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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.
  • 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