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Deep Learning supported gait analysis

Deep Learning supported gait analysis
type:Student research project

M.Sc. Ady Naber

person in charge:

Sandro Braun

Gait analysis is important for the assessment of clinical endpoints for the therapy of e.g. Morbus Parkinson or Multiple Sclerosis (MS).
However, the current procedure requires a gait analysis lab setup or exhaustive manual annotation work.
Our aim is to develop a tool for marker-free video-based gait analysis under real-world conditions.
Therefore, we strive to employ modern techniques of Computer Vision and Deep Learning, 
to extract the clinically relevant gait parameters with a high level of automation.