A Technological Monitoring Architecture for Academics' Mental and Physical Health
Resumo
Educational institutions are moving to a hybrid model that allows onsite and online classes. Students and teachers must adapt to these changes in the teaching and learning routine, leading them to stress and anxiety moments. This work proposes an architecture to assist academics in detecting these stressful moments during daily activities. The proposal uses smart bands, machine learning algorithms, and a smartphone app for environment monitoring. The evaluation was conducted by collecting real data from heart rate spikes and enriching it using the location information to send recommendations. The results show that it is possible to identify stressful moments by respecting the academics environment by monitoring their routine.
Palavras-chave:
mental health, stress detection, smart bands, machine learning, education
Referências
Anderson, C. (2015). Docker [software engineering]. Ieee Software, 32(3):102–c3.
Bamber, M. D. and Morpeth, E. (2018). Effects of mindfulness meditation on college student anxiety: a meta-analysis. Mindfulness, 10(2):203–214.
Bülow, M. W. (2022). Designing synchronous hybrid learning spaces: Challenges and opportunities. In Understanding Teaching-Learning Practice, pages 135–163. Springer International Publishing
Carroll, N. and Conboy, K. (2020). Normalising the “new normal”: Changing tech-driven work practices under pandemic time pressure. International Journal of Information Management, 55:102186
Carter, T., Pascoe, M., Bastounis, A., Morres, I. D., Callaghan, P., and Parker, A. G. (2021). The effect of physical activity on anxiety in children and young people: a systematic review and meta-analysis. Journal of Affective Disorders, 285:10–21.
Chaturvedi, K., Vishwakarma, D. K., and Singh, N. (2021). COVID-19 and its impact on education, social life and mental health of students: A survey. Children and Youth Services Review, 121:105866.
Di iorio Silva, G., Sergio, W. L., Ströele, V., and Dantas, M. A. (2021). Asap-academic support aid proposal for student recommendations. In International Conference on Advanced Information Networking and Applications (AINA-2021), pages 40–53.
Gorman, J. M. and Sloan, R. P. (2000). Heart rate variability in depressive and anxiety disorders. American heart journal, 140(4):S77–S83
Gustems-Carnicer, J., Calderón, C., and Calderón-Garrido, D. (2019). Stress, coping strategies and academic achievement in teacher education students. European Journal of Teacher Education, 42(3):375–390
Hall, G., Laddu, D. R., Phillips, S. A., Lavie, C. J., and Arena, R. (2021). A tale of two pandemics: How will covid-19 and global trends in physical inactivity and sedentary behavior affect one another? Progress in cardiovascular diseases, 64:108
Hamdan, K. M., Al-Bashaireh, A. M., Zahran, Z., Al-Daghestani, A., Samira, A.-H., and Shaheen, A. M. (2021). University students’ interaction, internet self-efficacy, self-regulation and satisfaction with online education during pandemic crises of covid-19 (sars-cov-2). International Journal of Educational Management
Hasanbasic, A., Spahic, M., Bosnjic, D., Mesic, V., Jahic, O., et al. (2019). Recognition of stress levels among students with wearable sensors. In 2019 18th International Symposium INFOTEH-JAHORINA (INFOTEH), pages 1–4. IEEE.
