18EC825 Biomedical Signal Processing syllabus for EC

Introduction to Biomedical Signals:

The nature of Biomedical Signals, Examples of Biomedical Signals, Objectives and difficulties in Biomedical analysis.

Electrocardiography:

Basic electrocardiography, ECG leads systems, ECG signal characteristics.

Signal Conversion :

Simple signal conversion systems, Conversion requirements for biomedical signals, Signal conversion circuits

Signal Averaging:

Basics of signal averaging, signal averaging as a digital filter, a typical averager, software for signal averaging, limitations of signal averaging.

Adaptive Noise Cancelling:

Principal noise canceller model, 60-Hzadaptive cancelling using a sinewave model, other applications of adaptive filtering

Data Compression Techniques:

Turning point algorithm, AZTEC algorithm, Fan algorithm, Huffinancoding, data reduction algorithms The Fourier transform, Correlation, Convolution, Power spectrum estimation, Frequency domain analysis ofthe ECG

Cardiological signal processing:

Basic Electrocardiography, ECG data acquisition, ECG lead system, ECG signal characteristics (parameters and their estimation), Analog filters, ECG amplifier, and QRS detector, Power spectrum of the ECG, Bandpass filtering techniques, Differentiation techniques, Template matching techniques, A QRS detection algorithm, Real-time ECGprocessing algorithm, ECGinterpretation, STsegment analyzer, Portable arrhythmia monitor.

Neurological signal processing:

The brain and its potentials, The electrophysiological origin ofbrain waves, The EEG signal andits characteristics (EEG rhythms, waves, andtransients),Correlation.

Analysis of EEG channels:

Detection of EEG rhythms, Template matching for EEG, spike and wave detection

Course Outcomes:

At the end of the course, students will beable to:

1.Psess the basicmathematical, scientific and computational skills necessary to analyse ECG and EEG signals.

2. Apply classical and modern filtering and compression techniques for ECGand EEGsignals.

3. Develop a thorough understanding on basics of ECG and EEG feature extraction.

4. Evaluate various event detection techniques for the analysis of the EEG and ECG

5. Develop algorithms toprocess and analyze biomedical signals for better diagnosis.

Question paper pattern:

• Examination will be conducted for 100 marks with question paper containing 10 full questions, each of 20 marks.
• Each full question can have a maximum of 4 sub questions.
• There will be 2 full questions from eachmodule covering all the topics of the module.
• Students will have to answer 5 full questions, selecting one full question from each module.
• The total marks will be proportionally reduced to 60 marks as SEE marks is 60.

Text Books:

1. Biomedical DigitalSignal Processing- Willis I.Tompkins, PIIl 2001.

2. Biomedical Signal Processing Principles and Techniques- D CReddy, McGraw- Hill publications 2005.

Reference Book:

• Biomedical Signal Analysis-Rangaraj M. Rangayyan, John Wiley & Sons 2002.