To detect whether a patient has a pronated foot the doctor will usually stand behind the patient and directly observe their walking state and then give a diagnosis However this diagnosis usually only has comments such as normal mild or moderate There will not be a very precise quantification There are many indicators to quantify the flat feet level Here we choose a commonly used indicator in a clinical practice called Rear Foot Angle RFA which is defined as the angle between the midline of the lower leg and the midline of the heel This research uses the SiamRPN++ tracking algorithm to track multiple marker dots attached to the patient’s foot in the image and uses the self-assembled stereo cameras with the PSMNet algorithm to obtain its 3D position to simulate common motion capture systems Then estimating the RFA of the left and right leg in each frame to do the quantification In addition to the RFA measured in the original camera image plane in order to solve the viewing angle error caused by using a fixed-position camera this research also proposes a virtual camera follow-up based estimation by perspective projecting 3D dots position from camera coordinates to the virtual camera one then estimating RFA in the virtual image plane Using this method to measure RFA can have a more stable result in the swing phase
Multi-Dots SiamRPN++ Tracking for Pronated Foot Analysis in PSMNet Stereo Space
東成, 釋. (Author). 2020
Student thesis: Doctoral Thesis