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Smart Technology Applications in Healthcare Before, During, and After the COVID-19 Pandemic

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Sustainable Smart Healthcare

Part of the book series: SpringerBriefs in Applied Sciences and Technology ((BRIEFSAPPLSCIENCES))

Abstract

This chapter compares smart healthcare applications before, during, and after the COVID-19 pandemic. A smart healthcare application can be judged as sustainable if it was already widely used before the COVID-19 pandemic and is also prevalent after the pandemic. In contrast, if a smart healthcare application does not survive after the COVID-19 pandemic, it is not sustainable. To analyze this, smart technology applications in healthcare before the COVID-19 pandemic are divided into direct and indirect smart healthcare applications. Then the features of smart healthcare applications at this stage are summarized. Data analysis techniques applicable at this stage are also introduced. Subsequently, the challenges posed by the COVID-19 pandemic to the applications of smart technologies in healthcare are listed. To address these challenges, new smart healthcare technology applications have been proposed at this stage. The characteristics of such novel smart healthcare applications are discussed with the support of selected cases from the literature. Data analysis techniques applicable at this stage are also introduced. Finally, smart technology applications in healthcare post-COVID-19 pandemic are discussed, which are mainly for returning to normal life. Other novel smart healthcare applications are yet to be proposed. For this purpose, the features of such novel smart technology applications are discussed.

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References

  1. T. Chen, A fuzzy parallel processing scheme for enhancing the effectiveness of a dynamic just-in-time location-aware service system. Entropy 16, 2001–2022 (2014)

    Article  Google Scholar 

  2. M. Jordan, What is ‘smart’ technology? (2011). http://knowit.co.nz/2011/08/what-is-smart-technology

  3. J. Markoff, Google Cars drive themselves, in traffic (2010). http://www.nytimes.com/2010/10/10/science/10google.html?_r=0

  4. K. Michael, M.G. Michael, The social and behavioural implications of location-based services. J. Location Based Services 5(3–4), 121–137 (2011)

    Article  Google Scholar 

  5. D. Zhou, B. Wang, S.M. Rahimi, X. Wang, A study of recommending locations on location-based social network by collaborative filtering. Lect. Notes Comput. Sci. 7310, 255–266 (2012)

    Article  Google Scholar 

  6. H. Gao, J. Tang, X. Hu, H. Liu, Exploring temporal effects for location recommendation on location-based social networks, in Proceedings of the 7th ACM Conference on Recommender Systems (2013), pp. 93–100

    Google Scholar 

  7. T. Chen, M.C. Chiu, Smart technologies for assisting the life quality of persons in a mobile environment: a review. J. Ambient. Intell. Humaniz. Comput. 9, 319–327 (2018)

    Article  Google Scholar 

  8. K.W. Smith, N.E. Avis, S.F. Assmann, Distinguishing between quality of life and health status in quality of life research: a meta-analysis. Qual. Life Res. 8(5), 447–459 (1999)

    Article  Google Scholar 

  9. G. Demiris, M.J. Rantz, M.A. Aud, K.D. Marek, H.W. Tyrer, M. Skubic, A.A. Hussam, Older adults’ attitudes towards and perceptions of ‘smart home’ technologies: a pilot study. Med. Inform. Internet Med. 29(2), 87–94 (2004)

    Article  Google Scholar 

  10. L. Shu, Y. Yu, W. Chen, H. Hua, Q. Li, J. Jin, X. Xu, Wearable emotion recognition using heart rate data from a smart bracelet. Sensors 20(3), 718 (2020)

    Article  Google Scholar 

  11. G. Cho, S. Lee, J. Cho, Review and reappraisal of smart clothing. Int. J. Human-Comp. Interaction 25(6), 582–617 (2009)

    Article  Google Scholar 

  12. M. Shweta, P. Tanvi, S. Poonam, M. Nilashree, Multipurpose smart bag. Procedia Comp. Sci. 79, 77–84 (2016)

    Article  Google Scholar 

  13. Y.C. Lin, T. Chen, A multibelief analytic hierarchy process and nonlinear programming approach for diversifying product designs: smart backpack design as an example. Proc. Inst. Mech. Eng. Part B: J. Eng. Manuf. 234(6–7), 1044–1056 (2020)

