Wound assessment is essential for evaluating wound healing. One cornerstone of wound care practice is the use of clinical guidelines that mandate regular documentation, including wound size and wound tissue composition, to determine the rate of wound healing. The traditional method requires wound care professionals to manually measure the wound area and tissue composition, which is time-consuming, costly, and difficult to reproduce. In this work, we propose an approach for automatic wound assessment that incorporates automatic color and measurement calibration and artificial intelligence algorithms. Our approach enables the comparison of images taken at different times, even if they were taken under different lighting conditions, distances, lenses, and camera sensors. We designed a calibration chart and developed automatic algorithms for color and measurement calibration. The wound area and wound composition on the images were annotated by three physicians with more than ten years of experience. Deep learning models were then developed to mimic what the physicians did on the images. We examined two network variants, U-Net with EfficientNet and U-Net with MobileNetV2, on wound images with a size of 1024 × 1024 pixels. Our best-performing algorithm achieved a mean intersection over union (IoU) of 0.6964, 0.3957, 0.6421, and 0.1552 for segmenting a wound area, epithelialization area, granulation tissue, and necrotic tissue, respectively. Our approach was able to accurately segment the wound area and granulation tissue but was inconsistent with respect to the epithelialization area and necrotic tissue. The calibration chart, which helps calibrate colors and scales, improved the performance of the algorithm. The approach could provide a thorough assessment of the wound, which could help clinicians tailor treatment to the patient’s condition.

Offloading plantar pressure in a diabetic foot with neuropathy is challenging in conventional clinical practice. Custom-made insole (CMI) materials play an important role in plantar pressure reduction, but the assessment is costly and time-consuming. Finite element analysis (FEA) can provide an efficient evaluation of different insoles on the plantar pressure distribution. This study investigated the effect of CMI materials and their combinations on plantar pressure reduction for the diabetic foot with neuropathy using FEA. The study was conducted by constructing a three-dimensional foot model along with CMI to study the peak contact pressure between the foot and CMI. The softer material (E = 5 MPa) resulted in a better reduction of peak contact pressure compared with the stiffer material (E = 11 MPa). The plantar pressure was well redistributed with softer material compared with the stiffer material and its combination. In addition, the single softer material resulted in reduced frictional stress under the first metatarsal head compared with the stiffer material and the combination of materials. The softer material and its combination have a beneficial effect on plantar pressure reduction and redistribution for a diabetic foot with neuropathy. This study provided an effective approach for CMI material selection using FEA.

Diabetic foot ulcer patients are usually unaware of excessive pressure on their feet due to lost pressure sensitivity. Offloading insoles are used to alleviate foot pain. This study investigated the effect of infill pattern and infill density on plantar pressure reduction for 3D-printed insoles while walking. The study involves five infill patterns: grid, honeycomb, triangle, cubic, and gyroid, along with several infill densities ranging from 14% to 20%. The test 3D-printed thermoplastic polyurethane specimens were assessed for mechanical properties to identify suitable infill patterns for creating prototypes of insoles. The results indicated that the honeycomb infill pattern exhibited the highest maximum compression load at 50% compressive strain and has a significant area under the loading-unloading curve, signifying high energy absorption. Conversely, the gyroid infill pattern exhibited the lowest maximum compression load at 50% compressive strain and minimal energy absorption. Both infill patterns with 20% infill density were applied in 3D-printed insoles and tested on the foot plantar pressure of healthy male volunteers during walking. No statistically significant differences in plantar pressure were observed between the two infill patterns compared to walking without insoles. A reduction in plantar pressure at hindfoot was observed when using the insoles, although this change was not statistically significant.

BACKGROUND: Charcot foot deformity, a severe complication of diabetes, involves neuropathy and abnormal peak plantar pressure in the midfoot and forefoot. However, orthotic interventions and shoe modifications are used to address the sequelae of Charcot neuroarthropathy, offering different approaches to managing abnormal peak plantar pressure. OBJECTIVE: To compare the effects of three types of therapeutic offloading diabetic shoes; prefabricated, relasting, and double rocker-modified shoes on peak plantar pressure in the midfoot and forefoot of nonulcerated chronic Charcot foot during walking. METHODOLOGY: A repeated measure design involved 15 participants (40% males and 60% females) with a mean age of 60.73 years (SD=10.50), with Charcot neuropathy. Participants were provided with three types of shoes; prefabricated, relasting, and double rocker-modified shoes, each equipped with the same custom-made insole (CMI). Plantar pressure was recorded while walking on level ground, focusing on the forefoot, midfoot, and hindfoot. The study also investigated additional variables affecting plantar pressure distribution, including the pressure-time integral and contact area. FINDINGS: The type of shoe had distinct effects on the distribution of plantar pressure. The double rocker-modified shoe particularly impacted forefoot pressure during the terminal stance phase of the gait cycle. Peak plantar pressure at the forefoot increased by 5.37% with double rocker-modified shoes compared to relasting shoes. Both double rocker-modified and prefabricated shoes reduced midfoot peak plantar pressure by 8.73% and 11.97%, respectively. Similar trends were observed at the hindfoot, with reductions in peak plantar pressure. However, there were no significant differences in regional peak plantar pressure between the types of shoes except for the central forefoot (F (1.61, 22.5) = 5.69,p = 0.014). CONCLUSION: There were no significant differences in the effectiveness of prefabricated, relasting, and double rocker-modified shoes in reducing and redistributing peak plantar pressure in high-risk areas of chronic Charcot foot.