Clinical Gait Analysis

Processing clinical gait data to identify gait abnormalities within a neurorehabilitation program.

Working with the Daan Theeuwes Centrum and the Amsterdam UMC, a streamlined approach to assess gait abnormalities for the purpose of clinical evaluation was developed and validated. Using an automated rule based method and vertical ground reaction force data, raw gait information is segmented and processed into gait cycles for feature extraction. In order to objectify clinical impression and document changes in gait pattern, four normalcy index for overall gait, hip joints, knee joints and trunk flexion-extension were obtained using a method based on principal component analysis. The results demonstrate a potential for the normalcy index to be used to quantify abnormal gait based on its degree of deviation from normality, and may be adapted within future research as a robust metric to evaluate rehabilitation progress and aid with prognosis modeling.