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A methodological modular framework is presented for automated assessment of gait patterns. The processing steps of data selection, gait parameter calculation and evaluation are not limited to a specific field of application and are largely independent of case-based clinical expert knowledge. For these steps, a variety of mathematical methods was used and the validity of the approach to assess gait parameters tested by applying it to the clinical problem of Botulinum Toxin A (BTX-A) treatment of the spastic equinus foot. A set of 3670 parameters was ranked by relevance for classification of a group of 42 diplegic cerebral palsy (CP) patients and an age-matched reference group. The same procedure was performed for pre- and post-therapeutic data sets of these patients. Gait parameters of high relevance coincided well with results of previous studies based on partly manual and more subjective parameter selection. A norm distance measure is introduced to facilitate the quantification of deviations from a normal walking pattern and can be used as an overall scalar measure to evaluate differences in gait patterns or as a set of measures attributing each joint angle separately.

A modular methodology for automated gait data evaluation: The aim of Instrumented Gait Analysis is to measure data such as joint kinematics or kinetics during gait in a quantitative way. The data evaluation for clinical purposes is often performed by experienced physicians (diagnosis of specific motion dysfunction, planning and validation of therapy). Due to subjective evaluation and complexity of the pathologies, there exists no objective, standardized data analysis method for these tasks. This article covers the development of a modular, computer-based methodology to quantify the degree of pathological gait in comparison to normal behavior, as well as to automatically search for interpretable gait abnormalities and to visualize the results. The outcomes are demonstrated with two different patient groups.