Skip to main content
It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.

Bio-Signal Processing: Course Outline

Course provides a good foundation of the fundamentals of digital signal processing and its application to biomedical signal processing

Course Contents

  • Review of signals and systems and their properties.
  • Modeling of Dynamic Systems.
  • Linear Constant Coefficients Differential Equation (LCCDE) and Difference Equation.
  • Review of Laplace transform.
  • Transfer Function.
  • Poles and Zeros.
  • Sampling and Reconstruction.
  • Up-sampling and down sampling.
  • Z-transform and its application in the analysis of Discrete LTI system.
  • computation of frequency response from Pole.
  • Zero plot.
  • Review of the Frequency domain analysis of Continuous time systems.
  • CTFS, CTFT, DTFT, DFT (DTFS), FFT.
  • Design and implementation of analog and digital finite impulse response (FIR) and infinite impulse respons (IIR) filters.
  • A quick introduction to statistical signal processing.
  • feature extraction and pattern recognition techniques.
  • Case Studies of various Biomedical Signals: ECG, EEG

Lab Outline

  • Introduction to MATLAB Signal Processing Tool Box
  • Signal generation, convolution, impulse response
  • Up- Down- Sampling
  • Spectral Leakage and Zero Padding
  • Introduction to Simulink
  • Sampling and Reconstruction through Simulink
  • Frequency Response of Discrete Time Systems
  • Implementation of FFT DIT algorithm in MATKAB
  • Design and Implementation of LP, HP filter
  • Design and Implementation of BP filters
  • Data classification
  • ECG acquisition and introduction MIT/BIH arrhythmia database
  • QRS Detection: Pan-Tompkins Algorithm Part I
  • QRS Detection: Pan-Tompkins Algorithm Part I
  • ECG Rhythm Analysis