This paper proposes a method for the detection of emotion-relevant activities performed when seated and its corresponding system based on wrist-worn inertial sensors combined with a pressure detection smart cushion. In particular, aiming at providing an additional source of information in traditional emotion Recognition systems, we focus on shame-, fear-, and joy-related activities. Experiments are conducted and the results of performance evaluation show the proposed method achieves high Recognition accuracy with a set obtained by fusing time-and frequency-domain features extracted from the different available sensors.
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Titolo: | Posture and Gesture Analysis Supporting Emotional Activity Recognition |
Autori: | |
Data di pubblicazione: | 2019 |
Handle: | http://hdl.handle.net/20.500.11770/289754 |
ISBN: | 9781538666500 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |