A Framework of Intelligent Mental Health Monitoring in Smart Cities and Societies

References

• B. B. Bhavani, and L. V. Raghuveer, “, Ed. Smart healthcare system for psychological disorders in smart cities,” in Advanced Controllers for Smart Cities, Vol. 65, F. Al-Turjman, and N. Gowthaman, Ed. EAI/Springer Innovations in Communication and Computing. Cham: Springer, 2021, pp. 65–76.
   Google Scholar
• J. Tian, and L. Gao, “Using data monitoring algorithms to physiological indicators in motion based on Internet of things in smart city,” Sustain. Cities Soc., Vol. 67, p. 102727, 2021.
   Web of Science ®Google Scholar
• H. Zhu, L. Shen, and Y. Ren, “How can smart city shape a happier life? The mechanism for developing a happiness driven smart city,” Sustain. Cities Soc., Vol. 80, p. 103791, 2022.
   Web of Science ®Google Scholar
• M. Mouton, A. Ducey, J. Green, L. Hardcastle, S. Hoffman, M. Leslie, and M. Rock, “Towards ‘smart cities’ as ‘healthy cities’: Health equity in a digital age,” Can. J. Public Health, Vol. 110, no. 3, pp. 331–334, 2019.
   PubMed Web of Science ®Google Scholar
• C. Huang, et al., “Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China,” Lancet, Vol. 395, no. 10223, pp. 497–506, 2020.
   PubMed Web of Science ®Google Scholar
• H. A. Rothan, and S. N. Byrareddy, “The epidemiology and pathogenesis of coronavirus disease (COVID-19) outbreak,” J. Autoimmun., Vol. 109, p. 102433, 2020.
   PubMed Web of Science ®Google Scholar
• World Health Organization, Depression and other common mental disorders: Global health estimates (No. WHO/MSD/MER/2017.2). World Health Organization, 2017.
   Google Scholar
• World Health Organization, Fact sheets on sustainable development goals: Health targets. Mental Health (May 2018).
   Google Scholar
• https://ncrb.gov.in/sites/default/files/Chapter-2-Suicides_2019.pdf
   Google Scholar
• https://www.who.int/news-room/fact-sheets/detail/suicide
   Google Scholar
• M. A. Rahman, M. S. Hossain, A. J. Showail, N. A. Alrajeh, and M. F. Alhamid, “A secure, private, and explainable IoHT framework to support sustainable health monitoring in a smart city,” Sustain. Cities Soc., Vol. 72, p. 103083, 2021.
   Web of Science ®Google Scholar
• S. M. Nagarajan, G. G. Deverajan, P. Chatterjee, W. Alnumay, and U. Ghosh, “Effective task scheduling algorithm with deep learning for Internet of Health Things (IoHT) in sustainable smart cities,” Sustain. Cities Soc., Vol. 71, p. 102945, 2021.
   Web of Science ®Google Scholar
• M. M. Kamruzzaman, I. Alrashdi, and A. Alqazzaz, “New opportunities, challenges, and applications of edge-AI for connected healthcare in internet of medical things for smart cities,” J. Healthc. Eng., Vol. 2022, pp. 1–14, Hindawi, 2022.
   Web of Science ®Google Scholar
• K. Ćosić, S. Popović, M. Šarlija, and I. Kesedžić, “Impact of human disasters and COVID-19 pandemic on mental health: Potential of digital psychiatry,” Psychiatr. Danub., Vol. 32, no. 1, pp. 25–31, 2020.
   PubMed Web of Science ®Google Scholar
• S. Trautmann, J. Rehm, and H. U. Wittchen, “The economic costs of mental disorders,” EMBO Rep., Vol. 17, no. 9, pp. 1245–1249, 2016.
   PubMed Web of Science ®Google Scholar
• E. Reguly. “More than 100 million Europeans in lockdown as Spain announces emergency quarantine and Italian virus cases surge,” The Globe and Mail (March 15, 2020).
   Google Scholar
• P. Carlsson-Szlezak, M. Reeves, and P. Swartz, “Understanding the economic shock of coronavirus,” Harv. Bus. Rev., Vol. 27, pp. 4–5, 2020.
