The course explores the principles of cybernetics, covering system design for human-machine
integration, practical implementation, and ethical considerations. Students will learn to collect and
analyze multimodal neurophysiological and behavioral data, such as EEG, EDA, and eye-
tracking. They will apply machine learning techniques to detect patterns and classify states, such
as stress levels or focus, and design multimodal interactions that adaptively influence users or
environments like smart interfaces and responsive systems. Applications of these skills span
multiple domains, including medical diagnostics and treatment, such as neurofeedback for mental
health; worker support and well-being, like fatigue monitoring in high-stakes professions; human-
vehicle systems, such as adaptive driving assistance; and creative fields like art and interactive
design. Additional applications include education and training through personalized learning
environments. The course combines theoretical foundations with hands-on practice through a
startup simulation. Students will design and develop a functional cybernetic system, culminating
in a final pitch that highlights its scalability, innovation and societal impact
- Docente: Esther Mauron
- Docente: Samy Rima