Kastornova, V. A. and Gerova, N. V. (2021). Use of hybrid learning in school education in france. In 2021 1st International Conference on Technology Enhanced Learning in Higher Education (TELE). IEEE
Kiran, M., Murphy, P., Monga, I., Dugan, J., and Baveja, S. S. (2015). Lambda architecture for cost-effective batch and speed big data processing. In 2015 IEEE International Conference on Big Data (Big Data), pages 2785–2792. IEEE
Klein, A. and Lehner, W. (2009). Representing data quality in sensor data streaming environments. Journal of Data and Information Quality (JDIQ), 1(2):1–28
Leite, D., Santos, H., Rodrigues, A., Monteiro, C., and Maciel, A. (2021). A hybrid learning approach for subjects on software development of automation systems, combining PBL, gamification and virtual reality. In Anais do XXXII Simpósio Brasileiro de Informática na Educação (SBIE 2021). Sociedade Brasileira de Computação - SBC
Li, Q., Li, Z., and Han, J. (2021). A hybrid learning pedagogy for surmounting the challenges of the COVID-19 pandemic in the performing arts education. Education and Information Technologies, 26(6):7635–7655
Lima, M. D. S. and Maciel, R. S. P. (2021). Practices and digital technological resources for remote education: an investigation of brazilian professor's profile. In Anais do XXXII Simpósio Brasileiro de Informática na Educação (SBIE 2021). Sociedade Brasileira de Computação - SBC
Melillo, P., Bracale, M., and Pecchia, L. (2011). Nonlinear heart rate variability features for real-life stress detection. case study: students under stress due to university examination. BioMedical Engineering OnLine, 10(1):96
Misra, R., McKean, M., West, S., and Russo, T. (2000). Academic stress of college students: Comparison of student and faculty perceptions. College Student Journal, 34(2)
Munir, A., Kansakar, P., and Khan, S. U. (2017). Ifciot: Integrated fog cloud iot: A novel architectural paradigm for the future internet of things. IEEE Consumer Electronics Magazine, 6(3):74–82
Pakhomova, T. O., Komova, O. S., Belia, V. V., Yivzhenko, Y. V., and Demidko, E. V. (2021). Transformation of the pedagogical process in higher education during the quarantine. Linguistics and Culture Review, 5(S2):215–230
Pascoe, M. C., Hetrick, S. E., and Parker, A. G. (2019). The impact of stress on students in secondary school and higher education. International Journal of Adolescence and Youth, 25(1):104–112.
Pitanga, F. J. G., Beck, C. C., and Pitanga, C. P. S. (2020). Physical activity and reducing sedentary behavior during the coronavirus pandemic. Arquivos brasileiros de cardiologia, 114:1058–1060.
Priya, A., Garg, S., and Tigga, N. P. (2020). Predicting anxiety, depression and stress in modern life using machine learning algorithms. Procedia Computer Science, 167:1258–1267
REIS, H. M., ALVARES, D., JAQUES, P. A., and ISOTANI, S. (2021). A proposal of model of emotional regulation in intelligent learning environments. Informatics in Education
Silva, G., Stroele, V., Dantas, M., and Campos, F. (2019). Hold up: Modelo de detecção e controle de emoções em ambientes acadêmicos. In Brazilian Symposium on Computers in Education (Simpósio Brasileiro de Informática na Educação-SBIE), volume 30, page 139
Sohail, N. (2013). Stress and academic performance among medical students. J Coll Physicians Surg Pak, 23(1):67–71.
Souza, A. P. d. S., Silva, M. R. M., Silva, A., Lira, P., Silva, J., Silva, M., et al. (2020). Anxiety symptoms in university professors during the covid-19 pandemic. Health Sci J, 14
Vaziri, H., Casper, W. J., Wayne, J. H., and Matthews, R. A. (2020). Changes to the work–family interface during the covid-19 pandemic: Examining predictors and implications using latent transition analysis. Journal of Applied Psychology, 105(10):1073
Verma, P. and Sood, S. K. (2018). A comprehensive framework for student stress monitoring in fog-cloud IoT environment: m-health perspective. Medical & Biological Engineering & Computing, 57(1):231–244
Vitasari, P., Wahab, M. N. A., Othman, A., Herawan, T., and Sinnadurai, S. K. (2010). The relationship between study anxiety and academic performance among engineering students. Procedia-Social and Behavioral Sciences, 8:490–497
Zaccaro, A., Piarulli, A., Laurino, M., Garbella, E., Menicucci, D., Neri, B., and Gemignani, A. (2018). How breath-control can change your life: A systematic review on psycho-physiological correlates of slow breathing. Frontiers in Human Neuroscience, 12.
