Physiological Signals
One Semester
Hawthorn
Available to incoming Study Abroad and Exchange students
Overview
This unit provides students with an understanding of the biophysical origin of the major electrophysiological signals that can be non-invasively recorded together with the standard methods and approaches for i) their recording and storage and ii) their time and frequency domain analysis
Requisites
Prerequisites
MBP10001
Technology and Data AcquisitionRules
150 Credit Points
AND
MBP10001 Technology and Data Acquisition
Teaching periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Semester 1
Location
Hawthorn
Start and end dates
03-March-2025
01-June-2025
01-June-2025
Last self-enrolment date
16-March-2025
Census date
31-March-2025
Last withdraw without fail date
24-April-2025
Results released date
08-July-2025
Learning outcomes
Students who successfully complete this unit will be able to:
- Accurately record physiological signals
- Critically analyse physiological signals
- Plan and use MATLAB tools to deal with physiological signals
- Identify and quantify key features in signals of diagnostic and biological importance
- Synthesise and report on the key features of the signals
Teaching methods
Hawthorn
Type | Hours per week | Number of weeks | Total (number of hours) |
---|---|---|---|
Face to Face Contact (Phasing out) Lecture | 3.00 | 12 weeks | 36 |
Face to Face Contact (Phasing out) Tutorial Labs | 2.00 | 6 weeks | 12 |
Specified Learning Activities (Phasing out) Various | 4.00 | 6 weeks | 24 |
Unspecified Learning Activities (Phasing out) Independent Learning | 6.50 | 12 weeks | 78 |
TOTAL | 150 |
Assessment
Type | Task | Weighting | ULO's |
---|---|---|---|
Assignment | Individual | 20% | 2,4,5 |
Examination | Individual | 60% | 2,4 |
Laboratory Report | Individual | 20% | 1,2,3,4,5 |
Content
- Biophysical origin of ECG/MCG, EEG/MEG, EOG and EMG
- General signal properties: stationarity, ergodicity, noise
- Data recording: Nyquist sampling theorem, signal bandwidth, ADC
- Signal Analysis: FFT and power spectral analysis, high, low and bandpass filtering, ICA, parametric time series analysis, filter bank, basic wavelet analysis, signal averaging
- MATLAB/SIMULINK programming methods
Study resources
Reading materials
A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.