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504204 ELECTIVE III
BIOMEDICAL SIGNALS AND SYSTEMS
Teaching Scheme Examination Scheme
Lectures: 3 Hrs./Week Theory: 100 Marks
Credit: 3
Introduction to Biomedical Signals,Nature of Biomedical Signals, Examples of Biomedical
Signals –EMG, ECG, EEG, ERPs,PCG,VMG, VAG, Objectives of Biomedical Signal Analysis,
Difficulties in Biomedical Signal Analysis, Concurrent, Coupled, and Correlated Processes-
Illustration of the Problem with Case-Studies. Filtering for Removal of Artifacts- Illustration of the
Problem with Case-Studies,Time-Domain Filters, Frequency-Domain Filters, Optimal Filtering, The
Wiener Filter, Adaptive Filters for Removal of Interference, Selecting an Appropriate Filter
Application: Removal of Artifacts in the ECG, Event Detection, Detection of Events and Waves,
Correlation Analysis of EEG channels, Cross-spectral Techniques. The Matched Filter, Detection of
the P Wave, Homomorphic Filtering, Application- ECG Rhythm Analysis, Identification of Heart
Sounds, Waveshape and waveform Complexity, Analysis of Event-related Potentials, Morphological
Analysis of ECG Waves, Envelope Extraction and Analysis of Activity, Application- Normal and
Ectopic ECG Beats, Analysis of Exercise ECG. Frequency-domain Characterization The Fourier
Spectrum, Estimation of the Power Spectral Density Function, Measures Derived form PSDs.
Modeling Biomedical Systems, Point Processes Parametric System Modeling Autoregressive of Allpole
Modeling, Pole-Zero Modeling, Electromechanical Models of Signal Generation, Application-
Heart-rate Variability, Spectral Modeling and Analysis of PCG. Analysis of Nonstationary Signals,
Time-Variant Systems, Fixed Segmentation, Adaptive Segmentation, Use of Adaptive Filters for
Segmentation, Application- Adaptive Segmentation of EEG Signals, Adaptive Segmentation of PCG
Signals. Pattern Classification and Diagnostic Decision , Pattern Classification, Supervised Pattern
Classification, Unsupervised Pattern Classification, Probabilistic Models and Statistical Decision ,
Logistic regression Analysis The Training and Test Steps, Neural Networks, Measures of Diagnostic
Accuracy and Cost, Reliability of Classifier and Decisions
References
1. R. M. Rangayyan “Biomedical Signal Analysis- A case study approach”, Wiley Publications.
2. Eugene N Bruce, “Biomedical signal processing and signal modeling”, Wiley publications.
For more details, visit http://www.unipune.ernet.in/stud_info/Syllabi/Syllabus_2008.html
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