Algorithms for the Analysis and Diagnosis in pHealth

Recommended Prerequisites

1. Basic knowledge of algebra and calculus

2. Basic knowledge of signal processing (Z-transform, Fourier)

3. Basic knowledge of programming (preferably using MatLab)

Teaching Methods

Theoretical lessons (2 hours/week)

Lectures about theoretical concepts, principles and fundamental techniques.

Examples that epitomize the practical relevance of the subject and exemplify its application in real situations.

Learning Outcomes

In this course, students are expected to learn the fundamentals of automatic analysis and interpretation of biosignals, particularly in the context of pHealth. Techniques and methodologies will be studied for the analysis, classification and interpretation of information based on clinical data (signals).

Work Placement(s)

No

Syllabus

Introduction

General overview of pHealth applications for monitoring and early diagnosis.

- Application profiles

- Types and characteristics of biosignals

2. Analysis and diagnosis of biosignals

- The study of basic analysis and processing methodologies: filters, transform (Z, Fourier).

- The study of time/frequency methodologies: wavelets, Wigner-Ville transform.

- Methods for non-linear analysis (Lyapunov exponent, entropy, etc.)

- Source separation methods (ICA, etc.)

3. Areas of application

- Definition of concrete problems in different clinical domains

- The state of the art in the analysis and interpretation of specific biosignals: ECG, ICG, BP, EEG, PPG, breathing and cardiac sound.

- The state of the art in the extraction of the characteristics of physiological signs for diagnosis (time and frequency domain).

- Application of classification techniques (neuronal networks, diffuse systems) in the development of auxiliary systems.

Assessment Methods

Assessment
Research work: 25.0%
Laboratory work or Field work: 25.0%
Exam: 50.0%

Bibliography

• Introduction to Biomedical Engineering, Third Edition; John Enderle, Joseph Bronzino; 2011.

• Nonlinear Biomedical Signal Processing Vol. II: Dynamic Analysis and Modeling, Metin Akay, Wiley-IEEE Press, 2000.

• Signals and Systems Analysis in Biomedical Engineering, Robert B. B. Northrop, Taylor & Francis Ltd, March 2003.

• Signals and Systems in Biomedical Engineering : Signal Processing and Physiological Systems Modeling, Suresh R. Devasahayam, Evangelia Micheli Tzanakou, Kluwer Academic / Plenum Publishers, Dordrecht, Netherlands, 2000.

• Bioelectrical Signal Processing In Cardiac And Neurological Applications, Leif Sornmo, Pablo Laguna, Elsevier, 2005.

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

• Artigos científicos a serem definidos.