This paper presents an Android smartphone app to collect emotion-labeled physiological signals in the wild. The app controls a body sensor network that starts and stops sensors in random moments, without user knowing. Experiments involved recording the galvanic skin response (GSR), photoplethysmogram (PPG), 2-channel electromyogram (EMG), and 4-channel electroencephalogram (EEG) of 30 volunteers. AI models trained using the collected data determined a person's valence and arousal levels with an accuracy of 92.8% and 94%, respectively. The app is free to download by contacting the authors.
A smartphone app to collect emotion-labeled signals in the wild using a body sensor network
Pistolesi, Francesco
Primo
;Baldassini, MicheleSecondo
;Lazzerini, BeatriceUltimo
2022-01-01
Abstract
This paper presents an Android smartphone app to collect emotion-labeled physiological signals in the wild. The app controls a body sensor network that starts and stops sensors in random moments, without user knowing. Experiments involved recording the galvanic skin response (GSR), photoplethysmogram (PPG), 2-channel electromyogram (EMG), and 4-channel electroencephalogram (EEG) of 30 volunteers. AI models trained using the collected data determined a person's valence and arousal levels with an accuracy of 92.8% and 94%, respectively. The app is free to download by contacting the authors.File in questo prodotto:
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