    Article  Google Scholar 

  14. H.-C. Wu, T.-C.T. Chen, C.-H. Huang, Y.-C. Shi, Comparing built-in power banks for a smart backpack design using an auto-weighting fuzzy-weighted-intersection FAHP approach. Mathematics 8(10), 1759 (2020)

    Article  Google Scholar 

  15. A. Al-Refaie, T. Chen, M. Judeh, Optimal operating room scheduling for normal and unexpected events in a smart hospital. Oper. Res. Int. J. 18, 579–602 (2018)

    Article  Google Scholar 

  16. S. Warren, R.L. Craft, J.T. Bosma, Designing smart health care technology into the home of the future, in Workshops on Future Medical Devices: Home Care Technologies for the 21st Century (1999)

    Google Scholar 

  17. P. Treleaven, J. Wells, 3D body scanning and healthcare applications. Computer 40(7), 28–34 (2007)

    Article  Google Scholar 

  18. R.A. Khan, A.S.K. Pathan, The state-of-the-art wireless body area sensor networks: a survey. Int. J. Distrib. Sens. Netw. 14(4), 1550147718768994 (2018)

    Article  Google Scholar 

  19. S.B. Baker, W. Xiang, I. Atkinson, Internet of things for smart healthcare: technologies, challenges, and opportunities. IEEE Access 5, 26521–26544 (2017)

    Article  Google Scholar 

  20. S. Ali, R.P. Singh, M. Javaid, A. Haleem, H. Pasricha, R. Suman, J. Karloopia, A review of the role of smart wireless medical sensor network in COVID-19. J. Indus. Integr. Manage. 5(04), 413–425 (2020)

    Article  Google Scholar 

  21. K.J. Hsu, H.E. Lee, Y.M. Wu, S.J. Lan, S.T. Huang, Y.Y. Yen, Masticatory factors as predictors of oral health-related quality of life among elderly people in Kaohsiung City, Taiwan. Qual. Life Res. 23, 1395–1405 (2014)

    Article  Google Scholar 

  22. T.H. Välimäki, J.A. Martikainen, K. Hongisto, S. Väätäinen, H. Sintonen, A.M. Koivisto, Impact of Alzheimer’s disease on the family caregiver’s long-term quality of life: results from an ALSOVA follow-up study. Qual. Life Res. 25, 687–697 (2016)

    Article  Google Scholar 

  23. K. Orru, H. Orru, M. Maasikmets, R. Hendrikson, M. Ainsaar, Well-being and environmental quality: does pollution affect life satisfaction? Qual. Life Res. 25, 699–705 (2016)

    Article  Google Scholar 

  24. S. Moonie, X. Huang, D.A. Sterling, Quality of life estimation with structural equation modeling in school aged children with asthma. Glob. Health Govern. 3(1), 1 (2009)

    Google Scholar 

  25. T. Chen, Ubiquitous multicriteria clinic recommendation system. J. Med. Syst. 40, 1–11 (2016)

    Article  Google Scholar 

  26. T.C.T. Chen, Ubiquitous clinic recommendation by predicting a patient’s preferences. Electron. Commer. Res. Appl. 23, 14–23 (2017)

    Article  Google Scholar 

  27. T. Chen, Y.-C. Wang, Recommending suitable smart technology applications to support mobile healthcare after the COVID-19 pandemic using a fuzzy approach. Healthcare 9(11), 1461 (2021)

    Article  Google Scholar 

  28. A. Burlea-Schiopoiu, K. Ferhati, The managerial implications of the key performance indicators in healthcare sector: a cluster analysis. Healthcare 9, 19 (2020)

    Article  Google Scholar 

  29. I. Shah, Fighting COVID-19 with police patrol robots and drones (2021). https://www.police.gov.sg/media-room/features/fighting-covid-19-with-police-patrol-robots-and-drones

