Basic knowledge of information transmission systems, to comprehend the main communication standards for wireless sensor networks.
Ability to choose the best network architecture and elements for applications related to monitoring, processing and transmission of biomedical data and signals.
Elements of signal processing and architecture for wearable and implantable biosensors.
Course Prerequisites
Basic knowledge of statistics and signal processing, usually acquired from the course on biosignal and bioimage processing.
Teaching Methods
Lectures (hours/year in lecture theatre): 42 Workshops (hours/year in a lab): 10 The lectures are given using slides, providing additional explanations and examples at the blackboard. Laboratory activities are based on “hands on” experience with real sensors and wireless networks.
Assessment Methods
The final exam is an oral test devoted to score the student knowledge by means of four/five questions, starting from a candidate-selected topic.
As an alternative to the oral examination, a project may be presented, the topic of which must be defined together with the course lecturers, which may include: analysis and understanding of the literature references, description of the architectures of the system under study, parts of the project possibly implemented in Matlab or by means of other tools used in the laboratories.
In both cases, the ability to identify the most suitable wireless transmission architectures for monitoring, processing, and transmitting biomedical signals will be evaluated.
The minimum score to pass the exam is 18, the top score is 30 cum laude.
Texts
H. Karl, A. Willig, “Protocols and Architectures for Wireless Sensor Networks,” Wiley, 2005.
Contents
Point-to-point transmission systems, modulation and coding of information sources. Basic notions of Wireless sensor network architectures: sensors, communication nodes or motes, data gateways and processing elements. Main network topologies. Radio communication techniques for sensor networks: from physical layer to routing protocols. Wearable and implantable biosensor transmission technologies. Signal processing on sensed data: linear and nonlinear filtering techniques. Laboratory activities on design platforms for wireless communication systems and sensors, focused on biomedical applications.
