The sensitivity of joint kinematics and kinetics to marker placement during a change of direction task

McFadden, Ciarán; Daniels, Katherine; Strike, Siobhán

doi:10.1016/j.jbiomech.2020.109635

Cited by 27 publications

(16 citation statements)

References 44 publications

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“…Errors are likely to vary at different times, which was also highlighted by the reference trail comparison as most IMC (except rotation) measures examined were within the benchmark. This is in line with previous studies [25,28].…”

Section: Discussionsupporting

confidence: 94%

“…Errors or inconsistencies (e.g., due to differences in thickness of subcutaneous fat) in the placement of markers relative to target anatomical landmarks is thus the single greatest contributor to measurement variability in contemporary clinical gait analysis [22]. It affects the kinematic measures by up to 15 degrees in the sagittal plane, 15 degrees in the transversal plane and 17 degrees in the transverse plane [22][23][24][25][26]. In interpreting the accuracy and precision found for the IMC system in this study, we compared the bias and RMSD to those previously reported for MMC-based systems, resulting from marker placement error within, and between, assessors ( Table 2).…”

Section: Discussionmentioning

confidence: 99%

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Agreement between Inertia and Optical Based Motion Capture during the VU-Return-to-Play- Field-Test

Richter

Daniels

King

et al. 2020

Sensors

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The validity of an inertial sensor-based motion capture system (IMC) has not been examined within the demands of a sports-specific field movement test. This study examined the validity of an IMC during a field test (VU®) by comparing it to an optical marker-based motion capture system (MMC). Expected accuracy and precision benchmarks were computed by comparing the outcomes of a linear and functional joint fitting model within the MMC. The kinematics from the IMC in sagittal plane demonstrated correlations (r2) between 0.76 and 0.98 with root mean square differences (RMSD) < 5°, only the knee bias was within the benchmark. In the frontal plane, r2 ranged between 0.13 and 0.80 with RMSD < 10°, while the knee and hip bias was within the benchmark. For the transversal plane, r2 ranged 0.11 to 0.93 with RMSD < 7°, while the ankle, knee and hip bias remained within the benchmark. The findings indicate that ankle kinematics are not interchangeable with MMC, that hip flexion and pelvis tilt higher in IMC than MMC, while other measures are comparable to MMC. Higher pelvis tilt/hip flexion in the IMC can be explained by a one sensor tilt estimation, while ankle kinematics demonstrated a considerable level of disagreement, which is likely due to four reasons: A one sensor estimation, sensor/marker attachment, movement artefacts of shoe sole and the ankle model used.

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Section: Discussionsupporting

confidence: 94%

Section: Discussionmentioning

confidence: 99%

Agreement between Inertia and Optical Based Motion Capture during the VU-Return-to-Play- Field-Test

Richter

Daniels

King

et al. 2020

Sensors

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“…This allows three-dimensional (3D) assessment during both static positions and dynamic conditions, including daily life motor tasks ( Schmid et al, 2016 ; Diebo et al, 2018 ; Severijns et al, 2020 , 2021 ). However, the validity and accuracy of such skin marker-based methods is highly dependent on correct marker placement, which is known to be one of the main sources of variability in kinematic results ( Della Croce et al, 2005 ; Gorton et al, 2009 ; McFadden et al, 2020 ). Nevertheless, information on spinal marker placement accuracy (i.e., palpation error) and its possible effect on spinal alignment measurements, in both healthy and deformed spines, is scarce.…”

Section: Introductionmentioning

confidence: 99%

Spinal Palpation Error and Its Impact on Skin Marker-Based Spinal Alignment Measurement in Adult Spinal Deformity

Severijns

Overbergh

Schmid

et al. 2021

Front. Bioeng. Biotechnol.

