Dynamic 3D scanning as a markerless method to calculate multi-segment foot kinematics during stance phase: Methodology and first application

Herrewegen, Inge Van den; Cuppens, Kris; Broeckx, Mario; Barisch‐Fritz, Bettina; Sloten, Jos Vander; Leardini, Alberto; Peeraer, Louis

doi:10.1016/j.jbiomech.2014.06.010

Cited by 21 publications

(6 citation statements)

References 22 publications

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“…Previous attempts at markerless foot tracking involved scanning and fitting a visual hull to the foot model during walking. However, this approach was not successful in capturing the full gait cycle, particularly push-off and heel contact, which were challenging to accurately capture [61].…”

Section: Challenges and Future Directionsmentioning

confidence: 99%

Dynamic Gait Analysis in Paediatric Flatfeet: Unveiling Biomechanical Insights for Diagnosis and Treatment

Böhm,

Stebbins,

Kothari

et al. 2024

Children

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Background: Flatfeet in children are common, causing concern for parents due to potential symptoms. Technological advances, like 3D foot kinematic analysis, have revolutionized assessment. This review examined 3D assessments in paediatric idiopathic flexible flat feet (FFF). Methods: Searches focused on paediatric idiopathic FFF in PubMed, Web of Science, and SCOPUS. Inclusion criteria required 3D kinematic and/or kinetic analysis during posture or locomotion, excluding non-idiopathic cases, adult feet, and studies solely on pedobarography or radiographs. Results: Twenty-four studies met the criteria. Kinematic and kinetic differences between FFF and typical feet during gait were outlined, with frontal plane deviations like hindfoot eversion and forefoot supination, alongside decreased second peak vertical GRF. Dynamic foot classification surpassed static assessments, revealing varied movement patterns within FFF. Associations between gait characteristics and clinical measures like pain symptoms and quality of life were explored. Interventions varied, with orthoses reducing ankle eversion and knee and hip abductor moments during gait, while arthroereisis normalized calcaneal alignment and hindfoot eversion. Conclusions: This review synthesises research on 3D kinematics and kinetics in paediatric idiopathic FFF, offering insights for intervention strategies and further research.

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Section: Challenges and Future Directionsmentioning

confidence: 99%

Dynamic Gait Analysis in Paediatric Flatfeet: Unveiling Biomechanical Insights for Diagnosis and Treatment

Böhm,

Stebbins,

Kothari

et al. 2024

Children

View full text Add to dashboard Cite

show abstract

“…4D scanning systems have been used in ergonomic and anthropometry research to investigate shape changes and deformation patterns during various activities. While the foot [ 19 , 20 , 25 , 26 ] and face [ 21 ] have received more attention, there is a growing interest in applying 4D scanning technology to analyze body and breast dynamics [ 22 – 24 ]. Although only a limited number of studies have explored this area, it has been recognized as having great potential for ergonomics studies and sportswear design [ 18 ].…”

Section: Related Workmentioning

confidence: 99%

Ultra-dense Motion Capture: An exploratory full-automatic approach for dense tracking of breast motion in 4D

Liu,

Yick,

Sun

et al. 2024

PLoS ONE

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Understanding the dynamic deformation pattern and biomechanical properties of breasts is crucial in various fields, including designing ergonomic bras and customized prostheses, as well as in clinical practice. Previous studies have recorded and analyzed the dynamic behaviors of the breast surface using 4D scanning, which provides a sequence of 3D meshes during movement with high spatial and temporal resolutions. However, these studies are limited by the lack of robust and automated data processing methods which result in limited data coverage or error-prone analysis results. To address this issue, we identify revealing inter-frame dense correspondence as the core challenge towards conducting reliable and consistent analysis of the 4D scanning data. We proposed a fully-automatic approach named Ulta-dense Motion Capture (UdMC) using Thin-plate Spline (TPS) to augment the sparse landmarks recorded via motion capture (MoCap) as initial dense correspondence and then rectified it with a sophisticated post-alignment scheme. Two downstream tasks are demonstrated to validate its applicability: virtual landmark tracking and deformation intensity analysis. For evaluation, a dynamic 4D human breast anthropometric dataset DynaBreastLite was constructed. The results show that our approach can robustly capture the dynamic deformation characteristics of the breast surfaces, significantly outperforms baselines adapted from previous works in terms of accuracy, consistency, and efficiency. For 10 fps dataset, average error of 0.25 cm on control-landmarks and 0.33 cm on non-control (arbitrary) landmarks were achieved, with 17-70 times faster computation time. Evaluation was also carried out on 60 fps and 120 fps datasets, with consistent and large performance gaining being observed. The proposed method may contribute to advancing research in breast anthropometry, biomechanics, and ergonomics by enabling more accurate tracking of the breast surface deformation patterns and dynamic characteristics.

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“…Anatomical landmarks can be reliably approximated from the registered scans (Van den Herrewegen et al, 2014). The first metatarsal head, fifth metatarsal head, and second toe landmarks were used to align all scans to be centered at the second metatarsal head, with the forward axis pointing towards the second toe.…”

Section: Data Processingmentioning

confidence: 99%

Dynamic foot morphology explained through 4D scanning and shape modeling

Boppana¹,

Anderson²

2020

Preprint

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A detailed understanding of foot morphology can enable the design of more comfortable and better fitting footwear. However, foot morphology varies widely within the population, and changes dynamically during the loading of stance phase. This study presents a parametric statistical shape model from 4D foot scans to capture both the inter-and intra-individual variability in foot morphology. Thirty subjects walked on a treadmill while 4D scans of their right foot were taken at 90 frames-per-second during stance phase. Each subject's height, weight, foot length, foot width, arch length, and sex were also recorded. The 4D scans were all registered to a common high-quality foot scan, and a principal component analysis was done on all processed 4D scans. Elastic-net linear regression models were built to predict the principal component scores, which were then inverse transformed into 4D scans. The best performing model was selected with leave-one-out cross-validation. The chosen model was predicts foot morphology across stance phase with a root-mean squared error of 5.2 ± 2.0 mm. This study shows that statistical shape modeling can be used to predict dynamic changes in foot morphology across the population. The model can be used to investigate and improve foot-footwear interaction, allowing for better fitting and more comfortable footwear.

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Dynamic 3D scanning as a markerless method to calculate multi-segment foot kinematics during stance phase: Methodology and first application

Cited by 21 publications

References 22 publications

Dynamic Gait Analysis in Paediatric Flatfeet: Unveiling Biomechanical Insights for Diagnosis and Treatment

Dynamic Gait Analysis in Paediatric Flatfeet: Unveiling Biomechanical Insights for Diagnosis and Treatment

Ultra-dense Motion Capture: An exploratory full-automatic approach for dense tracking of breast motion in 4D

Dynamic foot morphology explained through 4D scanning and shape modeling

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