Emotion Recognition: Photoplethysmography and Electrocardiography in Comparison

Automatically recognizing negative emotions, such as anger or stress, and also positive ones, such as euphoria, can contribute to improving well-being. In real-life, emotion recognition is a difficult task since many of the technologies used for this purpose in both laboratory and clinic environment...

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Published in:Biosensors
Main Authors: Sergio Rinella, Simona Massimino, Piero Giorgio Fallica, Alberto Giacobbe, Nicola Donato, Marinella Coco, Giovanni Neri, Rosalba Parenti, Vincenzo Perciavalle, Sabrina Conoci
Format: Article
Language:English
Published: MDPI AG 2022-09-01
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Online Access:https://www.mdpi.com/2079-6374/12/10/811
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author Sergio Rinella
Simona Massimino
Piero Giorgio Fallica
Alberto Giacobbe
Nicola Donato
Marinella Coco
Giovanni Neri
Rosalba Parenti
Vincenzo Perciavalle
Sabrina Conoci
author_facet Sergio Rinella
Simona Massimino
Piero Giorgio Fallica
Alberto Giacobbe
Nicola Donato
Marinella Coco
Giovanni Neri
Rosalba Parenti
Vincenzo Perciavalle
Sabrina Conoci
author_sort Sergio Rinella
collection DOAJ
container_title Biosensors
description Automatically recognizing negative emotions, such as anger or stress, and also positive ones, such as euphoria, can contribute to improving well-being. In real-life, emotion recognition is a difficult task since many of the technologies used for this purpose in both laboratory and clinic environments, such as electroencephalography (EEG) and electrocardiography (ECG), cannot realistically be used. Photoplethysmography (PPG) is a non-invasive technology that can be easily integrated into wearable sensors. This paper focuses on the comparison between PPG and ECG concerning their efficacy in detecting the psychophysical and affective states of the subjects. It has been confirmed that the levels of accuracy in the recognition of affective variables obtained by PPG technology are comparable to those achievable with the more traditional ECG technology. Moreover, the affective psychological condition of the participants (anxiety and mood levels) may influence the psychophysiological responses recorded during the experimental tests.
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spelling doaj-art-e77cdb66c5684fe7ab3b06a17ec6db432025-08-19T22:55:16ZengMDPI AGBiosensors2079-63742022-09-01121081110.3390/bios12100811Emotion Recognition: Photoplethysmography and Electrocardiography in ComparisonSergio Rinella0Simona Massimino1Piero Giorgio Fallica2Alberto Giacobbe3Nicola Donato4Marinella Coco5Giovanni Neri6Rosalba Parenti7Vincenzo Perciavalle8Sabrina Conoci9Department of Educational Sciences, University of Catania, via Biblioteca 4, 95124 Catania, ItalyDepartment of Biomedical and Biotechnological Sciences, Section of Physiology, University of Catania, via S. Sofia 89, 95125 Catania, ItalyINSTM (National Interuniversity Consortium of Science and Technology of Materials), via G. Giusti 9, 50121 Firenze, ItalyDepartment of Engineering, University of Messina, Contrada Di Dio, 98158 Messina, ItalyDepartment of Engineering, University of Messina, Contrada Di Dio, 98158 Messina, ItalyDepartment of Educational Sciences, University of Catania, via Biblioteca 4, 95124 Catania, ItalyDepartment of Engineering, University of Messina, Contrada Di Dio, 98158 Messina, ItalyDepartment of Biomedical and Biotechnological Sciences, Section of Physiology, University of Catania, via S. Sofia 89, 95125 Catania, ItalyDepartment of Sciences of Life, Kore University of Enna, Cittadella Universitaria, 94100 Enna, ItalyDepartment of Chemical, Biological, Pharmaceutical and Environmental Science, University of Messina, Viale F. Stagno d’Alcontres 31, Vill. S. Agata, 98166 Messina, ItalyAutomatically recognizing negative emotions, such as anger or stress, and also positive ones, such as euphoria, can contribute to improving well-being. In real-life, emotion recognition is a difficult task since many of the technologies used for this purpose in both laboratory and clinic environments, such as electroencephalography (EEG) and electrocardiography (ECG), cannot realistically be used. Photoplethysmography (PPG) is a non-invasive technology that can be easily integrated into wearable sensors. This paper focuses on the comparison between PPG and ECG concerning their efficacy in detecting the psychophysical and affective states of the subjects. It has been confirmed that the levels of accuracy in the recognition of affective variables obtained by PPG technology are comparable to those achievable with the more traditional ECG technology. Moreover, the affective psychological condition of the participants (anxiety and mood levels) may influence the psychophysiological responses recorded during the experimental tests.https://www.mdpi.com/2079-6374/12/10/811bio-signal processingphotoplethysmographyunobtrusive sensing
spellingShingle Sergio Rinella
Simona Massimino
Piero Giorgio Fallica
Alberto Giacobbe
Nicola Donato
Marinella Coco
Giovanni Neri
Rosalba Parenti
Vincenzo Perciavalle
Sabrina Conoci
Emotion Recognition: Photoplethysmography and Electrocardiography in Comparison
bio-signal processing
photoplethysmography
unobtrusive sensing
title Emotion Recognition: Photoplethysmography and Electrocardiography in Comparison
title_full Emotion Recognition: Photoplethysmography and Electrocardiography in Comparison
title_fullStr Emotion Recognition: Photoplethysmography and Electrocardiography in Comparison
title_full_unstemmed Emotion Recognition: Photoplethysmography and Electrocardiography in Comparison
title_short Emotion Recognition: Photoplethysmography and Electrocardiography in Comparison
title_sort emotion recognition photoplethysmography and electrocardiography in comparison
topic bio-signal processing
photoplethysmography
unobtrusive sensing
url https://www.mdpi.com/2079-6374/12/10/811
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