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Spinal alignment measurement in spinal deformity research has recently shifted from using mainly two-dimensional static radiography toward skin marker-based motion capture approaches, allowing three-dimensional (3D) assessments during dynamic conditions. The validity and accuracy of such skin marker-based methods is highly depending on correct marker placement. In this study we quantified, for the first time, the 3D spinal palpation error in adult spinal deformity (ASD) and compared it to the error in healthy spines. Secondly, the impact of incorrect marker placement on the accuracy of marker-based spinal alignment measurement was investigated. 3D, mediolateral and inferosuperior palpation errors for thoracolumbar and lumbar vertebral levels were measured on biplanar images by extracting 3D positions of skin-mounted markers and their corresponding anatomical landmarks in 20 ASD and 10 healthy control subjects. Relationships were investigated between palpation error and radiographic spinal alignment (lordosis and scoliosis), as well as body morphology [BMI and soft tissue (ST) thickness]. Marker-based spinal alignment was measured using a previously validated method, in which a polynomial is fit through the marker positions of a motion trial and which allows for radiograph-based marker position correction. To assess the impact of palpation error on spinal alignment measurement, the agreement was investigated between lordosis and scoliosis measured by a polynomial fit through, respectively, (1) the uncorrected marker positions, (2) the palpation error-corrected (optimal) marker positions, and (3) the anatomically corrected marker positions (toward the vertebral body), and their radiographic equivalents expressed as Cobb angles (ground truth), using Spearman correlations and root mean square errors (RMSE). The results of this study showed that, although overall accuracy of spinal level identification was similar across groups, mediolateral palpation was less accurate in the ASD group (ASDmean: 6.8 mm; Controlmean: 2.5 mm; p = 0.002). Significant correlations with palpation error indicated that determining factors for marker misplacement were spinal malalignment, in particular scoliotic deformity (r = 0.77; p < 0.001), in the ASD group and body morphology [i.e., increased BMI (rs = 0.78; p = 0.008) and ST thickness (rs = 0.66; p = 0.038)] in healthy spines. Improved spinal alignment measurements after palpation error correction, shows the need for radiograph-based marker correction methods, and therefore, should be considered when interpreting spinal kinematics.

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“…However, despite reported sub-millimetre accuracy, marker-based motion capture systems are subject to the limitation of soft tissue artefact and muscle contraction that affect the resultant knee kinematics (Fiorentino et al, 2017;Schulz & Kimmel, 2010). Soft tissue artefact (STA), being site, participant and movement task-specific, will impact upon the selection of marker locations and the subsequent biomechanical model utilised (Benoit et al, 2006;Cockcroft et al, 2016;McFadden et al, 2020;Schulz & Kimmel, 2010). The use of bone pins or advanced imaging validation methods to optimise kinematic data (Fiorentino et al, 2017;Mentiplay & Clark, 2018;Potvin et al, 2017) is impractical in sports settings.…”

Section: Introductionmentioning

confidence: 99%

Marker location and knee joint constraint affect the reporting of overhead squat kinematics in elite youth football players

Coyne

Newell

Hoozemans

et al. 2021

Sports Biomechanics

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Motion capture systems are used in the analysis and interpretation of athlete movement patterns for a variety of reasons, but data integrity remains critical regardless. The extent to which marker location or constraining degrees of freedom (DOF) in the biomechanical model impacts on this integrity lacks consensus. Ten elite academy footballers performed bilateral overhead squats using a marker-based motion capture system. Kinematic data were calculated using four different marker sets with 3DOF and 6DOF configurations for the three joint rotations of the right knee. Root mean squared error differences between marker sets ranged in the sagittal plane between 1.02 and 4.19 degrees to larger values in the frontal (1.30-6.39 degrees) and transverse planes (1.33 and 7.97 degrees). The cross-correlation function of the knee kinematic time series for all eight marker-sets ranged from excellent for sagittal plane motion (>0.99) but reduced for both coronal and transverse planes (<0.9). Two-way ANOVA repeated measures calculated at peak knee flexion revealed significant differences between marker sets for frontal and transverse planes (p < 0.05). Pairwise comparisons showed significant differences between some marker sets. Marker location and constraining DOF while measuring relatively large ranges of motion in this population are important considerations for data integrity.

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The sensitivity of joint kinematics and kinetics to marker placement during a change of direction task

Cited by 27 publications

References 44 publications

Agreement between Inertia and Optical Based Motion Capture during the VU-Return-to-Play- Field-Test

Agreement between Inertia and Optical Based Motion Capture during the VU-Return-to-Play- Field-Test

Spinal Palpation Error and Its Impact on Skin Marker-Based Spinal Alignment Measurement in Adult Spinal Deformity

Marker location and knee joint constraint affect the reporting of overhead squat kinematics in elite youth football players

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