Hands are important parts of a human body. It is not only the main tool for people to engage in productive labor, but also an important communication tool. When the hand moves, the human body produces a kind of signal named surface electromyography (sEMG), which is a kind of electrophysiological signal that accompanies muscle activity. It contains a lot of information about human movement consciousness. The bionic limb is driven by multi-degree-freedom control, which is got by converting the recognition result and this can meet the urgent need of people with disabilities for autonomous operation. A profound study of hand action pattern technology based on sEMG signals can achieve the ability of the bionic limb to distinguish the hand action fast and accurately. From the perspective of the pattern recognition of the bionic limb, this paper discussed the human hand action pattern recognition technology of sEMG. By analyzing and summarizing the current development of human hand movement recognition, the author proposed a bionic limb schema based on artificial neural network and the improved DT-SVM hand action recognition system. According to the research results, it is necessary to expand the type and total amount of hand movements and gesture recognition, in order to adapt to the objective requirements of the diversity of hand action patterns in the application of the bionic limb.
Application of Surface Electromyography in the Dynamics of Human Movement