Computational Intelligence in Gait and Movement Pattern Analysis
Analysis of gait or human movement oﬀers insights into information that can help in the diagnosis and treatment of walking and movement disorders. In this chapter, we begin by providing an overview of the commonly used biomechanical and motion analysis techniques used in gait analysis and highlight the key features extracted from graphs for characterizing movement patterns. The applications involving motion analysis are extensive, ranging from clinical applications, rehabilitation and health, to technique analysis and performance enhancement in sport. Many features and parameters are used to characterize movement patterns, and the type of gait features in such analysis tasks range from directly measurable variables to parameters that require signiﬁcant data processing. When analyzing movement, in addition to statistical techniques, approaches based on machine learning have been used to create better models for linking the inputs and outputs in the assessment of movement patterns. We brieﬂy discuss some areas of applications that have beneﬁted from using CI methods.