A Multimodal Perception Framework for Users Emotional State Assessment in Social Robotics

In this work, we present an unobtrusive and non-invasive perception framework based on the synergy between two main acquisition systems: the Touch-Me Pad, consisting of two electronic patches for physiological signal extraction and processing; and the Scene Analyzer, a visual-auditory perception sys...

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Main Authors: Lorenzo Cominelli, Nicola Carbonaro, Daniele Mazzei, Roberto Garofalo, Alessandro Tognetti, Danilo De Rossi
Format: Article
Language:English
Published: MDPI AG 2017-08-01
Series:Future Internet
Subjects:
Online Access:https://www.mdpi.com/1999-5903/9/3/42
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author Lorenzo Cominelli
Nicola Carbonaro
Daniele Mazzei
Roberto Garofalo
Alessandro Tognetti
Danilo De Rossi
author_facet Lorenzo Cominelli
Nicola Carbonaro
Daniele Mazzei
Roberto Garofalo
Alessandro Tognetti
Danilo De Rossi
author_sort Lorenzo Cominelli
collection DOAJ
description In this work, we present an unobtrusive and non-invasive perception framework based on the synergy between two main acquisition systems: the Touch-Me Pad, consisting of two electronic patches for physiological signal extraction and processing; and the Scene Analyzer, a visual-auditory perception system specifically designed for the detection of social and emotional cues. It will be explained how the information extracted by this specific kind of framework is particularly suitable for social robotics applications and how the system has been conceived in order to be used in human-robot interaction scenarios.
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spelling doaj.art-ef996f88fb1d4f149534e431b103f74e2022-12-21T18:32:30ZengMDPI AGFuture Internet1999-59032017-08-01934210.3390/fi9030042fi9030042A Multimodal Perception Framework for Users Emotional State Assessment in Social RoboticsLorenzo Cominelli0Nicola Carbonaro1Daniele Mazzei2Roberto Garofalo3Alessandro Tognetti4Danilo De Rossi5Research Center “E. Piaggio”, Faculty of Engineering, University of Pisa, 56122 Pisa, ItalyResearch Center “E. Piaggio”, Faculty of Engineering, University of Pisa, 56122 Pisa, ItalyResearch Center “E. Piaggio”, Faculty of Engineering, University of Pisa, 56122 Pisa, ItalyResearch Center “E. Piaggio”, Faculty of Engineering, University of Pisa, 56122 Pisa, ItalyResearch Center “E. Piaggio”, Faculty of Engineering, University of Pisa, 56122 Pisa, ItalyResearch Center “E. Piaggio”, Faculty of Engineering, University of Pisa, 56122 Pisa, ItalyIn this work, we present an unobtrusive and non-invasive perception framework based on the synergy between two main acquisition systems: the Touch-Me Pad, consisting of two electronic patches for physiological signal extraction and processing; and the Scene Analyzer, a visual-auditory perception system specifically designed for the detection of social and emotional cues. It will be explained how the information extracted by this specific kind of framework is particularly suitable for social robotics applications and how the system has been conceived in order to be used in human-robot interaction scenarios.https://www.mdpi.com/1999-5903/9/3/42perception frameworkphysiological signal acquisitionmultimodalitysocial roboticshuman-robot interaction
spellingShingle Lorenzo Cominelli
Nicola Carbonaro
Daniele Mazzei
Roberto Garofalo
Alessandro Tognetti
Danilo De Rossi
A Multimodal Perception Framework for Users Emotional State Assessment in Social Robotics
Future Internet
perception framework
physiological signal acquisition
multimodality
social robotics
human-robot interaction
title A Multimodal Perception Framework for Users Emotional State Assessment in Social Robotics
title_full A Multimodal Perception Framework for Users Emotional State Assessment in Social Robotics
title_fullStr A Multimodal Perception Framework for Users Emotional State Assessment in Social Robotics
title_full_unstemmed A Multimodal Perception Framework for Users Emotional State Assessment in Social Robotics
title_short A Multimodal Perception Framework for Users Emotional State Assessment in Social Robotics
title_sort multimodal perception framework for users emotional state assessment in social robotics
topic perception framework
physiological signal acquisition
multimodality
social robotics
human-robot interaction
url https://www.mdpi.com/1999-5903/9/3/42
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