Bamber, M. D. and Morpeth, E. (2018). Effects of mindfulness meditation on college student anxiety: a meta-analysis. Mindfulness, 10(2):203–214.
Bülow, M. W. (2022). Designing synchronous hybrid learning spaces: Challenges and opportunities. In Understanding Teaching-Learning Practice, pages 135–163. Springer International Publishing
Carroll, N. and Conboy, K. (2020). Normalising the “new normal”: Changing tech-driven work practices under pandemic time pressure. International Journal of Information Management, 55:102186
Carter, T., Pascoe, M., Bastounis, A., Morres, I. D., Callaghan, P., and Parker, A. G. (2021). The effect of physical activity on anxiety in children and young people: a systematic review and meta-analysis. Journal of Affective Disorders, 285:10–21.
Chaturvedi, K., Vishwakarma, D. K., and Singh, N. (2021). COVID-19 and its impact on education, social life and mental health of students: A survey. Children and Youth Services Review, 121:105866.
Di iorio Silva, G., Sergio, W. L., Ströele, V., and Dantas, M. A. (2021). Asap-academic support aid proposal for student recommendations. In International Conference on Advanced Information Networking and Applications (AINA-2021), pages 40–53.
Gorman, J. M. and Sloan, R. P. (2000). Heart rate variability in depressive and anxiety disorders. American heart journal, 140(4):S77–S83
Gustems-Carnicer, J., Calderón, C., and Calderón-Garrido, D. (2019). Stress, coping strategies and academic achievement in teacher education students. European Journal of Teacher Education, 42(3):375–390
Hall, G., Laddu, D. R., Phillips, S. A., Lavie, C. J., and Arena, R. (2021). A tale of two pandemics: How will covid-19 and global trends in physical inactivity and sedentary behavior affect one another? Progress in cardiovascular diseases, 64:108
Hamdan, K. M., Al-Bashaireh, A. M., Zahran, Z., Al-Daghestani, A., Samira, A.-H., and Shaheen, A. M. (2021). University students’ interaction, internet self-efficacy, self-regulation and satisfaction with online education during pandemic crises of covid-19 (sars-cov-2). International Journal of Educational Management
Hasanbasic, A., Spahic, M., Bosnjic, D., Mesic, V., Jahic, O., et al. (2019). Recognition of stress levels among students with wearable sensors. In 2019 18th International Symposium INFOTEH-JAHORINA (INFOTEH), pages 1–4. IEEE.
Kastornova, V. A. and Gerova, N. V. (2021). Use of hybrid learning in school education in france. In 2021 1st International Conference on Technology Enhanced Learning in Higher Education (TELE). IEEE
Kiran, M., Murphy, P., Monga, I., Dugan, J., and Baveja, S. S. (2015). Lambda architecture for cost-effective batch and speed big data processing. In 2015 IEEE International Conference on Big Data (Big Data), pages 2785–2792. IEEE
Klein, A. and Lehner, W. (2009). Representing data quality in sensor data streaming environments. Journal of Data and Information Quality (JDIQ), 1(2):1–28
Leite, D., Santos, H., Rodrigues, A., Monteiro, C., and Maciel, A. (2021). A hybrid learning approach for subjects on software development of automation systems, combining PBL, gamification and virtual reality. In Anais do XXXII Simpósio Brasileiro de Informática na Educação (SBIE 2021). Sociedade Brasileira de Computação - SBC
Li, Q., Li, Z., and Han, J. (2021). A hybrid learning pedagogy for surmounting the challenges of the COVID-19 pandemic in the performing arts education. Education and Information Technologies, 26(6):7635–7655
Lima, M. D. S. and Maciel, R. S. P. (2021). Practices and digital technological resources for remote education: an investigation of brazilian professor's profile. In Anais do XXXII Simpósio Brasileiro de Informática na Educação (SBIE 2021). Sociedade Brasileira de Computação - SBC
