A MATLAB-based biomedical signal de-noising applied to digital signal processing course for third-year students

Abstract

Signal de-noising is one of the major topics of engineering application covered in an undergraduate-level digital signal processing course. Generally speaking, it involves a number of tedious concepts that have intrinsic physical meaning, which is difficult for students to understand . In this paper, an educational method using diaphragmatic electromyographic (EMGdi) as the de-noising object, which runs on the MATLAB software, has been developed for the convenience of learning and understanding for three-years students in digital signal processing course. This method transforms the analog filter to a digital filter by applying bilinear transformation equations, which allows the students explore the various characteristics of digital filter, such as low pass filter, high pass filter, band pass filter and band stop filter. That means Laplace equation transformed by inductance, capacitance and resistance will be replaced by the z equation, which is used for deriving sequence of difference equations. In the case studies, the clinical EMGdi is used to show the features of the developed method. Furthermore, classroom experience in the Nanfang College of Sun Yat-sen University has shown that the developed method helps in consolidating a better understanding of signal de-noising processing in digital signal processing course.