Abstract
Abstract The advancing of technology can enhance human life. However, aging is still a problem for human. Through time, Meniscus will gradually wear out with continuous loading. Lower-limb exoskeleton had been studied for several years; this thesis follows previous research and focus on perfection in lower-limb exoskeleton. Electromyography (EMG) will transmit through muscle while muscle contraction. Researches had pointed out relationship between muscle activity and EMG. By knowing these characteristics, our lower-limb exoskeleton can be trained through an Adaptive Network-based Fuzzy Interface System (ANFIS), to control our exoskeleton instantaneously. Other researchers pointed out that muscle contraction can be divided into two types, concentric and eccentric. With the difference in muscle contraction, the model of EMG and moment should be adjusted. Accordingly, this thesis will deal with this problem to create a better principle in exoskeleton control. Our exoskeleton is based on special designed M shaped springs, which were used as energy storage element. We dynamically change the system mode to stance mode, swing mode or non-effect mode, with different supporting way in different modes, our exoskeleton pulls and releases the spring dynamically to store and provides the potential energy to our body while in need. With this idea of assisting in the correct time and the correct amount of energy, we would be able to ease off the problem of deteriorating cartilage and prolong the ability for elders to travel.