Um Modelo de Aprendizado Profundo Multimodal para Classificação de Estresse Utilizando Sinais Obtidos por Dispositivos Vestíveis de Pulso

• Vinícius P. Medeiros UFAM
• Fagner Cunha UFAM
• Eulanda M. dos Santos UFAM
• Eduardo Souto UFAM

DOI: https://doi.org/10.5753/sbcas.2022.222694

Abstract

The recent proliferation of wearable devices (e.g. smartphones and smartwatches) and their ability to measure various physiological signals creates an opportunity for continuous and unobtrusive monitoring of an individual's state of stress. With this in mind, we propose a new model for stress classification based on a convolutional neural network using data collected by wrist devices. We used the leave-one-subject-out (LOSO) validation to evaluate our model that reached an average accuracy rate of 95.67%, which is higher than most of the works in the literature.

References

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.