Course Title: Biomedical Signal Analysis

Part A: Course Overview

Course Title: Biomedical Signal Analysis

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

EEET1417

City Campus

Undergraduate

125H Electrical & Computer Engineering

Face-to-Face

Sem 2 2006,
Sem 2 2007,
Sem 2 2009,
Sem 2 2011,
Sem 2 2015,
Sem 2 2016

EEET2494

Bundoora Campus

Undergraduate

172H School of Engineering

Face-to-Face

Sem 2 2017,
Sem 2 2018

Course Coordinator: Dr Beth Jelfs

Course Coordinator Phone: +61 3 9925 1473

Course Coordinator Email: beth.jelfs@rmit.edu.au

Course Coordinator Location: 12.7.16-5


Pre-requisite Courses and Assumed Knowledge and Capabilities

You should have successfully completed the course EEET2369 Signals and Systems, an equivalent course, or provide evidence of equivalent capabilities.


Course Description

In this course you will develop your knowledge of digital signal processing (DSP), building upon the skills acquired in Signals and Systems (EEET2369). This course will introduce you to practical applications of DSP in the analysis of biomedical signals. You will learn about:

  • Different types of biomedical data recordings;
  • Signal acquisition and analog-to-digital conversion;
  • Time domain analysis of discrete signals;
  • Design of digital filters;
  • Frequency domain analysis of discrete signals;
  • Time-frequency analysis of non-stationary signals;
  • Classification of data;
  • How to select and apply these techniques to analyse various biomedical signals measured from the human body.

The theory of related to biomedical signal analysis will be explained during the interactive lectures and tutorial sessions. There will be opportunities for you to apply this knowledge in practical laboratory exercises and group mini-projects and to engage in one-on-one and group discussions. 

 


Objectives/Learning Outcomes/Capability Development

This course contributes to the following Program Learning Outcomes of the Bachelor of Engineering (Honours):

1.1 Comprehensive, theory based understanding of the underpinning natural and physical sciences and the engineering fundamentals applicable to the engineering discipline.

1.2 In-depth understanding of specialist bodies of knowledge within the engineering discipline.

1.3 Discernment of knowledge development and research directions within the engineering discipline.

2.1 Application of established engineering methods to complex engineering problem solving.

2.2 Fluent application of engineering techniques, tools and resources.

3.2 Effective oral and written communication in professional and lay domains.

3.6 Effective team membership and team leadership.

 


On completion of this course you should be able to:

  1. Explain acquisition of biomedical signals and measurements using analog-to-digital conversion, sampling and quantization;
  2. Identify different types of biomedical signals and sources of variability and noise in the data;
  3. Select and manage appropriate choices of digital filtering, and noise reduction as required;
  4. Implement spectral analysis and time-frequency analysis to evaluate biomedical signals;
  5. Apply a range of classification techniques;

 


Overview of Learning Activities

The learning activities in this course include:

  • Lectures designed to introduce you to concepts of biomedical signal processing and analysis.
  • Tutorials which will give you the opportunity to complete worked examples relating to concepts introduced in the lectures.
  • Laboratories designed to give you hands-on experience of the Matlab signal processing tools available. These have been specifically designed to help you understand the theory and applications without the mathematical rigours associated with the tools.
  • Mini-projects which are extensions to the laboratory work undertaken by you. The mini-projects also provide an opportunity for structured learning to aid your understanding of the mathematics and signal processing techniques.


Overview of Learning Resources

All learning resources for this course are available on the university online system accessible via MyRMIT. These resources include:

  • Weekly step by step guidance on how to proceed with your study;
  • Theoretical module including PDF document, explaining various topics and ideas;
  • Tutorial exercises including hand written and Matlab script examples with solutions;
  • Laboratory assignment instructions including written explanations and examples in Matlab;
  • Mini project work to develop your research skills as well as your team and communication skills through written reports and presentations.

 


Overview of Assessment

X  This course has no hurdle requirements.

You will be assessed on your knowledge and skills demonstrated from the following deliverables:

Assessment Task 1: Laboratory (reports)

Weighting 20%

This assessment task supports CLOs 1, 2, 3, 4 & 5.

Assessment Task 2: Mini Project (report and presentation)

Weighting 20%

This assessment task supports CLOs 1, 2, 3, 4, 5 & 6.

Assessment Task 3: Lecture Test (written)

Weighting 10%

This assessment task supports CLOs 1, 2, 3 & 4.

Assessment Task 4: Examination (written)

Weighting 50%

This assessment task supports CLOs 1, 2, 3, 4, 5 & 6.