Unit 1 Preliminaries, Biomedical signal origin & dynamics (ECG),

• Biomedical signal origin & dynamics (EEG
• EMG etc.) 3 7

Unit 2 Filtering for Removal of artifacts

4 lecture hours

• Statistical Preliminaries
• Time domain filtering (Synchronized Averaging
• Moving Average)
• Time domain filtering (Moving Average Filter to Integration
• Derivative- based operator)
• Frequency Domain Filtering (Notch Filter)
• Optimal Filtering: The Weiner Filter

Unit 3 Filtering for Removal of artifacts contd

• Optimal Filtering: The Weiner Filter
• Adaptive Filtering Selecting Appropriate Filter 4 9

Unit 4 Event Detection

4 lecture hours

• Example events (viz
• P, QRS and T wave in ECG)
• Derivative based Approaches for QRS Detection Pan Tompkins Algorithm for QRS Detection
• Dicrotic Notch Detection Correlation Analysis of EEG Signal

Unit 5 Waveform Analysis

4 lecture hours

• Illustrations of problem with case studies
• Morphological Analysis of ECG, Correlation coefficient
• The Minimum phase correspondent

Unit 6 Waveform Analysis contd

4 lecture hours

• Signal length
• Envelop Extraction
• Amplitude demodulation
• The Envelogram
• Analysis of activity
• Root Mean Square value
• Zero-crossing rate
• Turns Count
• Form factor

Unit 7 Frequency-domain Analysis

4 lecture hours

• Averaged Periodogram
• Blackman-Tukey Spectral Estimator
• Daniell's Spectral Estimator
• Measures derived from PSD

Unit 8 Modelling of Biomedical Systems

4 lecture hours

• Motor unit firing pattern
• Cardiac rhythm
• Formants and pitch of speech
• Point process
• Parametric system modelling
• Autoregressive model
• Autocorrelation method
• Application to random signals
• Computation of model parameters
• Levinson-Durbin algorithm
• Computation of gain factor
• Covariance method
• Spectral matching and parameterization
• Model order selection
• Relation between AR and Cepstral coefficients

Unit 9 Modeling of Biomedical Systems & Tutorials

4 lecture hours

• ARMA model
• Sequential estimation of poles and zeros
• Tutorial 1.1: Notch filter design
• Tutorial 1.2: Synchronized averaging
• Tutorial 1.3: Design Butterworth low pass filter
• Program Name: Master of Engineering Level: PG Branch: Applied Instrumentation Subject Code : ME02067051 Subject Name : Biomedical Signal Processing

Unit 10 Tutorials

4 lecture hours

• Tutorial 2.1: Design derivative-based filter
• Tutorial 2.2: Design Butterworth high pass filter
• Tutorial 2.3: Design Wiener filter
• Tutorial 3.1: Implement the Pan-Tompkins method for QRS detection

Unit 11 Tutorials

3 lecture hours

• Tutorial 3.2: Use cross-correlation to detect alpha rhythm
• Tutorial 3.3: Design a matched filter
• Tutorial 3.4: Pan-Tompkins method for QRS detection and the Lehner and Rangayyan method to detect dicrotic notch
• Tutorial 4.1: Half wave and full wave rectification
• Tutorial 4.2: RMS value calculation
• Tutorial 4.3: Turns count calculation
• Tutorial 4.4: RMS, Turns count and Zero-crossing rate calculations

Unit 12 Tutorials

3 lecture hours

• Tutorial 4.5: Derive the Envelogram
• Tutorial 4.6: RR interval and Form Factor calculations
• Tutorial 5.1: Power spectrum calculations using different windows
• Tutorial 5.2: Mean frequency and variance of PSD, Tutorial 5.3: Compute PSDs of Voiced
• Unvoiced and Silent portion of sound signal
• Tutorial 5.4: Compute mean frequency of PSDs and ratio of energies
• Tutorial 5.5: Study the changes in the PSDs by varying window width
• number of segments averaged, and type of the window used