AIMC Topic: Foot
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Predicting diabetic peripheral neuropathy through advanced plantar pressure analysis: a machine learning approach.
Scientific reports
Jul 1, 2025
Diabetic foot Ulceration (DFU) is a severe complication of diabetic foot syndrome, often leading to amputation. In patients with neuropathy, ulcer formation is facilitated by elevated plantar tissue stress under insensate feet. This study presents a ...
A novel deep learning approach to classify 3D foot types of diabetic patients.
Scientific reports
Apr 22, 2025
Diabetes mellitus is a worldwide epidemic that leads to significant changes in foot shape, deformities, and ulcers. Precise classification of diabetic foot not only helps identify foot abnormalities but also facilitates personalized treatment and pre...
Neural networks can accurately identify individual runners from their foot kinematics, but fail to predict their running performance.
Journal of biomechanics
Apr 2, 2025
Athletes and coaches may seek to improve running performance through adjustments to running form. Running form refers to the biomechanical characteristics of a runner's movement, and can distinguish individual runners as well as groups of runners, su...
Parametric cushioning lattice insole based on finite element method and machine learning: A preliminary computational analysis.
Journal of biomechanics
Apr 1, 2025
The cushioning performance of insole has always been a critical consideration in its design. While the development of intelligent methods and the emergence of additive manufacturing (AM) technology have enhanced design freedom and convenience, a stan...
A Comparative Study of Plantar Pressure and Inertial Sensors for Cross-Country Ski Classification Using Deep Learning.
Sensors (Basel, Switzerland)
Feb 28, 2025
This work presents a comparative study of low cost and low invasiveness sensors (plantar pressure and inertial measurement units) for classifying cross-country skiing techniques. A dataset was created for symmetrical comparative analysis, with data c...
Deep learning opportunistic screening for osteoporosis and osteopenia using radiographs of the foot or ankle - A pilot study.
European journal of radiology
Feb 4, 2025
BACKGROUND: The gold standard method for diagnosing low bone mineral density (BMD) is using dual-energy X-ray absorptiometry (DXA) however, most patients with low BMD are often not screened. We aimed to create a deep learning (DL) model to screen for...
Foot trajectory as a key factor for diverse gait patterns in quadruped robot locomotion.
Scientific reports
Jan 13, 2025
Four-legged robots are becoming increasingly pivotal in navigating challenging environments, such as construction sites and disaster zones. While substantial progress in robotic mobility has been achieved using reinforcement learning techniques, quad...
Swing limb detection using a convolutional neural network and a sequential hypothesis test based on foot pressure data during gait initialization in individuals with Parkinson's disease.
Physiological measurement
Dec 16, 2024
. Start hesitation is a key issue for individuals with Parkinson's disease (PD) during gait initiation. Visual cues have proven effective in enhancing gait initiation. When applied to laser-light shoes, swing-limb detection efficiently activates the ...
Super-fast and accurate nonlinear foot deformation Prediction using graph neural networks.
Journal of the mechanical behavior of biomedical materials
Dec 9, 2024
Recently, there has been a significant increase in the number of foot diseases, highlighting the importance of non-surgical treatments. Customized insoles, tailored to an individual's foot morphology, have emerged as a promising solution. However, th...
Robotic feet modeled after ungulates improve locomotion on soft wet grounds.
Bioinspiration & biomimetics
Nov 4, 2024
Locomotion on soft yielding grounds is more complicated and energetically demanding than on hard ground. Wet soft ground (such as mud or snow) is a particularly difficult substance because it dissipates energy when stepping and resists extrusion of t...
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