|dc.description.abstract||This thesis aims to design a novel task based knee rehabilitation exoskeleton device through kinematic synthesis. In contrast to prevailing research efforts, which attempt to mimic the human limb by assigning each human joint with an equivalent exoskeleton joint (e.g. a hinge joint for the elbow and knee), this thesis provides an alternative systematic approach for the design of exoskeletons to assist the complex 3D motions of the human Knee. With this method, it is not necessary to know the anatomy of the targeted limb, but rather to define the motion of the exoskeleton segments based on its point of attachment to the limb. Good alignment is often difficult and the distances between joints must be adjusted to accommodate the variety of human size. Furthermore, attempting to align each robotic joint axis with its human counterpart assumes that the position of the axis can be accurately known, and that such a fixed axis exists for the range of motion of the joint or set of joints, which is not always the case. In human- exoskeletons synergy, especially in industrial settings and rehabilitation applications, due to the repetitive and strenuous nature of the task, the fit, comfort and usability of these exoskeletons are important for the safety of the user and for the automation of the task. Improper fitting may lead an exoskeleton to move in a way that exceeds the range of movement of the human body and tear muscle ligaments or dislocate joints.
In this thesis, to study the motion of the desired clinical trajectories of the human knee, the state-of-the-art of motion capture and data analysis techniques are utilized. The collected experimental kinematic data is used as an input to the kinematic synthesis. Parallel mechanisms with single degree-of-freedom (DOF) are considered to generate the complex 3D motions of the lower leg. An exact workspace synthesis approach is utilized, in which, the parameterized forward kinematics equations of each serial chain are to be converted to implicit equations via elimination. The implicit description of the workspace is made to be a function of the structural parameters of the serial chain, making it easy to relate those parameters to the motion capture data. A prototype of the mechanism has been built using 3D printing technology. And an Electromyography (EMG) signals and Force sensing resistors (FSR) are utilized to implement an assist as needed controller. The EMG signal is captured from the user leg and force sensing resistors (FSR) are applied at the attachment point of the exoskeleton and the leg, this helps to get the amount of force applied by the exoskeleton to the leg as well as for recovery tracking. The assist as needed controller eliminates the need of constant supervision, and hence saves time and reduces cost of the rehabilitation process.||