Stefano Betti

Piaggio (Italy), Scuola Superiore Sant'Anna

Papers

Total Citations

H-Index

About

Stefano Betti is a researcher at the forefront of affective computing and human-robot interaction, specializing in the use of physiological signals to detect and classify human emotional states. His work bridges biomedical engineering, wireless sensor networks, and the Internet of Robotic Things (IoRT), aiming to make robots more responsive to human moods. Betti’s most cited study, “Mood classification through physiological parameters” (2019, 16 citations), demonstrates how wearable sensors can accurately infer emotional states, laying groundwork for empathetic machines. His subsequent papers extend this concept into wireless physiological sensor networks (8 citations) and IoRT frameworks (4 citations), where smart devices and cloud robotics collaborate to perceive user affect in real time. Though his citation counts are modest, Betti’s contributions are notable for their interdisciplinary integration—combining physiology, pervasive computing, and robotics to enhance daily life. His work is particularly relevant for researchers developing assistive technologies, as it offers a concrete pathway toward systems that not only sense but also adapt to human emotions, advancing the vision of truly intelligent and caring robotic companions.