  30. Z. Huang, X. Huang, A study on the application of voice interaction in automotive human machine interface experience design. AIP Conf. Proc. 1955, 040074 (2018)

    Article  Google Scholar 

  31. F. Longo, A. Padovano, S. Umbrello, Value-oriented and ethical technology engineering in industry 5.0: a human-centric perspective for the design of the factory of the future. Appl. Sci. 10, 4182 (2020)

    Google Scholar 

  32. H. Guo, Y. Meng, S. Chi, P. Ding, Design of human-machine interaction system based on Android mobile phone gesture and voice control. Nanjing Xinxi Gongcheng Daxue Xuebao 11, 216–220 (2019)

    Google Scholar 

  33. M. Periša, T.M. Kuljanić, I. Cvitić, P. Kolarovszki, Conceptual model for informing user with innovative smart wearable device in industry 4.0. Wirel. Netw. 27, 1615–1626 (2021)

    Google Scholar 

  34. G. Nichols, Disinfecting robots to fight coronavirus run into travel bans (2021). https://www.zdnet.com/article/disinfecting-robots-to-fight-coronavirus-run-into-travel-bans/

  35. S. Bian, B. Zhou, P. Lukowicz, Social distance monitor with a wearable magnetic field proximity sensor. Sensors 20, 5101 (2020)

    Article  Google Scholar 

  36. S. Wray, UK council’s beach crowd management app to be scaled nationally (2021). https://cities-today.com/ukcouncils-beach-crowd-management-app-to-be-scaled-nationally/

  37. S.S. Kim, J. Kim, F. Badu-Baiden, M. Giroux, Y. Choi, Preference for robot service or human service in hotels? Impacts of the COVID-19 pandemic. Int. J. Hosp. Manag. 93, 102795 (2021)

    Article  Google Scholar 

  38. A. Kulkarni, A. Vishwanath, C. Shah, Implementing a real-time, AI-based, face mask detector application for COVID-19 (2021). https://developer.nvidia.com/blog/implementing-a-real-time-ai-based-face-mask-detector-application-for-covid-19/

  39. R. Collado-Borrell, V. Escudero-Vilaplana, C. Villanueva-Bueno, A. Herranz-Alonso, M. Sanjurjo-Saez, Features and functionalities of smartphone apps related to COVID-19: systematic search in app stores and content analysis. J. Med. Internet Res. 22(8), e20334 (2020)

    Article  Google Scholar 

  40. T. Chen, C.-W. Lin, A FGM-decomposition fuzzy MCDM method for choosing diversified smart technology applications for supporting mobile health care amid and after the COVID-19 pandemic. Appl. Soft Comput. 121, 108758 (2022)

    Article  Google Scholar 

  41. D. Stone, L. Michalkova, V. Machova, Machine and deep learning techniques, body sensor networks, and Internet of Things-based smart healthcare systems in COVID-19 remote patient monitoring. Am. J. Med. Res. 9(1), 97–112 (2022)

    Article  Google Scholar 

  42. V. Bhardwaj, R. Joshi, A.M. Gaur, IoT-based smart health monitoring system for COVID-19. SN Computer Science 3(2), 137 (2022)

    Article  Google Scholar 

  43. O. Taiwo, A.E. Ezugwu, Smart healthcare support for remote patient monitoring during covid-19 quarantine. Inform. Med. Unlocked 20, 100428 (2020)

    Article  Google Scholar 

  44. M.M. Khan, S. Mehnaz, A. Shaha, M. Nayem, S. Bourouis, IoT-based smart health monitoring system for COVID-19 patients. Comput. Math. Methods Med. 2021, 8591036 (2021)

    Article  Google Scholar 

  45. G. Sageena, M. Sharma, A. Kapur, Evolution of smart healthcare: telemedicine during COVID-19 pandemic. J. Inst. Eng. (India): Ser. B 102, 1319–1324 (2021)

    Google Scholar 

  46. A.M. Joshi, U.P. Shukla, S.P. Mohanty, Smart healthcare for diabetes during COVID-19. IEEE Cons. Electron. Mag. 10(1), 66–71 (2020)

