Diabetic foot ulcers are one of the most serious complications associated with diabetes mellitus. Current research studies have demonstrated that biomechanical alterations of the diabetic foot contribute to the development of foot ulcers. However, the changes of soft tissue biomechanical properties associated with diabetes and its influences on the development of diabetic foot ulcers have not been investigated. The purpose of this study was to investigate the effect of diabetes on the biomechanical properties of plantar soft tissues and the relationship between biomechanical properties and plantar pressure distributions. We used the ultrasound indentation tests to measure force-deformation relationships of plantar soft tissues and calculate the effective Young's modulus and quasi-linear viscoelastic parameters to quantify biomechanical properties of plantar soft tissues. We also measured plantar pressures to calculate peak plantar pressure and plantar pressure gradient. Our results showed that diabetics had a significantly greater effective Young's modulus and initial modulus of quasi-linear viscoelasticity compared to non-diabetics. The plantar pressure gradient and biomechanical properties were significantly correlated. Our findings indicate that diabetes is linked to an increase in viscoelasticity of plantar soft tissues that may contribute to a higher peak plantar pressure and plantar pressure gradient in the diabetic foot.

Diabetic foot ulcers remain one of the most serious complications of diabetes. Peak plantar pressure (PPP) and peak pressure gradient (PPG) during walking have been shown to be associated with the development of diabetic foot ulcers. To gain further insight into the mechanical etiology of diabetic foot ulcers, examination of the pressure gradient angle (PGA) has been recently proposed. The PGA quantifies directional variation or orientation of the pressure gradient during walking and provides a measure of whether pressure gradient patterns are concentrated or dispersed along the plantar surface. We hypothesized that diabetics at risk of foot ulceration would have smaller PGA in key plantar regions, suggesting less movement of the pressure gradient over time. A total of 27 participants were studied, including 19 diabetics with peripheral neuropathy and 8 non-diabetic control subjects. A foot pressure measurement system was used to measure plantar pressures during walking. PPP, PPG, and PGA were calculated for four foot regions – first toe (T1), first metatarsal head (M1), second metatarsal head (M2), and heel (HL). Consistent with prior studies, PPP and PPG were significantly larger in the diabetic group compared with non-diabetic controls in the T1 and M1 regions, but not M2 or HL. For example, PPP was 165% (P = 0.02) and PPG was 214% (P < 0.001) larger in T1. PGA was found to be significantly smaller in the diabetic group in T1 (46%, P = 0.04), suggesting a more concentrated pressure gradient pattern under the toe. The proposed PGA may improve our understanding of the role of pressure gradient on the risk of diabetic foot ulcers.

Background: Lumbar disc herniation (LDH) is among the most common causes of lower back pain and sciatica. The causes of LDH have not been fully elucidated but most likely involve a complex combination of mechanical and biological processes. Magnetic resonance imaging (MRI) is a tool most frequently used for LDH because it can show abnormal soft tissue areas around the spine. Deep learning models may be trained to recognize images with high speed and accuracy to diagnose LDH. Although the deep learning model requires huge numbers of image datasets to train and establish the best model, this study processed enhanced medical image features for training the small-scale deep learning dataset.Methods: We propose automatic detection to assist the initial LDH exam for lower back pain. The subjects were between 20 and 65 years old with at least 6 months of work experience. The deep learning method employed the YOLOv3 model to train and detect small object changes such as LDH on MRI. The dataset images were processed and combined with labeling and annotation from the radiologist’s diagnosis record.Results: Our method proves the possibility of using deep learning with a small-scale dataset with limited medical images. The highest mean average precision (mAP) was 92.4% at 550 images with data augmentation (550-aug), and the YOLOv3 LDH training was 100% with the best average precision at 550-aug among all datasets. This study used data augmentation to prevent under- or overfitting in an object detection model that was trained with the small-scale dataset.Conclusions: The data augmentation technique plays a crucial role in YOLOv3 training and detection results. This method displays a high possibility for rapid initial tests and auto-detection for a limited clinical dataset.

