Development Of A Multi-posture Rehabilitation Training Robot For Lower Limb

Hemiplegia is a very common sequelae of stroke and it affects greatly on lowerlimb movements of the patients. Clinically, patients are usually treated with physicaltherapy. Treadmill gait rehabilitation robot is developed for the patients who havealready gained the walking abilities, but not fit for patients in early stage ofhemiplegia. In this research, a novel robot system is developed withposture-transform training and exoskeleton coordination training functions. By themethods of feedback system and the evaluation system, the stimulations towordpatients’ nerve and muscle are strengthened. The work also aims at improvingcardio-pulmonary function of the patients by the rehabilitation robot in clinicalapplication. The main works are listed as follows.1. The parameters of rehabilitation robot for lower limbs are confirmedaccording to clinical trials data especially the data of patients in early stage ofhemiplegia, as well as the medical theory of hemiplegia rehabilitation. The robot ismainly designed to assist patients’ lower limbs motion with the coordination of hipand knee in different mode, such as active-assistance training mode and passivetraining mode. Different spacial trajectory of the hip and knee such as gait trajectoryand straight line trajectory are provided in the meantime. In addition, the robotplatform can realize posture adjustment, to provide weight reduction and cardiotraining for the patients.2. The rehabilitation training robot for lower limbs is analysed and designed inconsideration of the following aspects: training system, Patients’ weight reduction&securing system, control system, feedback system and so on. Furthermore, thefeasibility of the key components and whole robot system are verified and tested.The performances of the rehabilitation training robot in multi-posture trainingcondition are compared with the horizontal condition. 3. The rehabilitation effect is tested by multi-posture training through tilt planechanging from horizontal to vertical and doing exoskeleton exercises by severalhealthy subjects on the robot. In this conditions, the effects under different trainingparameters such as tilting angle, traing mode, training trajectory and training time arecompared. The electromyography data, kinematic data, and cardio-pulmonary dataare collected and analyzed quantificationally on the robot.