Um Modelo de Aprendizado Profundo Multimodal para Classificação de Estresse Utilizando Sinais Obtidos por Dispositivos Vestíveis de Pulso
Resumo
A recente proliferação dos dispositivos vestíveis (e.g. smartphones e smartwatches) e sua capacidade de medir vários sinais fisiológicos criam uma oportunidade de monitoramento contínuo e discreto do estado de estresse de um indivíduo. Tendo isso em vista, este trabalho propõe um novo modelo para classificação de estresse baseado em uma rede de convolução usando dados coletados por dispositivos de pulso. Os resultados obtidos, utilizando a validação leave-one-subject-out (LOSO), alcançaram a taxa média de 95,67% de acurácia, sendo um valor superior à maioria dos trabalhos já existentes na literatura.Referências
Bernardi, L., Valle, F., Coco, M., Calciati, A., & Sleight, P. (1996). "Physical activity influences heart rate variability and very-low-frequency components in Holter electrocardiograms". Cardiovascular research, 32(2), 234-237.
Bobade, P., & Vani, M. (2020). "Stress detection with machine learning and deep learning using multimodal physiological data". In 2020 Second International Conference on Inventive Research in Computing Applications (ICIRCA) (pp. 51-57). IEEE.
Butler, G. (1993). "Definitions of stress". In Stress management in general practice (pp. 1-5). Royal College of General Practitioners.
Carneiro, D., Novais, P., Augusto, J. C., & Payne, N. (2017). "New methods for stress assessment and monitoring at the workplace". IEEE Transactions on Affective Computing, 10(2), 237-254.
Djuric, Z., Bird, C. E., Furumoto-Dawson, A., Rauscher, G. H., Ruffin IV, M. T., Stowe, R. P., ... & Masi, C. M. (2008). "Biomarkers of psychological stress in health disparities research". The open biomarkers journal, 1, 7.
Everly, G. S., & Lating, J. M. (2019). "The anatomy and physiology of the human stress response". In A clinical guide to the treatment of the human stress response (pp. 19-56). Springer, New York, NY.
Greco, A., Valenza, G., Lanata, A., Scilingo, E. P., & Citi, L. (2015). "cvxEDA: A convex optimization approach to electrodermal activity processing". IEEE Transactions on Biomedical Engineering, 63(4), 797-804.
McColl, D., Hong, A., Hatakeyama, N., Nejat, G., & Benhabib, B. (2016). "A survey of autonomous human affect detection methods for social robots engaged in natural HRI". Journal of Intelligent & Robotic Systems, 82(1), 101-133.
Rashid, N., Chen, L., Dautta, M., Jimenez, A., Tseng, P., & Al Faruque, M. A. (2021). "Feature Augmented Hybrid CNN for Stress Recognition Using Wrist-based Photoplethysmography Sensor". In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 2374-2377). IEEE.
Richard, L., Hurst, T., & Lee, J. (2019). "Lifetime exposure to abuse, current stressors, and health in federally qualified health center patients". Journal of Human Behavior in the Social Environment, 29(5), 593-607.
Samyoun, S., Mondol, A. S., & Stankovic, J. A. (2020). "Stress detection via sensor translation". In 2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS) (pp. 19-26). IEEE.
Schmidt, P., Reiss, A., Duerichen, R., Marberger, C., & Van Laerhoven, K. (2018). "Introducing wesad, a multimodal dataset for wearable stress and affect detection". In Proceedings of the 20th ACM international conference on multimodal interaction (pp. 400-408).
Selye, H. (1950). "Stress and the general adaptation syndrome". British medical journal, 1(4667), 1383.
Setz, C., Arnrich, B., Schumm, J., La Marca, R., Tröster, G., & Ehlert, U. (2009). "Discriminating stress from cognitive load using a wearable EDA device". IEEE Transactions on information technology in biomedicine, 14(2), 410-417.
Sun, F. T., Kuo, C., Cheng, H. T., Buthpitiya, S., Collins, P., & Griss, M. (2010). "Activity-aware mental stress detection using physiological sensors". In International conference on Mobile computing, applications, and services (pp. 282-301). Springer, Berlin, Heidelberg.
Vanderark, S. D., & Ely, D. (1993). "Cortisol, biochemical, and galvanic skin responses to music stimuli of different preference values by college students in biology and music". Perceptual and motor skills, 77(1), 227-234.
