Remote Emotion Recognition Using Continuous-Wave Bio-Radar System
Carolina Gouveia,
Beatriz Soares,
Daniel Albuquerque,
Filipa Barros,
Sandra C. Soares,
Pedro Pinho,
José Vieira,
Susana Brás
Affiliations
Carolina Gouveia
Instituto de Engenharia Electrónica e Telemática de Aveiro, Departamento de Electrónica, Telecomunicações e Informática, Intelligent Systems Associate Laboratory, University of Aveiro, 3810-193 Aveiro, Portugal
Beatriz Soares
Instituto de Telecomunicações, 3810-193 Aveiro, Portugal
Daniel Albuquerque
Instituto de Engenharia Electrónica e Telemática de Aveiro, Departamento de Electrónica, Telecomunicações e Informática, Intelligent Systems Associate Laboratory, University of Aveiro, 3810-193 Aveiro, Portugal
Filipa Barros
Center for Health Technology and Services Research, Department of Education and Psychology, University of Aveiro, 3810-193 Aveiro, Portugal
Sandra C. Soares
William James Center for Research, Department of Education and Psychology, University of Aveiro, 3810-193 Aveiro, Portugal
Pedro Pinho
Instituto de Telecomunicações, 3810-193 Aveiro, Portugal
José Vieira
Instituto de Engenharia Electrónica e Telemática de Aveiro, Departamento de Electrónica, Telecomunicações e Informática, Intelligent Systems Associate Laboratory, University of Aveiro, 3810-193 Aveiro, Portugal
Susana Brás
Instituto de Engenharia Electrónica e Telemática de Aveiro, Departamento de Electrónica, Telecomunicações e Informática, Intelligent Systems Associate Laboratory, University of Aveiro, 3810-193 Aveiro, Portugal
The Bio-Radar is herein presented as a non-contact radar system able to capture vital signs remotely without requiring any physical contact with the subject. In this work, the ability to use the proposed system for emotion recognition is verified by comparing its performance on identifying fear, happiness and a neutral condition, with certified measuring equipment. For this purpose, machine learning algorithms were applied to the respiratory and cardiac signals captured simultaneously by the radar and the referenced contact-based system. Following a multiclass identification strategy, one could conclude that both systems present a comparable performance, where the radar might even outperform under specific conditions. Emotion recognition is possible using a radar system, with an accuracy equal to 99.7% and an F1-score of 99.9%. Thus, we demonstrated that it is perfectly possible to use the Bio-Radar system for this purpose, which is able to be operated remotely, avoiding the subject awareness of being monitored and thus providing more authentic reactions.
