Study on the usage feasibility of continuous-wave radar for emotion recognition

• Autor(a) principal: Gouveia, Carolina
• Data de Publicação: 2020
• Outros Autores: Tomé, Ana, Barros, Filipa, Soares, Sandra C., Vieira, José, Pinho, Pedro
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10773/28338
• topic: Continuous wave radar; Emotion recognition; Pattern recognition; Support-vector machine; K-nearest neighbour; Random Forest

Non-contact vital signs monitoring has a wide range of applications, such as in safe drive and in healthcare. In mental health care, the use of non-invasive signs holds a great potential, as it would likely enhancethe patient’s adherence to the use of objective measures to assess their emotional experiences, henceallowing for more individualized and efficient diagnoses and treatment. In order to evaluate the possi-bility of emotion recognition using a non-contact system for vital signs monitoring, we herein present acontinuous wave radar based on the respiratory signal acquisition. An experimental set up was designedto acquire the respiratory signal while participants were watching videos that elicited different emotions(fear, happiness and a neutral condition). Signal was registered using a radar-based system and a stan-dard certified equipment. The experiment was conducted to validate the system at two levels: the signalacquisition and the emotion recognition levels. Vital sign was analysed and the three emotions were iden-tified using different classification algorithms. Furthermore, the classifier performance was compared,having in mind the signal acquired by both systems. Three different classification algorithms were used:the support-vector machine, K-nearest neighbour and the Random Forest. The achieved accuracy rates,for the three-emotion classification, were within 60% and 70%, which indicates that it is indeed possibleto evaluate the emotional state of an individual using vital signs detected remotely.