joint kinematics during functional activity
J. Biomech.
(2010) - et al.
Correcting for deformation in skin-based marker systems
J. Biomech.
(2001) - et al.
A linear soft tissue artefact model for human movement analysis: proof of concept using in vivo data
Gait Posture
(2012) - et al.
Soft tissue artifact distribution on lower limbs during treadmill gait: influence of skin markers׳ location on cluster design
J. Biomech.
(2015) - et al.
Can optimal marker weightings improve thoracohumeral kinematics accuracy?
J. Biomech.
(2015) - et al.
Surface marker cluster translation, rotation, scaling and deformation: their contribution to soft tissue artefact and impact on knee joint kinematics
J. Biomech.
(2015) - et al.
Effect of skin movement artifact on knee kinematics during gait and cutting motions measured in vivo
Gait Posture
(2006) - et al.
A soft tissue artefact model driven by proximal and distal joint kinematics
J. Biomech.
(2014) - et al.
A model of soft tissue artefact rigid component
J. Biomech.
(2015) - et al.
A hip joint kinematics driven model for the generation of realistic thigh soft tissue artefacts
J. Biomech.
(2013)