Melillo, P., Bracale, M., and Pecchia, L. (2011). Nonlinear heart rate variability features for real-life stress detection. case study: students under stress due to university examination. BioMedical Engineering OnLine, 10(1):96
Misra, R., McKean, M., West, S., and Russo, T. (2000). Academic stress of college students: Comparison of student and faculty perceptions. College Student Journal, 34(2)
Munir, A., Kansakar, P., and Khan, S. U. (2017). Ifciot: Integrated fog cloud iot: A novel architectural paradigm for the future internet of things. IEEE Consumer Electronics Magazine, 6(3):74–82
Pakhomova, T. O., Komova, O. S., Belia, V. V., Yivzhenko, Y. V., and Demidko, E. V. (2021). Transformation of the pedagogical process in higher education during the quarantine. Linguistics and Culture Review, 5(S2):215–230
Pascoe, M. C., Hetrick, S. E., and Parker, A. G. (2019). The impact of stress on students in secondary school and higher education. International Journal of Adolescence and Youth, 25(1):104–112.
Pitanga, F. J. G., Beck, C. C., and Pitanga, C. P. S. (2020). Physical activity and reducing sedentary behavior during the coronavirus pandemic. Arquivos brasileiros de cardiologia, 114:1058–1060.
Priya, A., Garg, S., and Tigga, N. P. (2020). Predicting anxiety, depression and stress in modern life using machine learning algorithms. Procedia Computer Science, 167:1258–1267
REIS, H. M., ALVARES, D., JAQUES, P. A., and ISOTANI, S. (2021). A proposal of model of emotional regulation in intelligent learning environments. Informatics in Education
Silva, G., Stroele, V., Dantas, M., and Campos, F. (2019). Hold up: Modelo de detecção e controle de emoções em ambientes acadêmicos. In Brazilian Symposium on Computers in Education (Simpósio Brasileiro de Informática na Educação-SBIE), volume 30, page 139
Sohail, N. (2013). Stress and academic performance among medical students. J Coll Physicians Surg Pak, 23(1):67–71.
Souza, A. P. d. S., Silva, M. R. M., Silva, A., Lira, P., Silva, J., Silva, M., et al. (2020). Anxiety symptoms in university professors during the covid-19 pandemic. Health Sci J, 14
Vaziri, H., Casper, W. J., Wayne, J. H., and Matthews, R. A. (2020). Changes to the work–family interface during the covid-19 pandemic: Examining predictors and implications using latent transition analysis. Journal of Applied Psychology, 105(10):1073
Verma, P. and Sood, S. K. (2018). A comprehensive framework for student stress monitoring in fog-cloud IoT environment: m-health perspective. Medical & Biological Engineering & Computing, 57(1):231–244
Vitasari, P., Wahab, M. N. A., Othman, A., Herawan, T., and Sinnadurai, S. K. (2010). The relationship between study anxiety and academic performance among engineering students. Procedia-Social and Behavioral Sciences, 8:490–497
Zaccaro, A., Piarulli, A., Laurino, M., Garbella, E., Menicucci, D., Neri, B., and Gemignani, A. (2018). How breath-control can change your life: A systematic review on psycho-physiological correlates of slow breathing. Frontiers in Human Neuroscience, 12.
Publicado
16/11/2022
Como Citar
LEÃO, Wagno Sérgio; SILVA, Gabriel Di iorio; STRÖELE, Victor; DANTAS, Mário; CAMPOS, Fernanda; BRAGA, Regina; DAVID, José Maria N..
A Technological Monitoring Architecture for Academics' Mental and Physical Health. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 33. , 2022, Manaus.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 846-858.
DOI: https://doi.org/10.5753/sbie.2022.224716.