    Article  Google Scholar 

  47. N. Nasser, Q. Emad-ul-Haq, M. Imran, A. Ali, I. Razzak, A. Al-Helali, A smart healthcare framework for detection and monitoring of COVID-19 using IoT and cloud computing. Neural Comput. Appl., 1–15 (2021)

    Google Scholar 

  48. T.C.T. Chen, Applications of XAI for forecasting in the manufacturing domain, in Explainable Artificial Intelligence (XAI) in Manufacturing: Methodology, Tools, and Applications (2023), pp. 13–50

    Google Scholar 

  49. World Health Organization, WHO coronavirus (COVID-19) dashboard (2023). https://covid19.who.int/

  50. D. Yetman, Are rapid COVID-19 test results reliable? (2022). https://www.healthline.com/health/how-accurate-are-rapid-covid-tests#summary

  51. M. Ennafiri, T. Mazri, Internet of things for smart healthcare: a review on a potential IOT based system and technologies to control COVID-19 pandemic. Inno. Smart Cities Appl. 4, 1256–1269 (2021)

    Google Scholar 

  52. S.A. Alanazi, M.M. Kamruzzaman, M. Alruwaili, N. Alshammari, S.A. Alqahtani, A. Karime, Measuring and preventing COVID-19 using the SIR model and machine learning in smart health care. J. Healthc. Eng. 2020, 8857346 (2020)

    Article  Google Scholar 

  53. H.W. Hethcote, The mathematics of infectious diseases. SIAM Rev. 42(4), 599–653 (2000)

    Article  Google Scholar 

  54. T.C.T. Chen, H.C. Wu, K.W. Hsu, A fuzzy analytic hierarchy process-enhanced fuzzy geometric mean-fuzzy technique for order preference by similarity to ideal solution approach for suitable hotel recommendation amid the COVID-19 pandemic. Digit. Health 8, 20552076221084456 (2022)

    Google Scholar 

  55. T. Chen, Y.C. Lin, A fuzzy back propagation network ensemble with example classification for lot output time prediction in a wafer fab. Appl. Soft Comput. 9(2), 658–666 (2009)

    Article  Google Scholar 

  56. Y.-C. Lin, T. Chen, An intelligent system for assisting personalized COVID-19 vaccination location selection: Taiwan as an example. Digit. Health 8, 20552076221109064 (2022)

    Google Scholar 

  57. Y.C. Lin, Y.C. Wang, T.C.T. Chen, H.F. Lin, Evaluating the suitability of a smart technology application for fall detection using a fuzzy collaborative intelligence approach. Mathematics 7(11), 1097 (2019)

    Article  Google Scholar 

  58. T. Chen, Y.-C. Lin, M.-C. Chiu, Approximating alpha-cut operations approach for effective and efficient fuzzy analytic hierarchy process analysis. Appl. Soft Comput. 85, 105855 (2019)

    Article  Google Scholar 

  59. T.B. Brakenhoff, B. Franks, B.M. Goodale, J. van de Wijgert, S. Montes, D. Veen, E.K. Fredslund, T. Rispens, L. Risch, A.V. Dowling et al., A prospective, randomized, single-blinded, crossover trial to investigate the effect of a wearable device in addition to a daily symptom diary for the remote early detection of SARS-CoV-2 infections (COVID-RED): a structured summary of a study protocol for a randomized controlled trial. Trials 22, 1–5 (2021)

    Article  Google Scholar 

  60. T. Mishra, M. Wang, A.A. Metwally, G.K. Bogu, A.W. Brooks, A. Bahmani, A. Alavi, A. Celli, E. Higgs, O. Dagan-Rosenfeld et al., Pre-symptomatic detection of COVID-19 from smartwatch data. Nat. Biomed. Eng. 2020(4), 1208–1220 (2020)

    Article  Google Scholar 

  61. Y.-C. Lin, T. Chen, Type-II fuzzy approach with explainable artificial intelligence for nature-based leisure travel destination selection amid the COVID-19 pandemic. Digit. Health 8, 20552076221106320 (2022)

