Course Title: Biomedical Signal Analysis and Image Processing

Part A: Course Overview

Course Title: Biomedical Signal Analysis and Image Processing

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

EEET1417

City Campus

Undergraduate

172H School of Engineering

Face-to-Face

 Sem 2 2025

EEET2494

Bundoora Campus

Undergraduate

172H School of Engineering

Face-to-Face

 Sem 2 2017,
Sem 2 2018,
Sem 2 2019,
Sem 2 2020,
Sem 2 2021,
Sem 2 2022,
Sem 2 2023,
Sem 2 2024

Course Coordinator: Dr Shaun Cloherty

Course Coordinator Phone: +61 3 9925 0424

Course Coordinator Email: shaun.cloherty@rmit.edu.au

Course Coordinator Location: 012.08.017

Course Coordinator Availability: By appointment


Pre-requisite Courses and Assumed Knowledge and Capabilities

Recommended Prior Study

You should have satisfactorily completed or received credit for the following course/s before you commence this course:

• EEET2369 Signals and Systems

If you have completed prior studies at RMIT or another institution that developed the skills and knowledge covered in the above course/s you may be eligible to apply for credit transfer.

Alternatively, if you have prior relevant work experience that developed the skills and knowledge covered in the above course/s you may be eligible for recognition of prior learning.

Please follow the link for further information on how to apply for credit for prior study or experience.


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 and images. You will learn about:

  • Different types of biomedical signals and imaging techniques;
  • Biomedical signal and image acquisition;
  • 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 signals and images;
  • How to select and apply these techniques to analyse various biomedical signals.

The theory related to biomedical signal analysis will be presented through a series of lectures and lectorial sessions. You will apply this knowledge in a series of practical laboratory exercises and a group project.

If you are enrolled in this course as a component of your Bachelor Honours Program, your overall mark will contribute to the calculation of the Weighted Average Mark (WAM).

See the WAM information web page for more information.


Objectives/Learning Outcomes/Capability Development

This course contributes to the program learning outcomes for the following program(s):

BH069P23 Bachelor of Engineering (Biomedical Engineering) (Honours)

PLO 1. Demonstrate a coherent and advanced understanding of scientific theories, principles and concepts and engineering fundamentals within the engineering discipline​
PLO 2. Demonstrate a coherent and advanced body of knowledge within the engineering discipline
PLO 4. Apply knowledge of established engineering methods to the solution of complex problems in the engineering discipline
PLO 5. Utilise mathematics, software, tools and techniques, referencing appropriate engineering standards and codes of practice, in the design of complex engineering systems
PLO 8. Communicate engineering designs and solutions respectfully and effectively, employing a range of advanced communication methods, in an individual or team environment, to diverse audiences.​​
PLO 10. Critically analyse, evaluate, and transform information, while exercising professional judgement, in an engineering context.

For more information on the program learning outcomes for your program, please see the program guide.


Upon successful completion of this course, you will be able to:

CLO1. Demonstrate a coherent and advanced understanding of the principles and concepts of signal and image processing in biomedical contexts.

CLO2. Design and implement signal and image processing algorithms and workflows tailored to biomedical applications.

CLO3. Critically evaluate the effectiveness, limitations and implications of signal and image processing methods in biomedical applications.

CLO4. Apply fundamental and advanced principles of biomedical signal and image processing to solve biomedical engineering problems.

CLO5. Synthesise knowledge of signal and image processing techniques to design, implement and verify signal and image processing solutions in individual and team projects.

CLO6. Effectively communicate complex technical concepts, design decisions, and engineering solutions to diverse engineering audiences using professional oral and written formats.


Overview of Learning Activities

Student learning occurs through the following experiences and evaluation processes:

  • Recorded lectures where syllabus material will be presented and explained, and the subject will be illustrated with demonstrations and examples.
  • Completion of tutorial questions and laboratory projects which provide an introduction to software tools for design, simulation and evaluation of signal and image processing systems, and are designed to give further practice in practical application of the course material and provide feedback on student progress and understanding.
  • Self-directed private study and problem-based learning, working through the course material as presented in class and learning materials, and gaining practice at solving conceptual and numerical problems.

Feedback will be provided throughout the semester in class and/or online discussions, through individual and group feedback on practical exercises and by individual consultation.


Overview of Learning Resources

You will be expected to use library and electronic resources (as well as any other appropriate resources) to engage in professional reading and private study of relevant material on biomedical signal and image processing.

The learning resources for this course include:

  • Lecture material prepared by teaching staff.
  • Recommended textbook and references as listed in the Course Guide Part B and the RMIT online teaching platform.
  • You will be expected to have access to suitable computing equipment for design and evaluation of signal and image processing systems. Required software (MATLAB) is freely available to RMIT students.


Overview of Assessment

Assessment 1: Laboratory Tasks, 40%, CLO1, CLO2, CLO3, CLO4, CLO5 and CLO6
Assessment 2: Laboratory Project, 30%, CLO1, CLO2, CLO3, CLO4, CLO5 and CLO6
Assessment 3: Lectorial Quizzes, 10%, CLO1, CLO2, CLO3
Assessment 4: Final timed assessment, 20%, CLO1, CLO2, CLO3

If you have a long-term medical condition and/or disability it may be possible to negotiate to vary aspects of the learning or assessment methods. You can contact the program coordinator or Equitable Learning Services if you would like to find out more.