Standardization of Foot Sizes of Patients with Diabetic Foot Ulcer through Anthropometric Survey

Priyadharshini, R.; Saraswathy, G.; Gopalakrishna, Gautham; Das, B.; Viswanathan, Vijay

doi:10.1080/09720073.2017.1335718

Cited by 4 publications

(26 citation statements)

References 11 publications

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“…A wide range of foot measures to quantify foot shape were reported within the included studies (see Fig. [5,30,32,37,41,44,48,55,67,76,82,87], eight studies measured ankle girth [30,32,42,48,49,73,79,87], six studies measured heel angle (frontal plane) [69,71,73,76,91,94], six studies measured ball angle [32,74,75,79,83,84], five studies measured long heel girth [30,34,48,67,86], three studies measured flare angle [11,58,85], and two studies measured toe length [50,84]. Figure 3 shows the most commonly reported foot dimensions.…”

Section: Foot Dimensions Measuredmentioning

confidence: 99%

Methodological and statistical approaches for the assessment of foot shape using three‐dimensional foot scanning: a scoping review

Allan

Munteanu

Bonanno

et al. 2023

Journal of Foot and Ankle Research

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Objective The objectives of this study were to: (i) review and provide a narrative synthesis of three-dimensional (3D) foot surface scanning methodological and statistical analysis protocols, and (ii) develop a set of recommendations for standardising the reporting of 3D foot scanning approaches. Methods A systematic search of the SCOPUS, ProQuest, and Web of Science databases were conducted to identify papers reporting 3D foot scanning protocols and analysis techniques. To be included, studies were required to be published in English, have more than ten participants, and involve the use of static 3D surface scans of the foot. Papers were excluded if they reported two-dimensional footprints only, 3D scans that did not include the medial arch, dynamic scans, or derived foot data from a full body scan. Results The search yielded 78 relevant studies from 17 different countries. The available evidence showed a large variation in scanning protocols. The subcategories displaying the most variation included scanner specifications (model, type, accuracy, resolution, capture duration), scanning conditions (markers, weightbearing, number of scans), foot measurements and definitions used, and statistical analysis approaches. A 16-item checklist was developed to improve the consistency of reporting of future 3D scanning studies. Conclusion 3D foot scanning methodological and statistical analysis protocol consistency and reporting has been lacking in the literature to date. Improved reporting of the included subcategories could assist in data pooling and facilitate collaboration between researchers. As a result, larger sample sizes and diversification of population groups could be obtained to vastly improve the quantification of foot shape and inform the development of orthotic and footwear interventions and products.

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Section: Foot Dimensions Measuredmentioning

confidence: 99%

Methodological and statistical approaches for the assessment of foot shape using three‐dimensional foot scanning: a scoping review

Allan

Munteanu

Bonanno

et al. 2023

Journal of Foot and Ankle Research

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“…Dynamic foot pressure measurement is necessary particularly for diabetic patients to prevent ulcers which can eventually lead to gangrene and amputation (34) . Plantar pressure off-loading at the ulcer site is one of the therapeutic interventions for healing DFU (36) . Due to peripheral neuropathy and vascular disease, the foot anatomy of patients with diabetes is significantly different from that of normal persons.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Due to peripheral neuropathy and vascular disease, the foot anatomy of patients with diabetes is significantly different from that of normal persons. The work reported in Priyadharshini et al (2017) (36) derived standardized foot anthropometric data for patients with DFU to use as a reference for developing pressure off-loading devices. Rabbani et al (2013) (37) developed a low-cost optical sensing system for dynamic foot pressure measurement for diabetic patients to prevent ulcers.…”

Section: Literature Reviewmentioning

confidence: 99%

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Competitive neural layer-based method to identify people with high risk for diabetic foot

Ferreira

Oliveira

et al. 2020

Computers in Biology and Medicine

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Background and Objective: To automatically identify patients with diabetes mellitus (DM) who have high risk of developing diabetic foot, via an unsupervised machine learning technique. Methods: We collected a new database containing 54 known risk factors from 250 patients diagnosed with diabetes mellitus. The database also contained a separate validation cohort composed of 73 subjects, where the perceived risk was annotated by expert nurses. A competitive neuron layer-based method was used to automatically split training data into two risk groups. Results: We found that one of the groups was composed of patients with higher risk of developing diabetic foot. The dominant variables that described group membership via our method agreed with the findings from other studies, and indicated a greater risk for developing such a condition. Our method was validated on the available test data, reaching 71% sensitivity, 100% specificity, and 90% accuracy. Conclusions: Unsupervised learning may be deployed to screen patients with diabetes mellitus, pointing out high-risk individuals who require priority follow-up in the prevention of diabetic foot with very high accuracy. The proposed method is automatic and does not require clinical examinations to perform risk assessment, being solely based on the information of a questionnaire answered by patients. 2 Our study found that discriminant variables for predicting risk group membership are highly correlated with expert opinion.

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“…Due to peripheral neuropathy and vascular diseases, the structure of the foot of diabetic patients differs from that of those without diabetes [ 33 ]. Diabetic patients are prone to various foot deformations, affecting their foot anthropometric measurements and pressure parameters [ 34 ].…”

Section: Introductionmentioning

confidence: 99%

Foot deformation analysis with different load-bearing conditions to enhance diabetic footwear designs

Zhang

Yick

Li³

et al. 2022

PLoS ONE

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In-depth analyses of foot surface measurements upon weight bearing are crucial to understand how the dorsal and plantar surfaces of the foot deform during motion to enhance the fit of footwear, which is particularly important for diabetic patients with stringent fit requirements to redistribute the plantar weight forces. This study analyzes diabetic foot deformations under 3 different weight bearing conditions (no weight bearing, half weight bearing, and 80% weight bearing) by using a novel foot scanning method that enables efficient scanning of the dorsal and plantar surfaces of the foot simultaneously. The feet of 48 patients with diabetes mellitus (DM) are scanned. With increased load on the feet, the width of the forefoot increases by 9.7%-10.4%, height of the midfoot decreases by 15.1%-18.2%, forefoot and midfoot rotate to the medial side by 16.9%-23.9% while the rearfoot rotates to the lateral side by 15.2% simultaneously, and the plantar of the foot increases contact with the floor by 11.4%-23.0%. Gender differences in foot shape are also found between males and females, males have a broader foot than females for the same foot length. Precise anthropometric information of foot changes and deformation therefore enables adequate foot protection, fit and comfort when designing footwear. This research contributes to shoe design considerations that focus on the deformation of the foot under different loads.

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Standardization of Foot Sizes of Patients with Diabetic Foot Ulcer through Anthropometric Survey

Cited by 4 publications

References 11 publications

Methodological and statistical approaches for the assessment of foot shape using three‐dimensional foot scanning: a scoping review

Methodological and statistical approaches for the assessment of foot shape using three‐dimensional foot scanning: a scoping review

Competitive neural layer-based method to identify people with high risk for diabetic foot

Foot deformation analysis with different load-bearing conditions to enhance diabetic footwear designs

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