AP4009 Biomedical Signal Processing Syllabus:
AP4009 Biomedical Signal Processing Syllabus – Anna University PG Syllabus Regulation 2021
COURSE OBJECTIVES:
Describe the properties and suitable models of biomedical signals
Introduce the basic signal processing techniques in analyzing biomedical signals
Develop computational skills in filtering of biomedical signals
Develop an understanding on ECG signal compression algorithms
Develop an understanding on feature extraction of biomedical signals
UNIT I INTRODUCTION TO BIOMEDICAL SIGNALS
Introduction to Biomedical Signals: The nature of Biomedical Signals, Examples of Biomedical Signals, Objectives and difficulties in Biomedical analysis. Electrocardiography: Basic electrocardiography, ECG lead systems, ECG signal characteristics. Signal Conversion :Simple signal conversion systems, Conversion requirements for biomedical signals, Signal conversion circuits
UNIT II SIGNAL AVERAGING
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
UNIT III DATA COMPRESSION TECHNIQUES
Data Compression Techniques: Turning point algorithm, AZTEC algorithm, Fan algorithm, Huffman coding, data reduction algorithms The Fourier transform, Correlation, Convolution, Power spectrum estimation, Frequency domain analysis of the ECG
UNIT IV CARDIOLOGICAL SIGNAL PROCESSING
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, Realtime ECG processing algorithm, ECG interpretation, ST segment analyzer, Portable arrhythmia monitor
UNIT V NEUROLOGICAL SIGNAL PROCESSING
Neurological signal processing: The brain and its potentials, The electrophysiological origin of brain 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
TOTAL : 45 PERIODS
COURSE OUTCOMES:
At the end of this course the student will be able to
CO1: Possess skills necessary to analyze ECG and EEG Signals
CO2: Apply classical and modern filtering techniques for ECG and EEG Signals
CO3: Apply classical and modern compression techniques for ECG and EEG Signals
CO4: Develop an understanding on ECG feature extraction
CO5: Develop an understanding on EEG feature extraction
REFERENCES
1. Rangaraj M Rangayyan “Biomedical Signal Analysis – A case study approach” IEEE press series in biomedical engineering, First Edition, 2002
2. John G Proakis, Dimitris and G. Manolakis, “Digital Signal Processing Principles algorithms, applications” PHI Third Edition. 2006
3. Willis J. Tompkins “ Biomedical Digital Signal Processing”, EEE, PHI, 2004
4. D C Reddy “Biomedical Signal Processing: Principles and Techniques”, Tata McGraw-Hill Publishing Co. Ltd, 2005
5. J G Webster “Medical Instrumentation: Application & Design”, John Wiley & Sons Inc., 2001