University of Technology Sydney

42906 Biomedical Signal Processing

6cp; 4hpw, on campus.
Requisite(s): (((48541 Signal Theory OR 48540 Signals and Systems OR 41090 Information and Signals OR 41162 Fundamentals of Biomedical Engineering Studio A OR 41160 Introduction to Biomedical Engineering) AND (120 credit points of completed study in Bachelor's Honours Embedded Degree owned by FEIT OR 120 credit points of completed study in Bachelor's Combined Honours Degree owned by FEIT OR 120 credit points of completed study in Bachelor's Combined Honours Degree co-owned by FEIT)) OR 42721 Introduction to Biomedical Engineering )
These requisites may not apply to students in certain courses. See access conditions.
Recommended studies:

basic knowledge of signal theory and basic skills of Matlab/Labview


Fields of practice: Biomedical Engineering major


Postgraduate

Description

This subject covers the concepts of signal processing and modelling related to biomedical signals and images along with methods of acquisition and classification. Biomedical signals, such as, Electrocardiogram (ECG or EKG), surface Electromyogram (sEMG), human cardiorespiratory signals and body movement signals, are discussed in relation to discrete signal processing algorithms for the analysis and monitoring. For the signal analysis of human body movement (measured by portable inertial sensors), several well-known techniques such as the band-pass FIR filtering and Joint Time-Frequency Analysis (JTFA) (including Short-Term Fourier Transforms and Wavelet) are presented along with techniques for data classification. For the signal analysis of human cardiorespiratory system, K-mean clustering algorithms, Support Vector Machine (SVM), 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 further discussed. Multidimensional filtering design for 2D image processing will also be explored.

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