   Google Scholar
• M. O’Sullivan. “Fast recovery or great depression? Three scenarios for the coronavirus economic crisis,” Forbes, March 29, 2020.
   Google Scholar
• C. Weller. “What we know about the economic impact of the coronavirus and How that should guide policy,” Forbes, 2020.
   Google Scholar
• F. K. Ayittey, M. K. Ayittey, N. B. Chiwero, J. S. Kamasah, and C. Dzuvor, “Economic impacts of Wuhan 2019-nCoV on China and the world,” J. Med. Virol., Vol. 92, no. 5, p. 473, 2020.
   PubMed Web of Science ®Google Scholar
• World Health Organization, Coronavirus disease (COVID-19) outbreak – technical guidance – EUROPE: Mental health and COVID-19. 2020.
   Google Scholar
• J. Shigemura, R. J. Ursano, J. C. Morganstein, M. Kurosawa, and D. M. Benedek, “Public responses to the novel 2019 coronavirus (2019-nCoV) in Japan: Mental health consequences and target populations,” Psychiatry Clin. Neurosci., Vol. 74, no. 4, p. 281, 2020.
   PubMed Web of Science ®Google Scholar
• Y. Huang, and N. Zhao, “Generalized anxiety disorder, depressive symptoms and sleep quality during COVID-19 outbreak in China: A web-based cross-sectional survey,” Psychiatry Res., Vol. 288, p. 112954, 2020.
   PubMed Web of Science ®Google Scholar
• J. Lai, et al., “Factors associated with mental health outcomes among health care workers exposed to coronavirus disease 2019,” JAMA Network Open, Vol. 3, no. 3, pp. e203976–e203976, 2020.
   PubMed Web of Science ®Google Scholar
• S. M. Lee, W. S. Kang, A. R. Cho, T. Kim, and J. K. Park, “Psychological impact of the 2015 MERS outbreak on hospital workers and quarantined hemodialysis patients,” Compr. Psychiatry, Vol. 87, pp. 123–127, 2018.
   PubMed Web of Science ®Google Scholar
• M. Billy, “The influence of dynamic organizations and the application of digital innovations to educational institutions in the world during the COVID-19 pandemic,” Available at SSRN 3588233. 2020.
   Google Scholar
• UNESCO, “School closures caused by Coronavirus (Covid-19),” 2020.
   Google Scholar
• N. Nikolakakis, E. Dragioti, N. Paritsis, K. Tsamakis, N. G. Christodoulou, and E. N. Rizos, “Association between happiness and psychopathology in an elderly regional rural population in Crete,” Psychiatriki., Vol. 30, no. 4, pp. 299–310, 2019.
   PubMedGoogle Scholar
• R. Mansour, K. Tsamakis, E. Rizos, G. Perera, J. Das-Munshi, R. Stewart, and C. Mueller, “Late-life depression in people from ethnic minority backgrounds: Differences in presentation and management,” J. Affect. Disord., Vol. 264, pp. 340–347, 2020.
   PubMed Web of Science ®Google Scholar
• Y. Yang, W. Li, Q. Zhang, L. Zhang, T. Cheung, and Y. T. Xiang, “Mental health services for older adults in China during the COVID-19 outbreak,” Lancet Psychiatry, Vol. 7, no. 4, p. e19, 2020.
   PubMed Web of Science ®Google Scholar
• M. Gautam, A. Thakrar, E. Akinyemi, and G. Mahr, “Current and future challenges in the delivery of mental healthcare during COVID-19,” SN Compr. Clin. Med., Vol. 2, no. 7, pp. 865–870, 2020.
   PubMedGoogle Scholar
• M. Policy Brief, UN Secretary-General Policy, Covid-19 and the Need for Action on Mental Health. New York, NY: United Nations, 2020.
   Google Scholar
• P. Brief, “The impact of COVID-19 on older persons,” United Nations (2020).
   Google Scholar
• K. H. Abdulkareem, M. A. Mohammed, A. Salim, M. Arif, O. Geman, D. Gupta, and A. Khanna, “Realizing an effective COVID-19 diagnosis system based on machine learning and IOT in smart hospital environment,” IEEE Internet Things J., Vol. 8, no. 21, pp. 15919–15928, 2021.
