Abstract
Abstract Electromyogram (EMG) is an phenomenon of physiology. As the muscle contracting more, the EMG signal grows shaper. We can use this kind of phenomenon designing our prosthesis. Except for those injured who totally lost their entire extremity, we can gather data from their EMG. The prosthesis system will notice that the user is tend to move his(her) body when the shacking amplitude of the use's EMG is much greater than that in the static release, static condition. Therefore, the object of designing this prosthesis is to enhance human's physical ability instead of providing artificial limbs. In the beginning of the thesis, we introduce the EMG processing circuit, which contain amplifiers and filters. The processed EMG data will then be connected to the torque on knee during the sit- to- stand motion. While the EMG signal is received by system during the time the user bend his knee, the relative assist torque will come out immediately, trying to make the user feel as easy as just stand still. The objective of this study is trying to improve the original assistant force algorithm, which is based on the force-estimate shoe-and-angle meter module. This kind of method will be mentioned usually in this thesis and kept preparing with the advanced method proposed in this thesis.