    Google Scholar 

  62. M.F. Bashir, B. Ma, L. Shahzad, A brief review of socio-economic and environmental impact of Covid-19. Air Qual. Atmos. Health 13, 1403–1409 (2020)

    Article  Google Scholar 

  63. H.-C. Wu, Y.-C. Wang, T. Chen, Assessing and comparing COVID-19 intervention strategies using a varying partial-consensus fuzzy collaborative intelligence approach. Mathematics 8, 1725 (2020)

    Article  Google Scholar 

  64. D.S.W. Ting, L. Carin, V. Dzau, T.Y. Wong, Digital technology and COVID-19. Nat. Med. 26(4), 459–461 (2020)

    Article  Google Scholar 

  65. T. Chen, C.-W. Lin, Smart and automation technologies for ensuring the long-term operation of a factory amid the COVID-19 pandemic: an evolving fuzzy assessment approach. Int. J. Adv. Manuf. Technol. 111, 3545–3558 (2020)

    Article  Google Scholar 

  66. T. Chen, M.-C. Chiu, Evaluating the sustainability of a smart technology application in healthcare after the COVID-19 pandemic: a hybridizing subjective and objective fuzzy group decision-making approach with XAI. Digit. Health 8, 20552076221136380 (2022)

    Google Scholar 

  67. Research and Markets, Mobile health (mHealth) market—growth, trends, COVID-19 impact, and forecasts (2021–2026) (2021). https://www.researchandmarkets.com/reports/4520220/mobile-health-mhealth-market-growth-trends

  68. P. Heijmans, Singapore PM pushes for living with COVID, without the fear (2021). https://www.bloomberg.com/news/articles/2021-10-09/singapore-premier-pushes-for-living-with-covid-without-the-fear

  69. M.A. Hall, D.M. Studdert, “Vaccine passport” certification—policy and ethical considerations. New Engl. J. Med. 385(11), e32(2021) (2021)

    Google Scholar 

  70. D.C. Nguyen, Q.V. Pham, P.N. Pathirana, M. Ding, A. Seneviratne, Z. Lin, O. Dobre, W.J. Hwang, Federated learning for smart healthcare: a survey. ACM Comput. Surv. 55(3), 1–37 (2022)

    Article  Google Scholar 

  71. Y.-C. Wang, T.-C.T. Chen, Analyzing the impact of COVID-19 vaccination requirements on travelers’ selection of hotels using a fuzzy multi-criteria decision-making approach. Healthc. Anal. 2, 100064 (2022)

    Article  Google Scholar 

  72. T. Chen, Obtaining the optimal cache document replacement policy for the caching system of an EC website. Eur. J. Oper. Res. 181(2), 828–841 (2007)

    Article  Google Scholar 

  73. S.D. Sierra Marín, D. Gomez-Vargas, N. Céspedes, M. Múnera, F. Roberti, P. Barria, S. Ramamoorthy, M. Becker, R. Carelli, C.A. Cifuentes, Expectations and perceptions of healthcare professionals for robot deployment in hospital environments during the COVID-19 pandemic. Front. Robot. AI 8, 612746 (2021)

    Google Scholar 

  74. R. Suhartina, T. Abuzairi, Pulse oximeter monitoring bracelet for COVID-19 patient using seeeduino. Jurnal Ilmiah Teknik Elektro Komputer dan Informatika 7(1), 81–87 (2021)

    Article  Google Scholar 

  75. T. Chen, Forecasting the yield of a semiconductor product with a collaborative intelligence approach. Appl. Soft Comput. 13, 1552–1560 (2013)

    Article  Google Scholar 

  76. M.-C. Chiu, T. Chen, A ubiquitous healthcare system of 3D printing facilities for making dentures: application of type-II fuzzy logic. Digit. Health 8, 20552076221092540 (2022)

    Google Scholar 

  77. T.C.T. Chen, Quality control in a 3D printing-based ubiquitous manufacturing system, in 3D Printing and Ubiquitous Manufacturing (2020), pp. 83–95

