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This study aimed to explore the potential of predicting diabetes by analyzing trends in plantar thermal and plantar pressure data, either individually or in combination, using various machine learning techniques. A total of twenty-six participants, comprising thirteen individuals diagnosed with diabetes and thirteen healthy individuals, walked along a 20 m path. In-shoe plantar pressure data were collected and the plantar temperature was measured both immediately before and after the walk. Each participant completed the trial three times, and the average data between the trials were calculated. The research was divided into three experiments: the first evaluated the correlations between the plantar pressure and temperature data; the second focused on predicting diabetes using each data type independently; and the third combined both data types and assessed the effect of such to enhance the predictive accuracy. For the experiments, 20 regression models and 16 classification algorithms were employed, and the performance was evaluated using a five-fold cross-validation strategy. The outcomes of the initial set of experiments indicated that the machine learning models were significant correlations between the thermal data and pressure estimates. This was consistent with the findings from the prior correlation analysis, which showed weak relationships between these two data modalities. However, a shift in focus towards predicting diabetes by aggregating the temperature and pressure data led to encouraging results, demonstrating the effectiveness of this approach in accurately predicting the presence of diabetes. The analysis revealed that, while several classifiers demonstrated reasonable metrics when using standalone variables, the integration of thermal and pressure data significantly improved the predictive accuracy. Specifically, when only plantar pressure data were used, the Logistic Regression model achieved the highest accuracy at 68.75%. Those predictions based solely on temperature data showed the Naive Bayes model as the lead with an accuracy of 87.5%. Notably, the highest accuracy of 93.75% was observed when both the temperature and pressure data were combined, with the Extra Trees Classifier performing the best. These results suggest that combining temperature and pressure data enhances the model's predictive accuracy. This can indicate the importance of multimodal data integration and their potentials in diabetes prediction. [ABSTRACT FROM AUTHOR]

An increase in plantar pressure and skin temperature is commonly associated with an increased risk of diabetic foot ulcers. However, the effect of insoles in reducing plantar temperature has not been commonly studied. The aim was to assess the effect of walking in insoles with different features on plantar temperature. Twenty-six (F/M:18/8) participants—13 with diabetes and 13 healthy, aged 55.67 ± 9.58 years—participated in this study. Skin temperature at seven plantar regions was measured using a thermal camera and reported as the difference between the temperature after walking with an insole for 20 m versus the baseline temperature. The mixed analyses of variance indicated substantial main effects for the Insole Condition, for both the right [Wilks' Lambda = 0.790, F(14, 492) = 4.393, p < 0.01, partial eta squared = 0.111] and left feet [Wilks' Lambda = 0.890, F(14, 492) = 2.103, p < 0.011, partial eta squared = 0.056]. The 2.5 mm-tall dimple insole was shown to be significantly more effective at reducing the temperature in the hallux and third met head regions compared to the 4 mm-tall dimple insole. The insoles showed to be significantly more effective in the diabetes group versus the healthy group, with large effect size for the right [Wilks' Lambda = 0.662, F(14, 492) = 8.037, p < 0.000, Partial eta-squared = 0.186] and left feet [Wilks' Lambda = 0.739, F(14, 492) = 5.727, p < 0.000, Partial eta-squared = 0.140]. This can have important practical implications for designing insoles with a view to decrease foot complications in people with diabetes. [ABSTRACT FROM AUTHOR]

Aim: To validate the paper grip test for assessing plantar flexion strength of the hallux.Methods: Plantar flexor strength for 69 people with diabetic neuropathy was assessed: (a) using the paper grip test while simultaneously a plantar pressure platform quantified the force under the hallux, and (b) using a hand-held dynamometer. Following testing, participants were divided into groups: (1) passed vs. failed paper grip test (2) males vs. females. Statistical analyses determined if differences were evident between the groups and assessed the relationship between the paper grip test and the hand-held dynamometer. The discrimination ability, sensitivity, specificity, and reproducibility of the paper grip test was established.Results: Participants who passed the paper grip test demonstrated greater grip force at the hallux than those who failed, and they also exhibited greater isometric maximum force during the hand-held dynamometry test (p ≤ 0.05). Grip force for males was significantly higher than for females. A moderate positive correlation between the paper grip test and the hand-held dynamometer was evident.Conclusions: In the population examined the paper grip test was found to be a valid clinical tool; it offers a non-invasive, inexpensive, and quick method to assess plantar flexion strength of the hallux. [ABSTRACT FROM AUTHOR]

Introduction Pathological conditions such as diabetic foot and plantar heel pain are associated with changes in the mechanical properties of plantar soft tissue. However, the causes and implications of these changes are not yet fully understood. This is mainly because accurate assessment of the mechanical properties of plantar soft tissue in the clinic remains extremely challenging. Purpose To develop a clinically viable non-invasive method of assessing the mechanical properties of the heel pad. Furthermore the effect of non-linear mechanical behaviour of the heel pad on its ability to uniformly distribute foot-ground contact loads in light of the effect of overloading is also investigated. Methods An automated custom device for ultrasound indentation was developed along with custom algorithms for the automated subject-specific modeling of heel pad. Non-time-dependent and time-dependent material properties were inverse engineered from results from quasi-static indentation and stress relaxation test respectively. The validity of the calculated coefficients was assessed for five healthy participants. The implications of altered mechanical properties on the heel pad's ability to uniformly distribute plantar loading were also investigated in a parametric analysis. Results The subject-specific heel pad models with coefficients calculated based on quasi-static indentation and stress relaxation were able to accurately simulate dynamic indentation. Average error in the predicted forces for maximum deformation was only 6.6±4.0%. When the inverse engineered coefficients were used to simulate the first instance of heel strike the error in terms of peak plantar pressure was 27%. The parametric analysis indicated that the heel pad's ability to uniformly distribute plantar loads is influenced both by its overall deformability and by its stress-strain behaviour. When overall deformability stays constant, changes in stress/strain behaviour leading to a more “linear” mechanical behaviour appear to improve the heel pad's ability to uniformly distribute plantar loading. Conclusions The developed technique can accurately assess the visco-hyperelastic behaviour of heel pad. It was observed that specific change in stress-strain behaviour can enhance/weaken the heel pad's ability to uniformly distribute plantar loading that will increase/decrease the risk for overloading and trauma. [ABSTRACT FROM AUTHOR]

