Subject-specific identification of three dimensional foot shape deviations using statistical shape analysis

Stanković, Kristina; Huysmans, Toon; Danckaers, Femke; Sijbers, Jan; Booth, Brian G.

doi:10.1016/j.eswa.2020.113372

Cited by 11 publications

(12 citation statements)

References 74 publications

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“…Stanković et al . were able to use heatmaps overlayed onto 3D scans of participant's feet to identify foot deformities 20 . In orthopaedics, heatmaps were used to visualise the differences between the shape of a bone defect and the normal anatomy, such as in scapulae, femorae and tibiae 21 , 22 .…”

Section: Discussionmentioning

confidence: 99%

Digital mapping of a manual fabrication method for paediatric ankle–foot orthoses

Wang

Lillia

Farhan

et al. 2021

Sci Rep

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Ankle–foot orthoses (AFOs) are devices prescribed to improve mobility in people with neuromuscular disorders. Traditionally, AFOs are manually fabricated by an orthotist based on a plaster impression of the lower leg which is modified to correct for impairments. This study aimed to digitally analyse this manual modification process, an important first step in understanding the craftsmanship of AFO fabrication to inform the digital workflows (i.e. 3D scanning and 3D printing), as viable alternatives for AFO fabrication. Pre- and post-modified lower limb plaster casts of 50 children aged 1–18 years from a single orthotist were 3D scanned and registered. The Euclidean distance between the pre- and post-modified plaster casts was calculated, and relationships with participant characteristics (age, height, AFO type, and diagnosis) were analysed. Modification maps demonstrated that participant-specific modifications were combined with universally applied modifications on the cast's anterior and plantar surfaces. Positive differences (additions) ranged 2.12–3.81 mm, negative differences (subtractions) ranged 0.76–3.60 mm, with mean differences ranging from 1.37 to 3.12 mm. Height had a medium effect on plaster additions (rs = 0.35). We quantified the manual plaster modification process and demonstrated a reliable method to map and compare pre- and post-modified casts used to fabricate children's AFOs.

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Section: Discussionmentioning

confidence: 99%

Digital mapping of a manual fabrication method for paediatric ankle–foot orthoses

Wang

Lillia

Farhan

et al. 2021

Sci Rep

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show abstract

“…Grant et al's model reconstructed internal foot bones with much lower RMSEs from sparse anatomical landmarks (1.21-1.66 mm for various foot segments) (Grant et al, 2020) but was trained with higher resolution MRI images. Other efforts to create statistical foot shape models did not incorporate parametric prediction of foot shape (Conrad et al, 2019;Stanković et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…Principal component (PC) analysis is a dimensionality-reduction method commonly in constructing SSMs (Reed and Parkinson, 2008;Conrad et al, 2019;Stanković et al, 2020). The first PC represents an axis containing the largest variance in the dataset, and each subsequent PC describes the largest variance orthogonal to the previous component's axis.…”

Section: Model Constructionmentioning

confidence: 99%

“…SSMs have recently been applied to characterize static foot shape across a population (Conrad et al, 2019) and recognize foot-shape deviations (Stanković et al, 2020). The aforementioned efforts to capture foot measurement changes over the gait cycle did capture 4D foot images (Barisch-Fritz et al, 2014a;Grau and Barisch-Fritz, 2018), but these efforts were not translated into a SSM.…”

Section: Introductionmentioning

confidence: 99%

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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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“…Gender was linked to ankle width, Achilles tendon size, and heel width. Classifying problematic feet using surface morphology has been reported which included hallux valgus, pes planus, and pes cavus profiles ( Stanković et al, 2020 ).…”

Section: Population-based Modeling Of Shapesmentioning

confidence: 99%

Toward improved understanding of foot shape, foot posture, and foot biomechanics during running: A narrative review

Mei

Kim²,

Xiang³

et al. 2022

Front. Physiol.

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The current narrative review has explored known associations between foot shape, foot posture, and foot conditions during running. The artificial intelligence was found to be a useful metric of foot posture but was less useful in developing and obese individuals. Care should be taken when using the foot posture index to associate pronation with injury risk, and the Achilles tendon and longitudinal arch angles are required to elucidate the risk. The statistical shape modeling (SSM) may derive learnt information from population-based inference and fill in missing data from personalized information. Bone shapes and tissue morphology have been associated with pathology, gender, age, and height and may develop rapid population-specific foot classifiers. Based on this review, future studies are suggested for 1) tracking the internal multi-segmental foot motion and mapping the biplanar 2D motion to 3D shape motion using the SSM; 2) implementing multivariate machine learning or convolutional neural network to address nonlinear correlations in foot mechanics with shape or posture; 3) standardizing wearable data for rapid prediction of instant mechanics, load accumulation, injury risks and adaptation in foot tissue and bones, and correlation with shapes; 4) analyzing dynamic shape and posture via marker-less and real-time techniques under real-life scenarios for precise evaluation of clinical foot conditions and performance-fit footwear development.

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Subject-specific identification of three dimensional foot shape deviations using statistical shape analysis

Cited by 11 publications

References 74 publications

Digital mapping of a manual fabrication method for paediatric ankle–foot orthoses

Digital mapping of a manual fabrication method for paediatric ankle–foot orthoses

Dynamic foot morphology explained through 4D scanning and shape modeling

Toward improved understanding of foot shape, foot posture, and foot biomechanics during running: A narrative review

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