   PubMed Web of Science ®Google Scholar
• M. N. Islam, T. T. Inan, S. Rafi, S. S. Akter, I. H. Sarker, and A. N. Islam, “A systematic review on the use of AI and ML for fighting the COVID-19 pandemic,” IEEE Trans. Artif. Intell., Vol. 1, no. 3, pp. 258–270, 2020.
   PubMedGoogle Scholar
• S. Tiwari, P. Chanak, and S. K. Singh, “A review of the machine learning algorithms for COVID-19 case analysis,” IEEE Trans. Artif. Intell., Vol. 4, no. 1, pp. 44–59, 2022.
   PubMedGoogle Scholar
• Y. Oh, S. Park, and J. C. Ye, “Deep learning COVID-19 features on CXR using limited training data sets,” IEEE Trans. Med. Imaging, Vol. 39, no. 8, pp. 2688–2700, 2020.
   PubMed Web of Science ®Google Scholar
• S. Guhathakurata, S. Saha, S. Kundu, A. Chakraborty, and J. S. Banerjee, “South Asian countries are less fatal concerning COVID-19: A fact-finding procedure integrating machine learning & multiple criteria decision-making (MCDM) technique,” J. Inst. Eng. (India): B, Vol. 102, pp. 1249–1263, 2021.
   Google Scholar
• S. Cohen, T. Kamarck, and R. Mermelstein, “A global measure of perceived stress,” J. Health Soc. Behav., Vol. 24, no. 4, pp. 385–396, 1983.
   PubMed Web of Science ®Google Scholar
• J. Chattopadhyay, S. Kundu, A. Chakraborty, and J. S. Banerjee, “Facial expression recognition for human computer interaction,” in International Conference on Computational Vision and Bio Inspired Computing, S. Smys, A.M. Iliyasu, R. Bestak, and F. Shi, Ed. Cham: Springer, 2018, pp. 1181–1192.
   Google Scholar
• L. A. Zadeh, “The concept of a linguistic variable and its application to approximate reasoning—I,” Inf. Sci. (Ny), Vol. 8, no. 3, pp. 199–249, 1975.
   Web of Science ®Google Scholar
• E. Hisdal, “The IF THEN ELSE statement and interval-valued fuzzy sets of higher type,” Int. J. Man Mach. Stud., Vol. 15, no. 4, pp. 385–455, 1981.
   Google Scholar
• https://www.kaggle.com/datasets/osmi/mental-health-in-tech-2016
   Google Scholar
• J. Maughan. Machine Learning with Orange, 2019. Available: https://medium.com/@jackmaughan_50251/machine-learning-with-orange-8bc1a541a1d7/
   Google Scholar
• Orange Visual Programming. https://orange-visual-programming.readthedocs.io/widgets/data/rank.html/
   Google Scholar
• T. Dolev, S. Zubedat, Z. Brand, B. Bloch, E. Mader, O. Blondheim, and A. Avital, “Physiological parameters of mental health predict the emergence of post-traumatic stress symptoms in physicians treating COVID-19 patients,” Transl. Psychiatry., Vol. 11, no. 1, pp. 1–9, 2021.
   PubMed Web of Science ®Google Scholar
• M. Yalçın, et al., “Psychiatric emergency visit trends and characteristics in a mental health epicenter in Istanbul during COVID-19 lockdown,” Soc. Psychiatry Psychiatr. Epidemiol., Vol. 56, pp. 2299–2310, 2021.
   PubMed Web of Science ®Google Scholar
• M. Grocke-Dewey, et al., “Examining the relationship between physical activity and mental health during the COVID-19 pandemic across five US States,” Prev. Med. Rep., Vol. 24, p. 101537, 2021.
   PubMedGoogle Scholar
• C. Summers, P. Wu, and A. J. Taylor, “Supporting mental health during COVID-19 using a digital behaviour change intervention: An open-label, single-arm, pre-post intervention research study,” JMIR Form. Res., Vol. 5, no. 10, pp. 1–12, 2021.
   Google Scholar
• D. Gordon, et al., “Developing an explanatory theoretical model for engagement with a web-based mental health platform: Results of a mixed methods study,” BMC Psychiatry, Vol. 21, no. 1, pp. 1–15, 2021.
   PubMed Web of Science ®Google Scholar