AIMC Topic: Foot
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A Deep Learning Method for Foot Progression Angle Detection in Plantar Pressure Images.
Sensors (Basel, Switzerland)
Apr 5, 2022
Foot progression angle (FPA) analysis is one of the core methods to detect gait pathologies as basic information to prevent foot injury from excessive in-toeing and out-toeing. Deep learning-based object detection can assist in measuring the FPA thro...
Subtalar axis determined by combining digital twins and artificial intelligence: influence of the orientation of this axis for hindfoot compensation of varus and valgus knees.
International orthopaedics
Feb 9, 2022
PURPOSE: Previous studies evaluating hindfoot and knee alignment have suggested compensation between the knee and the hindfoot deformities. However, these studies did not investigate the influence of the orientation of the subtalar axis on the result...
Anomalous Gait Feature Classification From 3-D Motion Capture Data.
IEEE journal of biomedical and health informatics
Feb 4, 2022
The gait kinematics of an individual is affected by various factors, including age, anthropometry, gender, and disease. Detecting anomalous gait features aids in the diagnosis and treatment of gait-related diseases. The objective of this study was to...
Different Effects of Robot-Assisted Gait and Independent Over-Ground Gait on Foot Plantar Pressure in Incomplete Spinal Cord Injury: A Preliminary Study.
International journal of environmental research and public health
Nov 17, 2021
BACKGROUND: There is insufficient evidence to establish the optimal treatment protocol for robot-assisted gait training.
A Deep Learning Approach for Foot Trajectory Estimation in Gait Analysis Using Inertial Sensors.
Sensors (Basel, Switzerland)
Nov 12, 2021
Gait performance is an important marker of motor and cognitive decline in older adults. An instrumented gait analysis resorting to inertial sensors allows the complete evaluation of spatiotemporal gait parameters, offering an alternative to laborator...
Gait Phase Estimation by Using LSTM in IMU-Based Gait Analysis-Proof of Concept.
Sensors (Basel, Switzerland)
Aug 26, 2021
Gait phase detection in IMU-based gait analysis has some limitations due to walking style variations and physical impairments of individuals. Therefore, available algorithms may not work properly when the gait data is noisy, or the person rarely reac...
Sexing white 2D footprints using convolutional neural networks.
PloS one
Aug 18, 2021
Footprints are left, or obtained, in a variety of scenarios from crime scenes to anthropological investigations. Determining the sex of a footprint can be useful in screening such impressions and attempts have been made to do so using single or multi...
Segmentation Approaches for Diabetic Foot Disorders.
Sensors (Basel, Switzerland)
Jan 30, 2021
Thermography enables non-invasive, accessible, and easily repeated foot temperature measurements for diabetic patients, promoting early detection and regular monitoring protocols, that limit the incidence of disabling conditions associated with diabe...
Machine-Learning Based Determination of Gait Events from Foot-Mounted Inertial Units.
Sensors (Basel, Switzerland)
Jan 27, 2021
A promising but still scarcely explored strategy for the estimation of gait parameters based on inertial sensors involves the adoption of machine learning techniques. However, existing approaches are reliable only for specific conditions, inertial me...
Artificial Intelligence-Assisted motion capture for medical applications: a comparative study between markerless and passive marker motion capture.
Computer methods in biomechanics and biomedical engineering
Dec 8, 2020
We aimed to determine whether artificial intelligence (AI)-assisted markerless motion capture software is useful in the clinical medicine and rehabilitation fields. Currently, it is unclear whether the AI-assisted markerless method can be applied to ...
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