The control strategy based on surface electromyography (sEMG) is an important basis for humancomputer interaction and has important significance in human control of peripheral devices. The myoelectric control strategy recognizes the body′s motion intention through sEMG, and then converts it into control commands to achieve a precise and stable control of peripheral devices. The use of sEMG has overcome the limitations of traditional input devices in terms of portability, operating space and special groups. This paper discussed the development of the myoelectric control strategy, and compared the differences between sEMG and the Electroencephalogram (EEG) as the input of the control system. The application of the sEMGbased control strategy in rehabilitation and orthopedics was expounded, and the future improvement of these applications was pointed out. This paper analyzed the technical problems related to the acquisition of sEMG and the improvement of the control effect and robustness, which hindered the development of myoelectric control strategy based on pattern recognition. Finally, the paper listed some feasible improvement directions for sEMG control systems.