Instrumented gait analysis in osteoarthritis: From lab towards ambulatory systems
Abstract
Knee osteoarthritis is a progressive disease characterized by the degeneration of articular cartilage of the knee joint. To understand the causes and effects of pathological gait symptoms and to optimize intervention management, refined methods for the quantitative assessment of gait and its impairment are necessary. However, objective functional gait measures are commonly not assessed in clinical practice. This thesis presents the application of state-of-the-art methods of human gait analysis using infrared cinematography to investigate the fundamentals of gait and the effect of non-invasive interventions in osteoarthritis. Although cinematography is considered the gold standard in movement analysis, its use for gait assessment in clinical routine is limited due to high costs and operational efforts. Therefore, a mobile sensorbased system was validated and then applied to a population of osteoarthritis patients undergoing total knee arthroplasty. The system achieved high discriminative ability and a highly accurate prediction of whether patients‘ gait improved or aggravated after surgery was possible based on pre-operative gait parameters. The findings are beneficial for the domain of intervention research and for the integration of objective and ambulatory gait analysis into clinical practice.
Keywords
Motion Capturing; Maschinelles Lernen; Bewegungsstörung; Beschleunigungssensor; Gelenkkrankheit; GanganalyseDOI
10.25593/978-3-96147-179-9ISBN
9783961471799, 9783961471799, 9783961471782Publisher
FAU University PressPublisher website
https://www.university-press.fau.de/Publication date and place
Erlangen, 2019Series
FAU Studien aus der Informatik, 7Classification
Biomechanics, human kinetics
Machine learning


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