Biomedical Signal Processing
Biomedical Signal Processing. Instructor: Prof. Sudipta Mukhopadhyay, Department of Electrical and Electronics Communication Engineering, IIT Kharagpur. This course is prepared for the engineering students in their final year of undergraduate studies or in their graduate studies. Electrical Engineering students with a good background in Signals and Systems are prepared to take this course. Students in other engineering disciplines, or in computer science, mathematics, geophysics or physics should also be able to follow this course. While a course in Digital Signal Processing would be useful, it is not necessary for a capable student. The course has followed problem solving approach as engineers are known as problem solvers. The entire course is presented in the form of series of problems and solutions.
(from nptel.ac.in)
Lecture 01  Motivation, Human Body as a System 
Lecture 02  Preliminaries: Building Blocks, Human Cell, Action Potential 
Biomedical Signal Origin and Dynamics 
Lecture 03  Cardiovascular System and Electrocardiogram 
Lecture 04  ECG Lead Configuration, ECG Unipolar Leads, Electroencephalogram 
Lecture 05  EEG Lead Position, Recording Configuration, and Applications 
Lecture 06  Electromyography, Electroneurogram, Event Related Potential, etc. 
Removal of Artifacts 
Lecture 07  Introduction and Statistical Preliminaries 
Lecture 08  Case Studies, Time Domain Filtering: Sync Averaging 
Lecture 09  Time Domain Filtering: Moving Average, Integration Filter, Derivative based Filter 
Lecture 10  Time Domain Filtering: Improved Derivation based Filter, Frequency Domain Filtering 
Lecture 11  Optimal Filtering 
Lecture 12  Optimal Filtering (cont.) 
Lecture 13  Optimal Filtering (cont.) 
Lecture 14  Adaptive Filtering: Need and Basics of Adaptive Filtering 
Lecture 15  Least Mean Square Adaptive Filtering 
Lecture 16  Recursive Least Square Adaptive Filtering 
Lecture 17  Summary of the Artifact Removal Techniques 
Event Detection 
Lecture 18  Example Events 
Lecture 19  QRS Wave Detection: 1st and 2nd Derivative Based Methods 
Lecture 20  QRS Wave Detection: Pan Tompkin Algorithm and Dicrotic Notch Detection 
Lecture 21  Case Study: EEG Signal Description 
Lecture 22  EEG Rhythm Detection: Cross Correlation Coefficient, Cross Spectral Density 
Lecture 23  EEG Rhythm Detection: Match Filter 
Lecture 24  Summary of the Event Detection 
Homomorphic System 
Lecture 25  Multiplicative Homomorphic System 
Lecture 26  Homomorphic Deconvolutions 
Waveform Analysis 
Lecture 27  Case Studies: Changes in ECG Waveform 
Lecture 28  Morphological Analysis of ECG Wave: Correlation Coefficient and Minimum Phase Correspondent 
Lecture 29  Minimum Phase Correspondent and Signal Length (cont.) 
Lecture 30  ECG Waveform Analysis 
Lecture 31  Envelop Extraction and Analysis 
Lecture 32  Analysis of Activity 
Lecture 33  Summary of Waveform Analysis 
Frequency Domain Characterization 
Lecture 34  Motivation, Periodogram 
Lecture 35  Periodogram (cont.) 
Lecture 36  More on Properties of Periodogram 
Lecture 37  Averaged Periodogram, BlackmanTukey Spectral Estimator 
Lecture 38  BlackmanTukey Spectral Estimator (cont.) 
Lecture 39  Daniels Spectral Estimator, Summary of Periodogram 
Modelling of Biomedical Systems 
Lecture 40  Modelling of Biomedical Systems: Motivation 
Lecture 41  Point Process 
Lecture 42  Parametric Model and AR Model Parameters 
Lecture 43  AR Model Parameter Estimation using ACF and Covariance Method 
Lecture 44  Spectral Matching, Modd Order Selection, Relation of AR Model and Cepstral Coefficients 
Lecture 45  Parameter Estimation of ARMA Model 
Lecture 46  Summary of the Chapter on Modelling of Biomedical Systems 
References 
Biomedical Signal Processing
Instructor: Prof. Sudipta Mukhopadhyay, Department of Electrical and Electronics Communication Engineering, IIT Kharagpur. This course introduces the fundamental concepts of biomedical signal processing.
