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Ghiasi S, Valenza G, Morelli MS, Bianchi M, Scilingo EP, Greco A. The Role of Haptic Stimuli on Affective Reading: a Pilot Study. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2019:4938-4941. [PMID: 31946968 DOI: 10.1109/embc.2019.8857337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
The affective role of touch has opened new perspectives in human-machine interaction. This paper presents an emotion recognition algorithm to investigate the role of tactile stimuli conveyed through a wearable haptic system during affective reading. To this end, a group of 32 healthy volunteers underwent an emotional stimulation by reading affective texts, with and without the concurrent presence of pleasant haptic stimuli. Throughout the experiment, autonomic nervous system dynamics was quantified through heart rate variability (HRV) and electrodermal activity (EDA) analyses. EDA and HRV features were then used as input of a SVM-RFE learning algorithm for an automatic recognition of neutral and arousing texts. The affective recognition of the reading was performed in the presence or absence of the haptic stimulation. Results show that the affective perception induced by the neutral and arousing reading were discriminated with a significantly improved accuracy (+14.5%) when a caress-like haptic stimulus was conveyed to the user.
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Greco A, Guidi A, Bianchi M, Lanata A, Valenza G, Scilingo EP. Brain Dynamics Induced by Pleasant/Unpleasant Tactile Stimuli Conveyed by Different Fabrics. IEEE J Biomed Health Inform 2019; 23:2417-2427. [PMID: 30668509 DOI: 10.1109/jbhi.2019.2893324] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
In this study, we investigated brain dynamics from electroencephalographic (EEG) signals during affective tactile stimulation conveyed by the dynamical contact with different fabrics. Thirty-three healthy subjects (16 females) were enrolled to interact with a haptic device able to mimic caress-like stimuli conveyed by strips of different fabrics moved back and forth at different velocities. Specifically, two velocity levels (i.e., 9.4 and 65 mm/sec) and two kinds of fabric (i.e., burlap and silk) were selected to deliver pleasant and unpleasant affective elicitations, according to subjects' self-assessment. EEG power spectra and functional connectivity were then calculated and analyzed. Experimental results, reported in terms of p-value topographic maps, demonstrated that caresses administered through unpleasant fabrics increased brain activity in the θ (4-8 Hz), α (8-14 Hz), and β (14-30 Hz) bands, whereas the use of pleasant fabrics enhanced functional connections in specific areas (e.g., frontal, occipital, and temporal cortices) depending on the oscillations frequency and caressing velocity. Furthermore, we adopted K-NN algorithms to automatically recognize the pleasantness of the haptic stimulation at a single-subject level using EEG power spectra, achieving a recognition accuracy up to 74.24%. Finally, we showed how brain oscillation power in the α and β bands over contralateral frontal- and central-cortex were the most informative features characterizing the pleasantness of a tactile stimulus on the forearm.
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Valenza G, Greco A, Bianchi M, Nardelli M, Rossi S, Scilingo EP. EEG oscillations during caress-like affective haptic elicitation. Psychophysiology 2018; 55:e13199. [DOI: 10.1111/psyp.13199] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2017] [Revised: 04/09/2018] [Accepted: 04/12/2018] [Indexed: 01/26/2023]
Affiliation(s)
- Gaetano Valenza
- Department of Information Engineering and the Bioengineering and Robotics Research Center “E. Piaggio,” School of Engineering; University of Pisa; Pisa Italy
| | - Alberto Greco
- Department of Information Engineering and the Bioengineering and Robotics Research Center “E. Piaggio,” School of Engineering; University of Pisa; Pisa Italy
| | - Matteo Bianchi
- Department of Information Engineering and the Bioengineering and Robotics Research Center “E. Piaggio,” School of Engineering; University of Pisa; Pisa Italy
| | - Mimma Nardelli
- Department of Information Engineering and the Bioengineering and Robotics Research Center “E. Piaggio,” School of Engineering; University of Pisa; Pisa Italy
| | - Simone Rossi
- Brain Investigation & Neuromodulation Lab (Si-BIN Lab), Department of Medicine, Surgery and Neuroscience, Neurology and Clinical Neurophysiology Unit; University of Siena; Siena Italy
| | - Enzo Pasquale Scilingo
- Department of Information Engineering and the Bioengineering and Robotics Research Center “E. Piaggio,” School of Engineering; University of Pisa; Pisa Italy
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Plusquellec P, Denault V. The 1000 Most Cited Papers on Visible Nonverbal Behavior: A Bibliometric Analysis. JOURNAL OF NONVERBAL BEHAVIOR 2018. [DOI: 10.1007/s10919-018-0280-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
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Beckerle P, Salvietti G, Unal R, Prattichizzo D, Rossi S, Castellini C, Hirche S, Endo S, Amor HB, Ciocarlie M, Mastrogiovanni F, Argall BD, Bianchi M. A Human-Robot Interaction Perspective on Assistive and Rehabilitation Robotics. Front Neurorobot 2017; 11:24. [PMID: 28588473 PMCID: PMC5440510 DOI: 10.3389/fnbot.2017.00024] [Citation(s) in RCA: 77] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2017] [Accepted: 05/05/2017] [Indexed: 11/30/2022] Open
Abstract
Assistive and rehabilitation devices are a promising and challenging field of recent robotics research. Motivated by societal needs such as aging populations, such devices can support motor functionality and subject training. The design, control, sensing, and assessment of the devices become more sophisticated due to a human in the loop. This paper gives a human-robot interaction perspective on current issues and opportunities in the field. On the topic of control and machine learning, approaches that support but do not distract subjects are reviewed. Options to provide sensory user feedback that are currently missing from robotic devices are outlined. Parallels between device acceptance and affective computing are made. Furthermore, requirements for functional assessment protocols that relate to real-world tasks are discussed. In all topic areas, the design of human-oriented frameworks and methods is dominated by challenges related to the close interaction between the human and robotic device. This paper discusses the aforementioned aspects in order to open up new perspectives for future robotic solutions.
