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Throughout the 2021-22 academic year, we will be prioritising face to face teaching as part of a blended learning approach that builds on the lessons learned over the course of the Coronavirus pandemic. Teaching will vary between online and on-campus delivery through the year, and you should read guidance from the academic department for details of how this will work for a particular module. You can find out more about the University’s overall response to Coronavirus at: https://warwick.ac.uk/coronavirus.

ES97H-15 Biomedical Signal Processing

Department
School of Engineering
Level
Taught Postgraduate Level
Module leader
Nigel Stocks
Credit value
15
Module duration
10 weeks
Assessment
100% coursework
Study location
University of Warwick main campus, Coventry
Introductory description

ES97H Biomedical Signal Processing

Module web page

Module aims

To introduce students to the principles of signal processing techniques when applied specifically to biomedical signals, including: ECG, MEG, EEG, SPO2, heart rate etc.

The module will provide the student with a firm grounding in methods and tools for extracting information from digitally acquired biomedical signals.

The module will introduce the practical implementation of signal processing techniques to digitally acquired biomedical signals.

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

  • Introduction to Biomedical Signals
    o The Nature of Biomedical Signals
    o Examples of Biomedical Signals
    o Objectives and Difficulties of Biomedical Signal Analysis
  • Revision of pre-requisites
    o Linear Systems Theory (continuous and discrete time)
    o Spectral methods (FT, DTFT, DFT, PSD)
  • Signal Acquisition
    o Measurement systems
    o Sampling theorem
    o Analogue-digital-conversion
    o windowing
  • Filtering
    o Filter types
    o Analogue
    o Digital FIR IIR
  • Random Physiological Signals
    o Signal as a Stochastic Process
    o Averaging techniques
  • Advanced Methods of Biomedical Signal Processing
    o DSP hardware and implementation
    o Medical Devices
Learning outcomes

By the end of the module, students should be able to:

  • Demonstrate a systematic knowledge of the complex physical and physiological principles that underpin biomedical signals.
  • Demonstrate an advanced understanding of the principles of digital signal processing.
  • Systematically apply methods to extract relevant information from biomedical signal measurements.
  • Critically assess the appropriateness of biomedical signal processing techniques for various problems in the field.
  • Evaluate the effectiveness of techniques applied to biomedical signals against specific benchmarks.
Indicative reading list
  1. Ramgaraj M. Rangayyan, Biomedical Signal Analysis: A Case-Study Approach. IEEE press 2001
  2. Eugene N. Bruce, Biomedical Signal Processing and Signal Modeling, John Wiley & Sons, 2000
  3. A V Oppenheim & R W Schafer, Discrete-time Digital Signal Processing, 2009, ISBN-13: 978-0131988422 ISBN-10: 0131988425 Edition: 3rd, Prentice-Hall: Englewood Cliffs, NJ
Research element

Research for Group project

Interdisciplinary

signal processing and biological signals including pathology

Subject specific skills

Matlab programming. Filter design. Noise reduction. data acquisition.

Transferable skills

Team work. presentation and communication skills.

Study time

Type Required
Lectures 20 sessions of 1 hour (8%)
Practical classes 3 sessions of 3 hours (4%)
Other activity 4 hours (2%)
Private study 117 hours (49%)
Assessment 90 hours (38%)
Total 240 hours
Private study description

Guided independent learning 117 hours

Other activity description

Revision Classes 2x2 hours

Costs

No further costs have been identified for this module.

You must pass all assessment components to pass the module.

Assessment group A
Weighting Study time
Group presentation 30%

Group presentation of main results of the group project

Signal processing test 50% 60 hours

A combination of qualitative short answers and qualitative multiple choice questions to

Worksheet based on Laboratory Classes 20% 30 hours

Coursework

Feedback on assessment

Model solutions to past papers.
Support through office hours.
Written feedback on assignment.
Cohort-level feedback on assignment
Cohort-level feedback on final exam.
Face to face feedback in laboratories

Pre-requisites

ES3C5

Courses

This module is Core for:

  • Year 4 of UESA-H163 MEng Biomedical Systems Engineering

This module is Optional for:

  • Year 1 of TESA-H800 Postgraduate Taught Biomedical Engineering

This module is Option list A for:

  • Year 4 of UESA-H114 MEng Engineering

This module is Option list B for:

  • Year 4 of UESA-HH31 MEng Systems Engineering
  • Year 4 of UCSA-G408 Undergraduate Computer Systems Engineering