Design And Implementation Of The Smartshoes And Applications For The Lower Extremity Exoskeleton

Lower Extremity Exoskeletons(LEEs) for the paraplegia patients are manned robots and they are designed to help these users regain the lower limb athletic abilities. When faced with complex environments, it's necessary to control the LEEs adaptively based on the motion state and feedback of the ground. So, the smartshoes are designed to get the gait data and recognize the ground surface types, which can assist the LEEs to adjust the control strategies intelligently. The main research contents in this thesis are as follows:Smartshoe scheme based on inertial and force sensors is proposed. A few sensors are analyzed to demonstrate which one is more suitable for the smartshoes. The hardware of smartshoes is compatible with the exokeletons, including the mechanical structure and circuit interface.Gait of the users is analyzed with the smartshoes, including step length and height, gait phases and pressure center. Inertial sensors are used to compute the step length and height based on the inertial navigation theory. Human gait phases are detected by measuring the ground contact forces. According to force sensor data the smartshoes also calculate trajectories of pressure center.Ground surface types are recognized. Downhill, uphill, level concrete floor and level lawn are the study objects. The smartshoes collect sensor data when the feet hit the ground, and features are extracted from the raw data. Principal component analysis method is used to reduce the data dimension, and the recognition is accomplished by minimum distance classifier.