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Course Detail

Learning Objectives

  • LO1: To enhance practical knowledge in biomedical signal analysis
  • LO2: To provide hands-on experience in filtering of biomedical signals

Course Outcomes

  • CO1: An ability to y to apply algorithms for signal processing
  • CO2: Ability to analyse biomedical signals and systems
  • CO3: Ability to evaluate biomedical signal acquisition and processing systems

Course Contents

  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

References

  1. Subasi, A., Practical guide for biomedical signals analysis using machine learning techniques: A MATLAB based approach. Academic Press, 2019.
  2. Blinowska, Katarzyn J., and Jaroslaw Zygierewicz. Practical biomedical signal analysis using MATLAB®. CRC Press, 2011.

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