ABSTRACT
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.
