University of Technology, Sydney

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42906 Biomedical Signal Processing

6cp; 4hpw
Requisite(s): (48541 Signal Theory OR 48540 Signals and Systems OR 41090 Information and Signals) AND (120 credit points of completed study in spk(s): C10061 Bachelor of Engineering Diploma Engineering Practice OR 120 credit points of completed study in spk(s): C10067 Bachelor of Engineering OR 120 credit points of completed study in spk(s): C10066 Bachelor of Engineering Science OR 120 credit points of completed study in spk(s): C09067 Bachelor of Engineering (Honours) Diploma Professional Engineering Practice OR 120 credit points of completed study in spk(s): C09066 Bachelor of Engineering (Honours))
These requisites may not apply to students in certain courses. See access conditions.
Recommended studies:

Basic knowledge about signal theory and basic skills of Matlab/Labview.


Field of practice: Biomedical Engineering major


Postgraduate

Description

This subject covers the concept of signal processing and modelling related to biomedical signals and images along with methods of acquisition and classification. Basics of some commonly encountered biomedical signals, such as human cardiorespiratory signals and body movement signals, are discussed along with discrete signal processing algorithms for the analysis and monitoring. For the analysis of human body movement signals (measured by portable inertial sensors), some well-known techniques such as the band pass digital filtering and the Joint Time-Frequency Analysis (JTFA) (including Short-Term Fourier Transforms and Wavelet) are included along with techniques for data classification. For the analysis of human cardiorespiratory signals, the K-mean clustering algorithms, Support Vector Machine, and most commonly used dynamic modelling approaches are also covered. Both stationary and non-stationary signal processing techniques for the analysis, detection and estimation of various cardiorespiratory signals are included. Multidimensional filtering design for 2D image processing is discussed.

Most of the discussed data processing techniques are demonstrated by using MATLAB simulation, tested in Labview environment, and implemented by using microcontroller and specialised devices.

Typical availability

Autumn session, City campus


Detailed subject description.

Access conditions

Note: The requisite information presented in this subject description covers only academic requisites. Full details of all enforced rules, covering both academic and admission requisites, are available at access conditions and My Student Admin.