Biosignal Processing and Data Mining

Synopsis Biosignal enhancement, feature extraction and physiological interpretation are important aspects in biomedical engineering field. Various biosignals can be manipulated through proper representation, transformation, visualization and optimization. This course will introduce fundamental concepts and approaches, such as filtering, detection, estimation, and classification, for various biosignal processing and data mining. It will provide students a brief picture of biosignal from detection to application by following the course "Introduction to Biosignal Detection".
Main Topics
  • Introduction

  • Decomposition and Reconstruction of Biosignals

  • Detection of Bioevents

  • Processing of Biosignals and Bioevents

  • Analysis of HRV in Time Domain

  • Analysis of HRV in Frequency Domain

  • Analysis of HRV in Nonlinear Domain

  • Instructor Wenxi Chen
    Office: 326C
    Teaching Assistant
    Time and Place Tuesday, Friday 9:00-10:40, S2
    10/13, 10/16, 10/20, 10/23, 10/27, 10/30, 11/4, 11/6, 11/10, 11/13, 11/17, 11/20, 11/24, 11/27
    Schedule Change
    Evaluation Programming tasks and research report
  • ITA25 Biosignal Processing and Data Mining

  • Reference Books
  • Biomedical Signal Processing and Signal Modeling,
    Eugene N. Bruce

  • Biomedical Signal Analysis: A Case-Study Approach,
    Rangaraj M. Rangayyan

  • Practical Biomedical Signal Analysis Using MATLAB,
    Katarzyn J. Blinowska and Jaroslaw Zygierewicz

  • Useful Websites
  • Statistical Data Mining Tutorials,
    Andrew W. Moore

  • Statistical Digital Signal Processing and Modeling,
    Monson H. Hayes

  • A Wavelet Tour of Signal Processing, 2nd Edition,
    Stephane Mallat

  • Created and updated by Wenxi Chen, Oct. 1, 2020