Università Roma Tre

Introduction to the course. Biomedical signals: Electroencephalography (EEG), Electromyography (EMG), Electrocardiography (ECG). Basic Elements of Signal Processing: representation in the Fourier domain, filtering, artifacts and noise rejection. Spectral estimation: non-parametric and parametric techniques. Time-frequency analysis: Short Time Fourier Transform and Spectrogram, Wavelet and Scalogram. Matlab Labs.

L. Sornmo, P. Laguna. Bioelectrical signal processing in cardiac and neurological applications. Elsevier Academic Press. 2005.
Materials on-line (notes, exercises, solutions. Download from Moodle).

The course aims to prepare students to selected activities of an experimental laboratory, in which the typical methods of Biomedical Engineering are applied. During class lessons, the topics necessary to understand the activities required for the acquisition and management of biomedical signals will be illustrated, through experimental tools typical of Engineering with a specific focus on practical laboratory activities execution and particular reference to the following topics:

• The electronics equipment of an experimental Biomedical Engineering laboratory.
• Systems and sensor for the acquisitions and measure of biomedical data and signals: sensors for human movement analysis and for electrophysiological signals, signal conditioning and acquisition systems.
• Experimental protocols for the acquisition of data: from the sensor to the digitization and storage on a computer.
• The organization of the acquisition phase and of the experimental setup for biomedical data and signals.
• The virtual instrumentation for the management of the experimental data: fundamentals of Labview.
• Embedded systems for biomedical applications: basics of biomedical wearable devices design.
• Laboratory experience on selected devices typical of the Biomedical Engineering laboratory.

• BRONZINO - BIOMEDICAL ENGINEERING HANDBOOK, TAYLOR AND FRANCIS GROUP

• ONLINE TUTORIALS ON moodle2 web platform