Design of Deep Learning Experiment Teaching Case based on EMG Signal Analysis

Against the background of new engineer, universities pay more and more attention to the cultivation of innovative talents with cross-disciplines. The artificial intelligence-related courses are typical interdisciplinary and strong practical courses, and experimental teaching is always an important part of it. In this paper, a case of deep learning experiment teaching based on electromyography signal feature extraction is designed for the intersection of disciplines. This case combines biological information and artificial intelligence technology, including data set construction, network model construction and training, biological information feature classification recognition and other experimental content. By studying this paper, students can not only understand the characteristics and applications of biological information, but also understand and master the basic methods and model construction process of using deep learning technology to process biological information. It has important reference value for training and improving students' ability to analyze and solve problems across disciplines.