The objective of this course is to provide the basic knowledge about the most widely used processing techniques specifically developed for biomedical signals. The goal is to provide knowledge about the filtering techniques, the spectral estimation (particularly of random processes), and of time-varying spectral analysis of nonstationary signals. Each processing technique will be coupled to applications on real biomedical signals.

Basic knowledge about the mathematical techniques for filtering and spectral analysis.
Knowledge of the information content of the physiological signals.
Knowledge about the diagnostic and monitoring potentialities and needs for the different processing techniques.
Knowledge of the critical processing aspects for the different biomedical signals.

Given a biomedical signal and a clinical need, the student will be able to apply the most proper processing technique, in order to fulfill the need and extract information from the signal. Since the students will learn about the most recent and performing processing techniques, it will be possible for them to develop advanced and automated feature extraction algorithms.

During the lab work, the students will improve their judgement capacity and autonomy.

The lab assignments will help improve the students’ oral and written communication skills.

The students will be required to regularly check the most renowned international journals in the field of biomedical signal processing, in order to learn the latest technical solutions for specific applications. Hence, a continuous formation is possible for the students.

The students should have a good knowledge of mathematics, signal theory, and physiology. The students should know the characteristics of the principal biomedical signals (EMG, ECG, EEG, ...).
For a proper understanding of the need for processing of different signals and for different clinical questions, the knowledge of the basics of human physiology and pathology is advisable.

The principal topics are:
- Digital filtering techniques (10h)
- Non-parametric spectral analysis techniques (10h)
- Parametric spectral analysis techniques (10h)
- Time-varying and time-frequency techniques (10h)
- Complexity and non-linear analysis (10h)
- Selected application of biomedical signal processing (20h)
- Open issues and recent processing solutions (10h)

The course is divided into frontal lessons and lab works. For the lab assignments, the students will be divided into groups of four members. There will be ten labs during the course. The lab works will be conducted by using MATLAB. The students will be asked to implement algorithms for the processing of real biomedical signals.

Teacher’s slides and scientific papers about recent technical innovations.

The exam consists of two parts: a practical part and an oral interview. The students have to pass the practical part before being admitted to the oral interview. The practical part consists in the design and implementation of processing strategies and to apply them to real biomedical signals. In the oral part, the students will be able to better discuss their choices and their strategy, with particular reference to the theoretical aspects of the questions of the practical part.