Von Dawans, B., Kirschbaum, C., & Heinrichs, M. (2011). "The Trier Social Stress Test for Groups (TSST-G): A new research tool for controlled simultaneous social stress exposure in a group format". Psychoneuroendocrinology, 36(4), 514-522.
Bobade, P., & Vani, M. (2020). "Stress detection with machine learning and deep learning using multimodal physiological data". In 2020 Second International Conference on Inventive Research in Computing Applications (ICIRCA) (pp. 51-57). IEEE.
Butler, G. (1993). "Definitions of stress". In Stress management in general practice (pp. 1-5). Royal College of General Practitioners.
Carneiro, D., Novais, P., Augusto, J. C., & Payne, N. (2017). "New methods for stress assessment and monitoring at the workplace". IEEE Transactions on Affective Computing, 10(2), 237-254.
Djuric, Z., Bird, C. E., Furumoto-Dawson, A., Rauscher, G. H., Ruffin IV, M. T., Stowe, R. P., ... & Masi, C. M. (2008). "Biomarkers of psychological stress in health disparities research". The open biomarkers journal, 1, 7.
Everly, G. S., & Lating, J. M. (2019). "The anatomy and physiology of the human stress response". In A clinical guide to the treatment of the human stress response (pp. 19-56). Springer, New York, NY.
Greco, A., Valenza, G., Lanata, A., Scilingo, E. P., & Citi, L. (2015). "cvxEDA: A convex optimization approach to electrodermal activity processing". IEEE Transactions on Biomedical Engineering, 63(4), 797-804.
McColl, D., Hong, A., Hatakeyama, N., Nejat, G., & Benhabib, B. (2016). "A survey of autonomous human affect detection methods for social robots engaged in natural HRI". Journal of Intelligent & Robotic Systems, 82(1), 101-133.
Rashid, N., Chen, L., Dautta, M., Jimenez, A., Tseng, P., & Al Faruque, M. A. (2021). "Feature Augmented Hybrid CNN for Stress Recognition Using Wrist-based Photoplethysmography Sensor". In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 2374-2377). IEEE.
Richard, L., Hurst, T., & Lee, J. (2019). "Lifetime exposure to abuse, current stressors, and health in federally qualified health center patients". Journal of Human Behavior in the Social Environment, 29(5), 593-607.
Samyoun, S., Mondol, A. S., & Stankovic, J. A. (2020). "Stress detection via sensor translation". In 2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS) (pp. 19-26). IEEE.
Schmidt, P., Reiss, A., Duerichen, R., Marberger, C., & Van Laerhoven, K. (2018). "Introducing wesad, a multimodal dataset for wearable stress and affect detection". In Proceedings of the 20th ACM international conference on multimodal interaction (pp. 400-408).
Selye, H. (1950). "Stress and the general adaptation syndrome". British medical journal, 1(4667), 1383.
Setz, C., Arnrich, B., Schumm, J., La Marca, R., Tröster, G., & Ehlert, U. (2009). "Discriminating stress from cognitive load using a wearable EDA device". IEEE Transactions on information technology in biomedicine, 14(2), 410-417.
Sun, F. T., Kuo, C., Cheng, H. T., Buthpitiya, S., Collins, P., & Griss, M. (2010). "Activity-aware mental stress detection using physiological sensors". In International conference on Mobile computing, applications, and services (pp. 282-301). Springer, Berlin, Heidelberg.
Vanderark, S. D., & Ely, D. (1993). "Cortisol, biochemical, and galvanic skin responses to music stimuli of different preference values by college students in biology and music". Perceptual and motor skills, 77(1), 227-234.
Von Dawans, B., Kirschbaum, C., & Heinrichs, M. (2011). "The Trier Social Stress Test for Groups (TSST-G): A new research tool for controlled simultaneous social stress exposure in a group format". Psychoneuroendocrinology, 36(4), 514-522.
Publicado
07/06/2022
Como Citar
MEDEIROS, Vinícius P.; CUNHA, Fagner; SANTOS, Eulanda M. dos; SOUTO, Eduardo.
Um Modelo de Aprendizado Profundo Multimodal para Classificação de Estresse Utilizando Sinais Obtidos por Dispositivos Vestíveis de Pulso. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 22. , 2022, Teresina.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 370-380.
ISSN 2763-8952.
DOI: https://doi.org/10.5753/sbcas.2022.222694.
