AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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2022
Augello, Agnese; Infantino, Ignazio; Pilato, Giovanni; Vitale, Gianpaolo
Extending Affective Capabilities for Medical Assistive Robots Journal Article
In: Cognitive Systems Research, vol. 73, pp. 21–25, 2022, ISSN: 13890417.
Abstract | Links | BibTeX | Tags: Anthropomorphic Robots, Assistive Robots, Emotion Detection, Facial Expressions, Human computer interaction, Human Robot Interaction, Humanoid Robots, Natural Language Processing, Robotics, Wellbeing
@article{augelloExtendingAffectiveCapabilities2022,
title = {Extending Affective Capabilities for Medical Assistive Robots},
author = { Agnese Augello and Ignazio Infantino and Giovanni Pilato and Gianpaolo Vitale},
doi = {10.1016/j.cogsys.2021.12.004},
issn = {13890417},
year = {2022},
date = {2022-01-01},
journal = {Cognitive Systems Research},
volume = {73},
pages = {21--25},
abstract = {In this work, we discuss methodologies and implementation choices to enable a humanoid robot to estimate patients' mood and emotions during postoperative home rehabilitation. The approach is modular and it has been implemented into a SoftBank Pepper robotic architecture; however, the approach is general and it can be easily adapted to other robotic platforms. A sample of an interactive session for the detection of the patient's affective state is also reported. textcopyright 2022 Elsevier B.V.},
keywords = {Anthropomorphic Robots, Assistive Robots, Emotion Detection, Facial Expressions, Human computer interaction, Human Robot Interaction, Humanoid Robots, Natural Language Processing, Robotics, Wellbeing},
pubstate = {published},
tppubtype = {article}
}
Augello, Agnese; Bella, Giulia Di; Infantino, Ignazio; Pilato, Giovanni; Vitale, Gianluigi
Multimodal Mood Recognition for Assistive Scenarios Proceedings Article
In: F.F., Samsonovich A. V. Ramos Corchado (Ed.): Procedia Computer Science, pp. 510–517, Elsevier B.V., 2022.
Abstract | Links | BibTeX | Tags: Assistive Robots, Emotion Analysis, Emotion Recognition, Mood
@inproceedings{augelloMultimodalMoodRecognition2022,
title = {Multimodal Mood Recognition for Assistive Scenarios},
author = { Agnese Augello and Giulia Di Bella and Ignazio Infantino and Giovanni Pilato and Gianluigi Vitale},
editor = { Samsonovich A.V. Ramos Corchado F.F.},
doi = {10.1016/j.procs.2022.11.098},
year = {2022},
date = {2022-01-01},
booktitle = {Procedia Computer Science},
volume = {213},
pages = {510--517},
publisher = {Elsevier B.V.},
abstract = {We illustrate a system performing multimodal human emotion detection from video input through the integration of audio emotional recognition, text emotional recognition, facial emotional recognition, and emotional recognition from a spectrogram. The outcomes of the four emotion recognition modalities are compared, and a final evaluation provides the most likely perceived emotion. The system has been designed to be easily implemented on cheap mini-computer based boards. It is conceived to be used as auxiliary tool in the field of telemedicine to remotely monitor the mood of patients and observe their healing process, which is closely related to their emotional condition. textcopyright 2022 The Author(s).},
keywords = {Assistive Robots, Emotion Analysis, Emotion Recognition, Mood},
pubstate = {published},
tppubtype = {inproceedings}
}