This module will provide a review of the fundamental principles of digital signal processing and introduce advanced methods, used and needed in the context of biomedical and healthcare applications.

The module covers the following:

• The Nature of Biomedical Signals and digital applications in healthcare.
  
• Basic concepts (review): Sources of variability (noise); Analogue to digital conversion; Spectral analysis (FFT based) and sampling theory; Digital filters.
  
• Random signals: Stationarity; Correlation; Covariance; Wiener-Khinchin Theorem; Welch’s method.
  
• Time-frequency and wavelet analysis: Short-time Fourier transform; Uncertainty principle; Continuous and discrete wavelet transforms. Applications in data compression.
  
• Multivariate analysis techniques: Principle component analysis; and Independent component analysis. Applications in Compressed sensing and artefact detection and removal.

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