Emotion Recognition: Photoplethysmography and Electrocardiography in Comparison
Sergio Rinella,
Simona Massimino,
Piero Giorgio Fallica,
Alberto Giacobbe,
Nicola Donato,
Marinella Coco,
Giovanni Neri,
Rosalba Parenti,
Vincenzo Perciavalle,
Sabrina Conoci
Affiliations
Sergio Rinella
Department of Educational Sciences, University of Catania, via Biblioteca 4, 95124 Catania, Italy
Simona Massimino
Department of Biomedical and Biotechnological Sciences, Section of Physiology, University of Catania, via S. Sofia 89, 95125 Catania, Italy
Piero Giorgio Fallica
INSTM (National Interuniversity Consortium of Science and Technology of Materials), via G. Giusti 9, 50121 Firenze, Italy
Alberto Giacobbe
Department of Engineering, University of Messina, Contrada Di Dio, 98158 Messina, Italy
Nicola Donato
Department of Engineering, University of Messina, Contrada Di Dio, 98158 Messina, Italy
Marinella Coco
Department of Educational Sciences, University of Catania, via Biblioteca 4, 95124 Catania, Italy
Giovanni Neri
Department of Engineering, University of Messina, Contrada Di Dio, 98158 Messina, Italy
Rosalba Parenti
Department of Biomedical and Biotechnological Sciences, Section of Physiology, University of Catania, via S. Sofia 89, 95125 Catania, Italy
Vincenzo Perciavalle
Department of Sciences of Life, Kore University of Enna, Cittadella Universitaria, 94100 Enna, Italy
Sabrina Conoci
Department of Chemical, Biological, Pharmaceutical and Environmental Science, University of Messina, Viale F. Stagno d’Alcontres 31, Vill. S. Agata, 98166 Messina, Italy
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.
