Course

Syllabus

Brief introduction to biomedical signals – Challenges in biomedical signal acquisition and analysis – Need for Computer Aided Diagnosis (CAD) 

Sampling and reconstruction – Types of noise – Random noise – Structured noise – Physiological interference – Linear time-invariant filters – Time domain filters – Synchronized averaging – Moving average filters – Derivative based filters. 

Transform domain analysis of signals and systems – Discrete Fourier Transform (DFT) and its properties – Pole-zero plot – Time-frequency analysis – Short-Time Fourier Transform (STFT) – Wavelet Transform 

Filter design – Butterworth filters – Notch and comb filters – Event detection – Analysis of waveshape and waveform complexity – Morphological analysis – Envelope extraction and analysis – Feature extraction – Receiver operating characteristics – Case studies – Removal of artifacts – QRS Detection and classification of ectopic beats in ECG signals – Detection of epileptic seizures in EEG signals – Study of muscular contraction using parametric analysis of EMG signals. 

Laboratory module will involve hands-on experiments on 

1. Digital signal processing – Basic operations 
2. Time domain filtering 
3. Discrete Fourier Transform (DFT) 
4. Frequency domain filtering 
5. Artifact removal in bio-signals 
6. Waveform analysis and feature extraction from bio-signals 
7. Pattern classification in bio-signals Recommended Tools: MATLAB, Python 

Learning Objectives 

LO1 To introduce characteristics of biomedical signals. 

LO2 To provide understanding of artifact removal in biomedical signals. 

LO3 To enhance knowledge in event detection and waveform analysis of biomedical signals. LO4 To provide insight on pattern classification in biomedical signals. 

Course Outcomes 

CO1 Ability to understand concepts of signal processing. CO2 Ability to apply algorithms for signal processing. 

CO3 Ability to analyse biomedical signals and systems. 

CO4 Ability to evaluate biomedical signal processing systems.

1. Rangayyan, Rangaraj M, Biomedical signal analysis, John Wiley & Sons, 2015 
2. Subasi, Abdulhamit. Biomedical signal analysis and its usage in healthcare in Biomedical Engineering and its Applications in Healthcare, pp. 423-452. Springer, 2019. 
3. Devasahayam, S.R., Signals and systems in biomedical engineering: signal processing and physiological systems modeling. Springer Science & Business Media, 2014. 
4. Haykin, Simon, and Barry Van Veen, Signals and systems, John Wiley & Sons, 2007 
5. John G.Proakis and DimitusG.Manolakis, “Digital Signal Processing, Principles, Algorithms and Applications”, Third Edition, Prentice Hall of India, 2002. 
6. Subasi, A., Practical guide for biomedical signals analysis using machine learning techniques: A MATLAB based approach. Academic Press, 2019. 
7. Blinowska, Katarzyn J., and Jaroslaw Zygierewicz. Practical biomedical signal analysis using MATLAB. CRC Press, 2011.