Video Analysis of Human Gait and Posture to Determine Neurological Disorders

Abstract

This paper investigates the application of digital image processing techniques to the detection of neurological disorder. Visual information extracted from the postures and movements of a human gait cycle can be used by an experienced neurologist to determine the mental health of the person. However, the current visual assessment of diagnosing neurological disorder is based very much on subjective observation, and hence the accuracy of diagnosis heavily relies on experience. Other diagnostic techniques employed involve the use of imaging systems which can only be operated under highly constructed environment. A prototype has been developed in this work that is able to capture the subject's gait on video in a relatively simple setup, and from which to process the selected frames of the gait in a computer. Based on the static visual features such as swing distances and joint angles of human limbs, the system identifies patients with Parkinsonism from the test subjects. To our knowledge, it is the first time swing distances are utilized and identified as an effective means for characterizing human gait. The experimental results have shown a promising potential in medical application to assist the clinicians in diagnosing Parkinsonism.

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