This study aims to develop a numerical method that can be used to investigate the cushioning properties of different insole materials on a subject-specific basis. Diabetic footwear and orthotic insoles play an important role for the reduction of plantar pressure in people with diabetes (type-2). Despite that, little information exists about their optimum cushioning properties. A new in-vivo measurement based computational procedure was developed which entails the generation of 2D subject-specific finite element models of the heel pad based on ultrasound indentation. These models are used to inverse engineer the material properties of the heel pad and simulate the contact between plantar soft tissue and a flat insole. After its validation this modelling procedure was utilised to investigate the importance of plantar soft tissue stiffness, thickness and loading for the correct selection of insole material. The results indicated that heel pad stiffness and thickness influence plantar pressure but not the optimum insole properties. On the other hand loading appears to significantly influence the optimum insole material properties. These results indicate that parameters that affect the loading of the plantar soft tissues such as body mass or a person's level of physical activity should be carefully considered during insole material selection. [ABSTRACT FROM AUTHOR]

Plantar pressure assessment is commonly used as a tool to assess the efficacy of insoles in reducing the risk of mechanical trauma to the plantar soft tissue during walking gait. The slow rebound (SR) Poron insole is intended to provide a custom fit to the foot and is believed to be superior in increasing the contact area and consequently reducing the contact pressure compared to a normal Poron (NP) insole. The aim of this study was to compare the effectiveness of SR or NP versus an ethylene vinyl acetate (EV) insole in increasing the contact area (CA), and in reducing the contact pressure (CP) at different regions of the foot during walking. Plantar pressure data was collected from nine healthy individuals during walking using commercially available in-shoe plantar pressure sensors. Although, the NP insole significantly increased the CA and decreased the CP on the entire foot compared to the EV, there was no significant change in CP or CA at any region of the foot in any of the tested insoles. CP showed a positive significant correlation with CA at heel, hallux and heel center in all three insoles. The expected significant negative correlation between regional CA and CP was not observed. [ABSTRACT FROM AUTHOR]

The purpose of this study is to demonstrate a new MRI compatible loading device capable of reconstructing realistic loading scenarios of the human foot for research in the field of foot biomechanics. This device has two different configurations: one used to compress the forefoot and one to bend the metatarsophalangeal joints. Required plantar pressure distribution under the metatarsal heads can be achieved by modifying the distribution of the dorsally applied forces. To validate the device, subject-specific plantar pressures were measured and then reconstructed using the device. For quiet stance the peak pressure reconstruction error was 3% while for mid-stance phase of gait it was 8%. The device was also used to measure the passive bending stiffness of the metatarsophalangeal joints of one subject with low intra-subject variability. A series of preliminary MRI scans confirmed that the loading device can be used to produce static weight-bearing images of the foot (voxel size: 0.23mm×0.23mm×1.00mm).The results indicate that the device presented here can accurately reconstruct subject specific plantar pressure distributions and measure the foot's metatarsophalangeal passive stiffness. Possible future applications include the validation of finite element models, the investigation of the relationship between plantar pressure and internal stresses/strains and the study of the foot's inter-segmental passive stiffness. [ABSTRACT FROM AUTHOR]

Aim: Footwear interventions are used within clinical practice in an effort to reduce ulcerations however the effectiveness of these interventions is unclear. The aim of this paper was to conduct a systematic review which examined the effectiveness of footwear as an intervention for prevention of diabetic foot ulcers or the reduction of biomechanical risk factors for ulceration and to discuss the quality and interpret the findings of research to date. Methods: The CINAHL, Medline and Cochrane Register of Controlled Trials databases were searched with 12 articles identified for review. Results: The majority of these studies were cross sectional and examined the effect of different footwear conditions on plantar pressure measurements. Factors which influenced study findings such as participant selection, measurement and analysis techniques, footwear design and compliance are discussed and recommendations for future studies are provided. Conclusions: No research to date has examined the effectiveness of footwear in preventing ulceration. Conflicting findings are reported on the effective of footwear interventions to prevent reulceration. While the use of rocker sole footwear and custom orthoses in plantar pressure reduction are supported in cross sectional studies, longitudinal studies are required to confirm their benefit. [ABSTRACT FROM AUTHOR]

Abstract: Background: Plantar pressure assessment is routinely used in a clinical setting for diagnosing foot problems and prescribing orthoses or footwear. Despite this, the measurement procedures and protocols that might have an effect on the results are not standardised. Objective: The purpose of this study was to evaluate, if variations in the data collection protocol such as the use of a walkway and stepping preference influence the measured plantar pressure parameters. Method: 21 participants who were recruited from a convenience sample and consented to participate were tested under a number of different conditions through which the effect of these variations was tested. A paired T-test was used to determine whether a significant difference in the data corresponding to each subject for different testing conditions existed. Results: Although there were significant differences between the plantar pressure measurement with the choice of the foot, there were no significant difference in the majority of plantar pressure parameters whilst using or not using the walkway. Conclusion: The results suggest that in a clinical and research setting extrinsic factors such as stepping preference needs to be considered to eliminate the effect of variability in plantar pressure data. [Copyright &y& Elsevier]