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 Acquisition

Rules

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
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
TOTAL150

Assessment

Type Task Weighting ULO's
AssignmentIndividual 20% 2,4,5 
ExaminationIndividual 60% 2,4 
Laboratory ReportIndividual 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.