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Exercise has been demonstrated to improve health in people with diabetes. However, exercise may increase risk for foot ulcers because of increased plantar pressure during most weight-bearing physical activities. To date, there is no study investigating the effect of various walking speeds and durations (i.e., the most common form of exercise in daily living) on the plantar foot. The objective of this study was to investigate the effect of various walking intensities on plantar tissue stiffness. A 3 × 2 factorial design, including three walking speeds (1.8, 3.6 and 5.4 mph) and two durations (10 and 20 min), was tested in 12 healthy participants. B-mode and elastographic ultrasound images were measured from the first metatarsal head to quantify plantar tissue stiffness after walking. Two-way ANOVA was used to examine the results. Our results showed that the walking speed factor caused a significant main effect of planar stiffness of the superficial layers (p = 0.007 and 0.003, respectively). However, the walking duration factor did not significantly affect the plantar stiffness. There was no interaction between the speed and duration factors on plantar tissue stiffness. Regarding the walking speed effect, there was a significant difference in the plantar stiffness between 1.8 and 3.6 mph (56.8 ± 0.8% vs. 53.6 ± 0.9%, p = 0.017) under 20 min walking duration. This finding is significant because moderate-to-fast walking speed (3.6 mph) can decrease plantar stiffness compared to slow walking speed (1.8 mph). This study suggests people at risk for foot ulcers walk at a preferred or fast speed (3.6 mph) rather than walk slowly (1.8 mph).

Background Walking exercise has been demonstrated to improve health in people with diabetes. However, it is largely unknown the influences of various walking intensities such as walking speeds and durations on dynamic plantar pressure distributions in non-diabetics and diabetics. Traditional methods ignoring time-series changes of plantar pressure patterns may not fully capture the effect of walking intensities on plantar tissues. The purpose of this study was to investigate the effect of various walking intensities on the dynamic plantar pressure distributions. In this study, we introduced the peak pressure gradient (PPG) and its dynamic patterns defined as the pressure gradient angle (PGA) to quantify dynamic changes of plantar pressure distributions during walking at various intensities. Methods Twelve healthy participants (5 males and 7 females) were recruited in this study. The demographic data were: age, 27.1 ± 5.8 years; height, 1.7 ± 0.1 m; and weight, 63.5 ± 13.5 kg (mean ± standard deviation). An insole plantar pressure measurement system was used to measure plantar pressures during walking at three walking speeds (slow walking 1.8 mph, brisk walking 3.6 mph, and slow running 5.4 mph) for two durations (10 and 20 min). The gradient at a location is defined as the unique vector field in the two-dimensional Cartesian coordinate system with a Euclidean metric. PGA was calculated by quantifying the directional variation of the instantaneous peak gradient vector during stance phase of walking. PPG and PGA were calculated in the plantar regions of the first toe, first metatarsal head, second metatarsal head, and heel at higher risk for foot ulcers. Two-way ANOVA with Fisher’s post-hoc analysis was used to examine the speed and duration factors on PPG and PGA. Results The results showed that the walking speeds significantly affect PPG (P < 0.05) and PGA (P < 0.05), and the walking durations does not. No interaction between the walking duration and speed was observed. PPG in the first toe region after 5.4 mph for either 10 or 20 min was significantly higher than 1.8 mph. Meanwhile, after 3.6 mph for 20 min, PPG in the heel region was significantly higher than 1.8 mph. Results also indicate that PGA in the forefoot region after 3.6 mph for 20 min was significantly narrower than 1.8 mph. Conclusions Our findings indicate that people may walk at a slow speed at 1.8 mph for reducing PPG and preventing PGA concentrated over a small area compared to brisk walking at 3.6 mph and slow running at 5.4 mph.

Ischial pressures seemed to be redistributed to the coccyx in response to the four smallest angle combinations and redistributed to the back support in response to the two largest angle combinations. Future work should confirm this pressure redistribution to the back support and determine the back support locations of redistribution.

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