“…This is in part because of the difficulties involved in obtaining in-vivo measurements of the scapular movement [Hill et al, 2007, Kontaxis et al, 2009. Recently, a number of studies have developed methods to obtain scapular kinematics in-vivo with relatively high accuracies [Brochard et al, 2011, Prinold et al, 2011, Shaheen et al, 2011a, Shaheen et al, 2011b, Warner et al, 2012.…”
“…This is in part because of the difficulties involved in obtaining in-vivo measurements of the scapular movement [Hill et al, 2007, Kontaxis et al, 2009. Recently, a number of studies have developed methods to obtain scapular kinematics in-vivo with relatively high accuracies [Brochard et al, 2011, Prinold et al, 2011, Shaheen et al, 2011a, Shaheen et al, 2011b, Warner et al, 2012.…”
“…Tracking the acromion shows potential for estimating scapular movement. In the acromion method, either a magnetic sensor [7][8][9][10][11][12] or a photogrammetric marker cluster [13][14][15][16][17][18] is attached to the skin over the flat portion of the acromion, and scapula anatomical landmarks are calibrated with respect to a coordinate system fixed to the scapula. It has been shown that the acromion method accuracy is limited by the presence of soft tissue artifacts, especially when the full range of motion (ROM) of the gleno-humeral joint is explored [7,8,19,20].…”
Section: Introductionmentioning
confidence: 99%
“…Recently, various studies have investigated several factors associated with the use of acromion marker clusters (AMCs) and stereo-photogrammetry that may affect the overall accuracy: (a) the AMC design [13], (b) the shoulder posture selected for the scapula anatomical calibration [17], (c) the AMC attachment location [16], and d) the type of anatomical calibration (single or double) [15]. Moreover, AMC-based scapular motion has been compared to that obtained from skin-marker-based methods [14].…”
Several studies have recently investigated how the implementations of acromion marker clusters (AMCs) method and stereo-photogrammetry affect the estimates of scapula kinematics. However, in the large majority of these studies, the accuracy assessment of the scapular kinematics obtained with AMCs was carried out through a comparative evaluation using a scapula locator that is prone to error. The present study assesses AMC accuracy based on best practice recommendations, both with single and double anatomical calibration implementations, during several passive shoulder movements. Experiments were carried out on three cadaveric specimens. The scapula motion was acquired with a stereo-photogrammetric system using intra-cortical pins. When the scapula kinematics was estimated using an AMC combined with a single anatomical calibration, the accuracy was highly dependent on the specimen and the type of motion (maximum errors between -6.2°and 44.8°) and the scapular motion was generally overestimated. Moreover, with this implementation, scapular orientation errors increased for shoulder configurations distant from the reference shoulder configuration chosen for the calibration procedure. The double calibration implementation greatly improved the estimate of the scapular kinematics for all specimens and types of motion (maximum errors between -1.0°and 14.2°). The double anatomical calibration implementation should be preferred since it reduces the kinematics errors to levels which are acceptable in most clinical applications.
“…This idea is the basis of 40 techniques like the double calibration, whereby the motion of markers in the bone frame 41 is linearly interpolated between previously measured positions at the ends of the motion 42 cycle Brochard et al, 2011 To simplify the calculations, the proximal segment was considered to be fixed, so that 53 all the kinematic variables represent the relative motion of the distal segment, as seen in 54 the proximal reference frame. Quaternions were preferred to other ways of representing 55 rotations like matrices, Euler angles or orientation vectors, because they allowed more 56 compact mathematical models of CoR errors, although it would be possible to derive 57 such models from any other representation.…”
This paper presents a mathematical model for the propagation of errors in body segment kinematics to the location of the center of rotation. Three functional calibration techniques, usually employed for the gleno-humeral joint, are studied: the methods based on the pivot of the instantaneous helical axis (PIHA) or the finite helical axis (PFHA), and the "symmetrical center of rotation estimation" (SCoRE). A procedure for correcting the effect of soft tissue artifacts is also proposed, based on the equations of those techniques and a model of the artifact, like the one that can be obtained by double calibration. An experiment with a mechanical analogue was performed to validate the procedure and compare the performance of each technique. The raw error (between 57 and 68 mm) was reduced by a proportion of between 1:6 and less than 1:15, depending on the artifact model and the mathematical method. The best corrections were obtained by the SCoRE method. Some recommendations about the experimental setup for functional calibration techniques and the choice of a mathematical method are derived from theoretical considerations about the formulas and the results of the experiment.
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