ES97H-15 Biomedical Signal Processing
ES97H Biomedical Signal Processing
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.
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 Filter types
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
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
- Ramgaraj M. Rangayyan, Biomedical Signal Analysis: A Case-Study Approach. IEEE press 2001
- Eugene N. Bruce, Biomedical Signal Processing and Signal Modeling, John Wiley & Sons, 2000
- 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 for Group project
signal processing and biological signals including pathology
Subject specific skills
Matlab programming. Filter design. Noise reduction. data acquisition.
Team work. presentation and communication skills.
|Lectures||20 sessions of 1 hour (13%)|
|Practical classes||3 sessions of 3 hours (6%)|
|Other activity||4 hours (3%)|
|Private study||117 hours (78%)|
Private study description
Guided independent learning 117 hours
Other activity description
Revision Classes 2x2 hours
No further costs have been identified for this module.
You must pass all assessment components to pass the module.
Assessment group A1
Group presentation of main results of the group project
A combination of qualitative and quantitative short answers
Feedback on assessment
Model solutions to past papers.
Support through office hours.
Written feedback on assignment.
Cohort-level feedback on in-class test
Face to face feedback in laboratories
To take this module, you must have passed:
This module is Core for:
- Year 4 of UESA-H163 MEng Biomedical Systems Engineering
This module is Optional for:
- Year 4 of UESA-H116 MEng Engineering with Exchange Year
- Year 5 of UESA-H115 MEng Engineering with Intercalated Year
- 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 UESA-HH33 MEng Systems Engineering with Exchange Year
- Year 5 of UESA-HH32 MEng Systems Engineering with Intercalated Year
- Year 4 of UCSA-G408 Undergraduate Computer Systems Engineering
- Year 5 of UCSA-G409 Undergraduate Computer Systems Engineering (with Intercalated Year)