Dynamic analysis of human gait cycle

number: 
3153
English
Degree: 
Author: 
Basma Abdulsahib Faihan
Supervisor: 
Dr. Sadiq J. Abass
year: 
2013
Abstract:

The locomotion biomechanics study provides very extensive and interesting material for investigating the physiological process involved and the neural mechanisms controlling the locomotor system of the body. Gait analysis, the systematic analysis of locomotion, is used today for pre˗treatment assessment, surgical decision making, postoperative follow-up, and management of patients. The purpose of the study is to investigate the dynamics of human walking over a complete gait cycle Level-walking experiments were performed by two-dimensional motion analysis using a digital video camera (Sony, 25 Hz) with two Advanced Mechanical Technology Inc. (AMTI) force plates. Kinematic data were obtained from the two-dimensional trajectories of 8 reflective markers using SkillSpector software (version 1.2.4). MATLAB software (version 8.1) has been adopted in this work to obtain Pedotti diagram and for inverse dynamics computation. The mass and the center of mass of each segment were obtained from anthropometric data. Digital low pass Butterworth filter with zero phase-shift and cut-off frequency of 4.5 Hz was used. Joints' angular displacement, forces, moments, powers and energies were obtained during gait cycle. The study was made on fourteen healthy volunteers (10 males and 4 females); a male with cerebral palsy, and an old female underwent unilateral knee arthroplasty. Since the greater trochanter marker might not appear during walking, suppressing arms' swing during walking was discussed. Because cerebral palsy subject might not move normally on the force plates' walkway; the ground reaction forces were estimated using only the single digital video camera. Vertical ground-reaction forces obtained from the kinematic data gave reasonable estimates of vertical ground forces (RMSEs of 11%˗19%), while the horizontal ground force showed less tendencies (RMSEs of 18%˗25%). These data can be used as standard measures in pathology studies, as input to theoretical joint models, and as input to mechanical joint simulators.