Back close

Course Detail

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

Course Contents

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

Textbooks

  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.

DISCLAIMER: The appearance of external links on this web site does not constitute endorsement by the School of Biotechnology/Amrita Vishwa Vidyapeetham or the information, products or services contained therein. For other than authorized activities, the Amrita Vishwa Vidyapeetham does not exercise any editorial control over the information you may find at these locations. These links are provided consistent with the stated purpose of this web site.

Admissions Apply Now