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Human gait and posture analysis for diagnosing neurological disorders

This paper describes a number of new techniques to enhance the performance of a video analysis system, free from motion markers and complicated setup procedures, for the purpose of quantitatively identifying gait abnormalities in static human posture analysis. Visual features are determined from still frame images out of the entire walking sequence. The features are used as a guide to train a neural network, in an attempt to providing assistance to clinicians in diagnosing patients with neurological disorders.