Bio-Medical Signal Processing detailed syllabus scheme for Electronics Engineering (EL), 2020-21 onwards has been taken from the DBATU official website and presented for the Bachelor of Technology students. For Subject Code, Course Title, Lecutres, Tutorials, Practice, Credits, and other information, do visit full semester subjects post given below.
For 8th Sem Scheme of Electronics Engineering (EL), 2020-21 Onwards, do visit EL 8th Sem Scheme, 2020-21 Onwards. For the Elective-VI scheme of 8th Sem 2020-21 onwards, refer to EL 8th Sem Elective-VI Scheme 2020-21 Onwards. The detail syllabus for bio-medical signal processing is as follows.
Bio-Medical Signal Processing Syllabus for Electronics Engineering (EL) 4th Year 8th Sem 2020-21 DBATU
Course Objectives:
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Course Outcomes:
After successfully completing the course students will be able to:
- The student will be able to model a biomedical system
- The student will be able to understand various methods of acquiring bio signals.
- The student will be able to understand various sources of bio signal distortions and its Remedial techniques
- The students will be able to analyze ECG and EEG signal with characteristic feature points.
- The student will have a basic understanding of diagnosing bio-signals and classifying them.
UNIT – 1 Introduction to Biomedical Signals
ECG, EEG, EMG, ENG etc. Event related potentials Biomedical Signal Analysis- Computer Aided Diagnosis. Concurrent, coupled and correlated processes – illustration with case studies. Noise Filtering: Random noise structured noise and physiological interference- noise and artifacts in ECG.
UNIT – 2 Time domain filters and Frequency domain Filters
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UNIT – 3 Event Detection
Detection of P, QRS and T waves in ECG- EEG rhythms- Correlation and coherence analysis of EEG channels- Detection of EEG spike and wave complexes-Homomorphic filtering. Analysis of event related potential – Morphological analysis of ECG waves- Envelope extraction and analysis- Analysis of activity: zero crossing rates.
UNIT – 4 Fourier Spectrum, Estimation of power spectral density
Moments and spectral power ratio. Power Cepstrum- Complex Cepstrum Biomedical applications of Cepstrum analysis.
UNIT – 5 Modeling of Biomedical systems:
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Unit – 6 Pattern classification and diagnostic decision:
Supervised and unsupervised pattern classification Probabilistic models and statistical decisions- Logistic regression analysis- training and test stepsneural networks- Measures of diagnostic accuracy and cost- Reliability of classifiers and decisions. Application: Normal versus Ectopic ECG beats- Detection of Knee Joint cartilage pathology.
Reference Books:
- Rangaraj M. Rangayyan, Biomedical Signal Analysis: A case study Approach, Wiley Interscience2002.24.
- D. C .Reddy, Biomedical Signal Processing: Principles and techniques, Tata McGrawHill, NewDelhi, 2005.
- Metin Akay, Biomedical Signal Processing, Academic press, Inc.
- Bruce, Biomedical Signal Processing & Signal Modeling, Wiley, 2001.
- Sornmo, Bioelectrical Signal Processing in Cardiac & Neurological Applications, Elsevier.
- Semmlow, Marcel Dekker Biosignal and Biomedical Image Processing, 2004.
- Enderle, Introduction to Biomedical Engineering, 2/e, Elsevier, 2005.
For detail syllabus of all subjects of Electronics Engineering (EL) 8th Sem 2020-21 onwards, visit EL 8th Sem Subjects of 2020-21 Onwards.