BioSignal Processing: Course Outline
Course provides a good foundation of the fundamentals of digital signal processing and its application to biomedical signal processing
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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.
 Upsampling and down sampling.
 Ztransform 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: PanTompkins Algorithm Part I
 QRS Detection: PanTompkins Algorithm Part I
 ECG Rhythm Analysis
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