A Deep Learning Method for Foot Progression Angle Detection in Plantar Pressure Images

A Deep Learning Method for Foot Progression Angle Detection in Plantar Pressure Images

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 through plantar pressure images. This study aims to es...

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Bibliographic Details
Main Authors: Akbari, V.B.H (Author), Ardhianto, P. (Author), Jan, Y.-K (Author), Liau, B.-Y (Author), Lin, C.-Y (Author), Lung, C.-W (Author), Subiakto, R.B.R (Author), Tsai, J.-Y (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
Angle detection
angle parameter
Angle parameter
Core method
Deep learning
foot clinic
Foot clinic
foot problems
Foot problems
Ground truth
Learning methods
object detection
Object detection
Object recognition
Physiological models
Plantar pressures
Precision model
YOLO
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