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Affiliation(s)
- Philipp Beckerle
- Institute for Mechatronic Systems, Mechanical Engineering, Technische Universität Darmstadt, Darmstadt, Germany
| | - Gionata Salvietti
- Human Centered Robotics Group, SIRSLab, Department of Information Engineering and Mathematics, University of Siena, Siena, Italy
| | - Ramazan Unal
- Department of Mechanical Engineering, Abdullah Gul University, Kayseri, Turkey
| | - Domenico Prattichizzo
- Human Centered Robotics Group, SIRSLab, Department of Information Engineering and Mathematics, University of Siena, Siena, Italy
| | - Simone Rossi
- Unit of Neurology and Clinical Neurophysiology, Department of Medicine, Surgery and Neuroscience, Section of Human Physiology, University of Siena, Siena, Italy
| | - Claudio Castellini
- Institute of Robotics and Mechatronics, DLR German Aerospace Center, Oberpfaffenhofen, Germany
| | | | | | - Heni Ben Amor
- Interactive Robotics Laboratory, School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, United States
| | - Matei Ciocarlie
- Department of Mechanical Engineering, Columbia University, New York, NY, United States
| | - Fulvio Mastrogiovanni
- Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genova, Genova, Italy
| | - Brenna D. Argall
- Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, United States
- Department of Mechanical Engineering, Northwestern University, Evanston, IL, United States
- Department of Physical Medicine and Rehabilitation, Northwestern University, Evanston, IL, United States
- Rehabilitation Institute of Chicago, Chicago IL, United States
| | - Matteo Bianchi
- Research Centre “Enrico Piaggio”, University of Pisa, Pisa, Italy
- Department of Information Engineering, University of Pisa, Pisa, Italy
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Beckerle P, Salvietti G, Unal R, Prattichizzo D, Rossi S, Castellini C, Hirche S, Endo S, Amor HB, Ciocarlie M, Mastrogiovanni F, Argall BD, Bianchi M. A Human-Robot Interaction Perspective on Assistive and Rehabilitation Robotics. Front Neurorobot 2017. [PMID: 28588473 DOI: 10.3389/frbot.2017.00024] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/26/2023] Open
Abstract
Assistive and rehabilitation devices are a promising and challenging field of recent robotics research. Motivated by societal needs such as aging populations, such devices can support motor functionality and subject training. The design, control, sensing, and assessment of the devices become more sophisticated due to a human in the loop. This paper gives a human-robot interaction perspective on current issues and opportunities in the field. On the topic of control and machine learning, approaches that support but do not distract subjects are reviewed. Options to provide sensory user feedback that are currently missing from robotic devices are outlined. Parallels between device acceptance and affective computing are made. Furthermore, requirements for functional assessment protocols that relate to real-world tasks are discussed. In all topic areas, the design of human-oriented frameworks and methods is dominated by challenges related to the close interaction between the human and robotic device. This paper discusses the aforementioned aspects in order to open up new perspectives for future robotic solutions.
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Affiliation(s)
- Philipp Beckerle
- Institute for Mechatronic Systems, Mechanical Engineering, Technische Universität Darmstadt, Darmstadt, Germany
| | - Gionata Salvietti
- Human Centered Robotics Group, SIRSLab, Department of Information Engineering and Mathematics, University of Siena, Siena, Italy
| | - Ramazan Unal
- Department of Mechanical Engineering, Abdullah Gul University, Kayseri, Turkey
| | - Domenico Prattichizzo
- Human Centered Robotics Group, SIRSLab, Department of Information Engineering and Mathematics, University of Siena, Siena, Italy
| | - Simone Rossi
- Unit of Neurology and Clinical Neurophysiology, Department of Medicine, Surgery and Neuroscience, Section of Human Physiology, University of Siena, Siena, Italy
| | - Claudio Castellini
- Institute of Robotics and Mechatronics, DLR German Aerospace Center, Oberpfaffenhofen, Germany
| | | | | | - Heni Ben Amor
- Interactive Robotics Laboratory, School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, United States
| | - Matei Ciocarlie
- Department of Mechanical Engineering, Columbia University, New York, NY, United States
| | - Fulvio Mastrogiovanni
- Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genova, Genova, Italy
| | - Brenna D Argall
- Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, United States
- Department of Mechanical Engineering, Northwestern University, Evanston, IL, United States
- Department of Physical Medicine and Rehabilitation, Northwestern University, Evanston, IL, United States
- Rehabilitation Institute of Chicago, Chicago IL, United States
| | - Matteo Bianchi
- Research Centre "Enrico Piaggio", University of Pisa, Pisa, Italy
- Department of Information Engineering, University of Pisa, Pisa, Italy
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