Matteo Spezialetti
Papers
5
Total Citations
332
H-Index
4
About
Matteo Spezialetti is a leading researcher at the intersection of human-robot interaction (HRI), affective computing, and rehabilitation technologies. His work focuses on endowing robots with emotional intelligence to make interactions more intuitive and natural, particularly through emotion and mood recognition from wearable data and visual analysis. Spezialetti’s most cited paper, “Emotion Recognition for Human-Robot Interaction: Recent Advances and Future Perspectives” (2020, 269 citations), provides a comprehensive survey that has become a foundational reference for the field. He has also made significant contributions to assistive robotics, including a LEAP-based virtual glove for hand rehabilitation (2018, 35 citations) and a deep learning approach for mood recognition from wearable sensors (2020, 20 citations). His innovative work extends to integrating brain-computer interfaces with hand tracking and robotic arms to improve decoding of motor signals. Spezialetti’s research is notable for its practical applications in socially assistive robotics, supporting elders and individuals with mood disorders, and advancing objective, automated rehabilitation and cognitive testing through HRI. His interdisciplinary approach bridges engineering, psychology, and clinical practice, making him a key figure in developing empathetic, responsive robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Measurements by A LEAP-Based Virtual Glove for the Hand Rehabilitation35 citations · 2018
- 3A Deep Learning Approach for Mood Recognition from Wearable Data20 citations · 2020
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