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Biomedical Signal Analysis

Course description

8 cu

Brief outline:

Introduction to the electrocardiogram, electroencephalogram, electromyogram, and other diagnostic signals. Computer techniques for processing and analysis of biomedical signals. Pattern classification and decision techniques for computer-aided diagnosis. Case studies from current applications and research.


A course on Signals, Linear Systems, and Transforms (Laplace, Fourier, and z transforms).


  • Learn about the genesis of biomedical signals, such as the action potential, EMG, ECG, EEG, and heart sound signals.
  • Review basic concepts of signals, systems, and digital filters.
  • Study the characteristics of biomedical signals: stationarity, periodicity, rhythm, wavelets, epochs, episodes, transients.
  • Learn signal processing techniques for filtering, noise removal, cancellation of interference, and characterization of signals.
  • Study techniques for the detection of events such as the QRS complex, heart sounds and murmurs, and the dicrotic notch.
  • Learn about spectral analysis of biomedical signals.

Background review and preparation:

You are advised to review a textbook on signals, linear systems, and transforms, such as Lathi BP, "Signal Processing and Linear Systems", Berkeley-Cambridge, Carmichael, CA, 1998; or Oppenheim AV, Willsky AS, and Nawab SH, "Signals and Systems", Prentice Hall, Englewood Cliffs, NJ, 2nd edition, 1997. You are also advised to familiarize yourself with MATLAB and the associated Signal Processing Toolbox.