Diagnosis and Self-Regulation Algorithms

Recommended Prerequisites

NA

Teaching Methods

The lectures will be mainly for discussing subjects with the students and problem-solving for theory application (with support from medical doctors). In the laboratory classes, students will develop computer applications for diagnostics and self-regulation, enhancing their self-learning and quest for knowledge skills.

Learning Outcomes

To know how to use the main quantitative algorithms used in the diagnosis of most common physiological systems (cardiovascular, respiratory, digestive, urinary tract, etc.).
Advanced treatment of physiological signals to extract their characteristics in temporal and frequency domains.
Theoretical analysis of homeostatic and self-regulation functions of human physiological systems. Design regulation systems for prostheses and clinical and hospital equipment.

Work Placement(s)

No

Syllabus

Ch. 1 Independent Component Analysis (ICA): Fundamentals, independence estimation, Fast ICA, medical uses.

Ch. 2 Fourier Transform, Windowing and Filters: Fourier transform, windowing, FIR and IIR filters, s-plane projection and discretization, medical uses.

Ch. 3 Wavelet Transform: Fourier limitations, continuous and discrete wavelet transforms, medical uses.

Ch. 4 Dimensionality Reduction: PCA and medical uses, Multidimensional Scaling (metric, classical, non-metric, visualization).

Ch. 5 Clustering: Introduction, clustering types, agglomerative and partition methods, medical uses.

Ch. 6 Recursive Identification: Dynamic systems, difference equations, transfer functions, stability, system discretization, ARX/ARMAX.

Ch. 7 Digital Control: Control basics, closed-loop specs, prototype and deadbeat controllers, pole-zero cancellation, PID, adaptive control.

Ch. 8 State Feedback and Optimal Control: State equation discretization, Z-transform, state feedback, optimal control, Riccati.

Head Lecturer(s)

Lorena Itatí Petrella

Assessment Methods

Assessment
Research work: 10.0%
Laboratory work or Field work: 20.0%
Synthesis work: 20.0%
Exam: 50.0%

Bibliography

The Medical Algorithms Project 2025, www.medal.org.

Time-Frequency and Wavelets in Biomedical Engineering,Metin Akay (Ed), 1997, Wiley-IEEE Press Series on Biomedical Engineering.

Wavelets in Medicine and Biology, Akram Aldroubi and Michael Unser, Eds., CRC Press, Boca Raton, FL, 1996.

Biomedical Signal Processing and Signal Modelling, E. N. Bruce, Wiley 2001.

Identification of Nonlinear Physiological Systems, Westwick e Kearney, IEEE Press Series Biom Eng 2003.

Physiological Control Systems, Analysis, Simulation and Estimation. Khoo, IEEE Press Series Biomed Eng 2000.