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Please use this identifier to cite or link to this item: http://hdl.handle.net/1860/3020

Title: The propulsion dynamics of human locomotion
Authors: Rosen, Sarah
Keywords: Biomedical engineering;Human Locomotion;Cerebral Palsy
Issue Date: 3-Jun-2009
Abstract: Gait analysis quantifies biomechanical aspects of an individual‟s gait. It can be used to quantify abnormalities in gait, identify underlying biomechanical mechanisms and track changes in gait biomechanics over time or in response to surgical or clinical interventions. In clinical gait analysis, kinematic and kinetic data are captured and used for clinical decision making; however, clinicians rely primarily on the kinematic information. Further, gait analyses are commonly performed in the confines of a closed clinical laboratory, and only on level surfaces with limited walking lengths. Another often overlooked component of gait analysis is the quantification of energy expenditure (EE), which is directly impacted by the interplay between kinetics and mechanical energy changes. The long-term goal of this research is to develop data collection and analytic methods to combine kinetic and kinematic, better quantify the relationship between kinetic and EE data and support means for data collection outside of traditional laboratories. In addition, application to pathological gait, specifically that of children with Cerebral Palsy (CP), was preliminarily assessed. The primary short term goal of this work was to develop analytic means to determine the acceleration of the center of mass (COM) and ground reaction forces (GRFs) during gait that relate to the consistency and stability of the gait pattern, as well as to energy expenditure. Application of a consistency test based on the force time integrals of the anterior-posterior (A-P) component of the GRF defined the boundaries of a consistent gait both in typically developed (TD) children and children with CP. GRFs characteristics were examined both in TD children and children with CP and the results demonstrated that GRFs characteristics differ between these populations and are capable of detecting gait abnormalities. Good correlations between the peak braking force and EE were found for both populations. An analytical method, consisting of two accelerometers placed on the back, was developed for derivation of GRFs characteristics from the COM‟s acceleration. The results showed good to excellent correlations to GRF data when several characteristics of the GRFs were compared. The results support the continuation of this work towards the achievement of the long term goal.
URI: http://hdl.handle.net/1860/3020
Appears in Collections:Drexel Theses and Dissertations

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