Background: Alterations in the lower limb kinematics and kinetics of diabetic patients have been reported in previous studies. Inappropriate choices of orthopedic insole materials, however, fail to prevent diabetic foot ulcers and modify abnormal gait. The aim of this study was to quantitatively compare the effects of contoured insoles with different materials on the kinematics of and kinetics changes in the diabetic elderly during gait. Methods: There were 21 diabetic patients who participated in this study. Three-dimensional (3D) experimental contoured insoles constructed of soft (i.e., Nora Lunalastik EVA and PORON^® Medical 4708) and rigid (i.e., Nora Lunalight A fresh and Pe-Lite) materials with Langer Biomechanics longitudinal PPT^® arch pads were adopted. An eight-camera motion capture system (VICON), two force plates, and an insole measurement system—Pedar^® with 99 sensors—were utilized to obtain the kinematics and kinetics data. The plug-in lower body gait model landmarks were used for dynamic data acquisition during gait. The corresponding data from five gait cycles were selected and calculated. Results: The range of motions (ROMs) of the ankle joint (p = 0.001) and knee joint (p = 0.044) were significantly influenced when the contoured insoles were worn in comparison to the barefoot condition. The joint moments of the lower limbs with maximum ankle plantarflexion during the loading response and maximum knee and hip flexions were significantly influenced by the use of contoured insoles with different materials in the diabetic elderly. The peak plantar pressure (PPP) of the forefoot (p < 0.001), midfoot (p = 0.009), and rearfoot (p < 0.001) was significantly offloaded by the contoured insoles during the stance phase, whilst the PPP of the rearfoot (p < 0.001) was significantly offloaded during the swing phase. Conclusions: The contoured insoles, especially those constructed with soft materials, significantly offloaded the PPP during gait—hence accommodating certain abnormal gait patterns more effectively compared to going barefoot.

Studying the in-shoe microclimate of older individuals is important for enhancing their foot comfort and preventing foot diseases. However, there is a lack of scientific work that explores the thermo-physiological wear comfort of older individuals with different footwear. This study aims to examine the effects of upper footwear materials on changes and distributions in the foot skin temperature and relative humidity for older individuals. Forty older individuals are recruited to perform sitting and walking activities under four experimental conditions in a conditioning chamber. The findings indicate that footwear upper constructed of highly permeable mesh fabric with large air holes shows fewer changes in foot skin temperature (ranging from 1.3 to 3.3 °C) and relative humidity (ranging from −13.3 to 5.7%) throughout the entire foot during dynamic walking, as well as higher subjective ratings on perceived thermal comfort when compared to footwear made of synthetic leather and composite layers. The findings serve to enhance current understanding of designing footwear with optimum comfort for older adults.

Early diagnosis of pediatric flatfoot is critical to provide effective and timely orthotic intervention to prevent long-term complications. Current methods like manual measurements or three-dimensional (3D) scanning are often not ideal for rapid screening. This study addresses this gap by developing a regression model to predict foot arch height (AH) among Chinese primary schoolchildren by using simple two-dimensional (2D) footprint parameters, thus enabling orthosis prescription in an accessible and timely manner. A correlational study is conducted with 57 Hong Kong children who are 8–12 years old with flatfeet. Anthropometric footprint measurements, including four footprint indexes, Clarke’s Angle (CA), Chippaux–Smirak Index (CSI), Staheli Index (SI), and Sztriter–Godunov index (KY) are obtained from 2D footprints, whereas the arch height (AH) is measured by a caliper. One-way ANOVA is used to identify the measurements associated with flatfoot severity. A stepwise regression analysis is also used to determine the key footprint predictors of AH. The results show that the footprint indexes, heel width, ball width, medial ball length, arch depth and arch breadth significantly differentiated flatfoot severity. The stepwise regression model explains 44% of the variance by identifying the CA, heel width (HW) and arch depth (AD) as the strongest predictors of AH. The CA, HW and AD measured from the 2D footprints can serve as practical predictors of AH in Chinese flatfooted children. This study offers a transformative, accessible tool for pediatric flatfoot screening. Unlike resource-intensive 3D scanning or clinical assessments, our approach uses simple 2D footprints to estimate AH. This enables rapid, preliminary screening in diverse settings, empowering individuals to identify potential issues and seek timely professional evaluation. By democratizing access to early detection, it streamlines referrals, reduces unnecessary complex assessments, and facilitates earlier, personalized orthotic intervention for improved long-term foot health.