BIOMEDICAL SIGNAL PROCESSING (18EC825)

BIOMEDICAL SIGNAL PROCESSING

Course Code : 18EC825
CIE Marks :40
Lecture Hours/Week : 03 
SEE Marks : 60
Total Number of Lecture Hours : 40 (8 Hrs /Module) 
Exam Hours :03
CREDITS — 03

Course Learning Objectives:

This course will enable students to:
Describe the origin, properties and suitable models of important biological signals such as ECG and EEG.
Know the basic signal processing techniques in analysing biological signals.
Acquire mathematical and computational skills relevant to the field of biomedical signal processing.
Describe the basics of ECG signal compression algorithms.
Know the complexity of various biological phenomena.
Understand the promises, challenges of the biomedical engineering.

Module -1

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 (Text-1) L1,L2

Module -2

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-Hz adaptive cancelling using a sine wave model, other applications of adaptive filtering (Text-1) L1,L2,L3

Module -3

Data Compression Techniques: Turning point algorithm, AZTEC algorithm, Fan algorithm, Hufiinan coding, data reduction algorithms The Fourier transform, Correlation, Convolution, Power spectrum estimation, Frequency domain analysis of the ECG (Text-1) L1,L2, L3

Module -4

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 ECG processing algorithm, ECG interpretation, ST segment analyzer, Portable arrhythmia monitor. (Text -2) L1,L2, L3

Module -5

Neurological signal processing: The brain and its potentials, The electrophysiological origin ofbrain waves, The EEG signal and its characteristics (EEG rhythms, waves, and transients), Correlation. Analysis of EEG channels: Detection of EEG rhythms, Template matching for EEG, spike and wave detection (Text-2) L1,L2, L3

Course Outcomes: At the end of the course, students will be able to:

l. Possess the basic mathematical, scientific and computational skills necessary to analyse ECG and EEG signals.
2. Apply classical and modern filtering and compression techniques for ECG and EEG signals.
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 to process and analyze biomedical signals for better diagnosis.

Question paper pattern:

Examination will be conducted for 100 marks with question paper containing 10 filll questions, each of 20 marks.
Each filll question can have a maximum of 4 sub questions.
There will be 2 fiill questions from each module covering all the topics of the module.
Students will have to answer 5 fiill 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 Digital Signal Processing- Willis J. Tompkins, PHI 2001.
2. Biomedical Signal Processing Principles and Techniques— D C Reddy, McGraw— Hill publications 2005.

Reference Book:

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