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EEEN30160

Academic Year 2024/2025

Biomedical Signal Processing (EEEN30160)

Subject:
Electronic & Electrical Eng
College:
Engineering & Architecture
School:
Electrical & Electronic Eng
Level:
3 (Degree)
Credits:
5
Module Coordinator:
Dr Elaine Corbett
Trimester:
Autumn
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

An understanding of biomedical signal processing is at the core of many widely used diagnostic and therapeutic biomedical devices such as ECGs, pacemakers, cochlear implants, ventilatory support systems, etc. In this module, students will learn how biomedical signals are represented in digital format, and how they can be digitally processed through mathematical techniques in order to extract useful information for understanding physiological systems and/or diagnosis. Fundamental processing tools ranging from signal averaging to filtering and frequency-domain analysis will be covered.
Students will learn these principles and techniques through an even mixture of lectures and computer lab exercises in Matlab, and will carry out a short software-based research project to process a biomedical signal.

About this Module

Learning Outcomes:

On successful completion of this subject the student will be able to:
• Explain basic principles of how an analog sensor signal can be converted reliably to a digital format for processing
• Translate signal representations between the time and frequency domains
• Design and implement digital filters and use them to remove noise or improve signal detection
• Describe and know how to address the core challenges in biomedical signal analysis, such as the interference of noise and artifacts in the signals
• Perform basic feature extraction and pattern classification for diagnostic applications

Indicative Module Content:

- Basics of Biomedical signal processing
- Fourier Transform
- Sampling
- Linear systems
- Z-transform
- Digital Filters design
- De-noising signals and signal manipulation
- Feature extraction from biomedical signals
- Introduction to classification and machine learning
-Introduction to biomedical image processing
- Matlab programming

Student Effort Hours:
Student Effort Type Hours
Lectures

23
Computer Aided Lab

20
Autonomous Student Learning

60
Total

103

Approaches to Teaching and Learning:
The module will be made up of Lectures, labs and a final project.
The lectures will be delivered in person twice weekly. There will be biweekly lab assignments. Lab time will be face to face, with no mandatory attendance. During the labs, students will work on their assignments and will have the chance to ask questions to the Lecturer and the TAs.

Requirements, Exclusions and Recommendations
Learning Requirements:

Sufficient mathematics background to be comfortable with integral calculus, probability theory, and basic linear algebra


Module Requisites and Incompatibles
Not applicable to this module.
 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Assignment(Including Essay): 4 MATLAB Assignments and Reports Week 2, Week 3, Week 4, Week 5, Week 6, Week 7, Week 8, Week 9 Alternative linear conversion grade scale 40% No
30
 No
Individual Project: MATLAB-based project and report, due at the end of exam period. Week 10, Week 11, Week 12, Week 14, Week 15 Alternative linear conversion grade scale 40% No
20
 No
Exam (In-person): Final Exam End of trimester
Duration:
2 hr(s)
 Alternative linear conversion grade scale 40% No
50
 No

Carry forward of passed components
No
 

Resit In Terminal Exam
Spring Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Autumn Computer Aided Lab Offering 1 Week(s) - Autumn: All Weeks Fri 13:00 - 14:50
Autumn Lecture Offering 1 Week(s) - 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12 Mon 14:00 - 14:50
Autumn Lecture Offering 1 Week(s) - Autumn: All Weeks Thurs 11:00 - 11:50
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