Generating pathological gait patterns via the use of robotic locomotion models.
In this article we explore the feasibility of modeling normal and pathological human gait using a relatively simple five-element model. We use a robust, nonlinear control scheme to regulate the gait patterns of the model. Simulated gait patterns are generated through the use of five constraint relationships that depend on four gait parameters. Two pathological conditions due to muscle weaknesses were simulated by modifying the control torques at the joints. We demonstrate that the model successfully approximates the qualitative and quantitative dynamic trends that were observed in normal and pathological human locomotion.
Ephanov
Anton
A
Mechanical Engineering Department, Southern Methodist University, Dallas, TX 75275, USA.
Hurmuzlu
Yildirim
Y
D000465:Algorithms; D003198:Computer Simulation; D005528:Foot / Q000503:physiopathology; D005684:Gait / Q000502:physiology*; D006615:Hip / Q000503:physiopathology; D006801:Humans; D007717:Knee / Q000503:physiopathology; D008124:Locomotion / Q000502:physiology*; D009038:Motion; D009127:Muscle Rigidity / Q000503:physiopathology; D018482:Muscle, Skeletal / Q000503:physiopathology; D009436:Neural Tube Defects / Q000503:physiopathology; D017711:Nonlinear Dynamics; D010146:Pain / Q000503:physiopathology; D011051:Poliomyelitis / Q000503:physiopathology; D011187:Posture / Q000502:physiology; D012371:Robotics / Q000379:methods* / Q000639:trends