Emotion Recognition: Photoplethysmography and Electrocardiography in Comparison.


Journal

Biosensors
ISSN: 2079-6374
Titre abrégé: Biosensors (Basel)
Pays: Switzerland
ID NLM: 101609191

Informations de publication

Date de publication:
30 Sep 2022
Historique:
received: 03 08 2022
revised: 23 09 2022
accepted: 26 09 2022
entrez: 27 10 2022
pubmed: 28 10 2022
medline: 29 10 2022
Statut: epublish

Résumé

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.

Identifiants

pubmed: 36290948
pii: bios12100811
doi: 10.3390/bios12100811
pmc: PMC9599834
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Governo Italiano
ID : Project ADAS+: Sviluppo di tecnologie e sistemi avanzati per la sicurezza dell'auto mediante pi-attaforme ADAS

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Auteurs

Sergio Rinella (S)

Department of Educational Sciences, University of Catania, via Biblioteca 4, 95124 Catania, Italy.

Simona Massimino (S)

Department of Biomedical and Biotechnological Sciences, Section of Physiology, University of Catania, via S. Sofia 89, 95125 Catania, Italy.

Piero Giorgio Fallica (PG)

INSTM (National Interuniversity Consortium of Science and Technology of Materials), via G. Giusti 9, 50121 Firenze, Italy.

Alberto Giacobbe (A)

Department of Engineering, University of Messina, Contrada Di Dio, 98158 Messina, Italy.

Nicola Donato (N)

Department of Engineering, University of Messina, Contrada Di Dio, 98158 Messina, Italy.

Marinella Coco (M)

Department of Educational Sciences, University of Catania, via Biblioteca 4, 95124 Catania, Italy.

Giovanni Neri (G)

Department of Engineering, University of Messina, Contrada Di Dio, 98158 Messina, Italy.

Rosalba Parenti (R)

Department of Biomedical and Biotechnological Sciences, Section of Physiology, University of Catania, via S. Sofia 89, 95125 Catania, Italy.

Vincenzo Perciavalle (V)

Department of Sciences of Life, Kore University of Enna, Cittadella Universitaria, 94100 Enna, Italy.

Sabrina Conoci (S)

Department of Chemical, Biological, Pharmaceutical and Environmental Science, University of Messina, Viale F. Stagno d'Alcontres 31, Vill. S. Agata, 98166 Messina, Italy.
LAB Sense Beyond Nano-URT Department of Sciences Physics and Technologies of Matter (DSFTM) CNR, Viale F. Stagno d'Alcontres 31, Vill. S. Agata, 98166 Messina, Italy.
Department of Chemistry ''Giacomo Ciamician'', University of Bologna, Via Selmi 2, 40126 Bologna, Italy.
Istituto per la Microelettronica e Microsistemi, Consiglio Nazionale delle Ricerche (CNR-IMM), Strada VIII n. 5, 95121 Catania, Italy.

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Classifications MeSH