    Google Scholar 

  78. Y.C. Wang, T. Chen, M.-C. Chiu, An improved explainable artificial intelligence tool in healthcare for hospital recommendation. Healthc. Anal. 3, 100147 (2023)

    Article  Google Scholar 

  79. Y.-C. Wang, T. Chen, A partial-consensus posterior-aggregation FAHP method—supplier selection problem as an example. Mathematics 7(2), 179 (2019)

    Article  Google Scholar 

  80. T. Chen, Y.C. Wang, A two-stage explainable artificial intelligence approach for classification-based job cycle time prediction. Int. J. Adv. Manuf. Technol. 123, 2031–2042 (2022)

    Article  Google Scholar 

  81. R.K. Solanki, A.S. Rajawat, A.R. Gadekar, M.E. Patil, Building a conversational chatbot using machine learning: towards a more intelligent healthcare application, in Handbook of Research on Instructional Technologies in Health Education and Allied Disciplines (2023), pp. 285–309

    Google Scholar 

  82. T. Chen, Y.C. Wang, An agent-based fuzzy collaborative intelligence approach for precise and accurate semiconductor yield forecasting. IEEE Trans. Fuzzy Syst. 22(1), 201–211 (2013)

    Article  Google Scholar 

  83. T. Chen, A hybrid fuzzy and neural approach with virtual experts and partial consensus for DRAM price forecasting. Int. J. Inno. Comput. Inf. Control 8(1), 583–597 (2012)

    Google Scholar 

  84. T. Chen, Applying a fuzzy and neural approach for forecasting the foreign exchange rate, in Computer Engineering: Concepts, Methodologies, Tools and Applications (2012), pp. 412–425

    Google Scholar 

  85. K. Ren, W. Zhang, Y. Rong, H. Zhang, Y. Yu, J. Wang, User response learning for directly optimizing campaign performance in display advertising, in Proceedings of the 25th ACM International Conference on Information and Knowledge Management (2016), pp. 679–688

    Google Scholar 

  86. T. Chen, A tailored non-linear fluctuation smoothing rule for semiconductor manufacturing factory scheduling. Proc. Inst. Mech. Eng. Part I: J. Syst. Control Eng. 223(2), 149–160 (2009)

    Google Scholar 

  87. T. Chen, Y.C. Wang, A nonlinear scheduling rule incorporating fuzzy-neural remaining cycle time estimator for scheduling a semiconductor manufacturing factory—a simulation study. Int. J. Adv. Manuf. Technol. 45, 110–121 (2009)

    Article  Google Scholar 

  88. H. Firdaus, S.I. Hassan, H. Kaur, A comparative survey of machine learning and meta-heuristic optimization algorithms for sustainable and smart healthcare. Afr. J. Comput. 11(4), 1–17 (2018)

    Google Scholar 

  89. T.C.T. Chen, K. Honda, Introduction to fuzzy collaborative forecasting systems, in Fuzzy Collaborative Forecasting and Clustering: Methodology, System Architecture, and Applications (2020), pp. 1–8

    Google Scholar 

  90. T.-C.T. Chen, Type-II fuzzy collaborative intelligence for assessing cloud manufacturing technology applications. Robot. Comp. Integr. Manuf. 78, 102399 (2022)

    Article  Google Scholar 

  91. P. Siirtola, Continuous stress detection using the sensors of commercial smartwatch, in Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers (2019), pp. 1198–1201

    Google Scholar 

  92. T. Chen, Y.C. Wang, H.C. Wu, Analyzing the impact of vaccine availability on alternative supplier selection amid the COVID-19 pandemic: a cFGM-FTOPSIS-FWI approach. Healthcare 9(1), 71 (2021)

    Article  Google Scholar 

  93. T. Chen, W.A. Chaovalitwongse, M.J. O’grady, K. Honda, Editorial: smart technologies for improving the quality of mobile health care. Health Care Manage. Sci. 23, 171–172 (2020)

    Google Scholar 

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    Tin-Chih Toly Chen

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Chen, TC.T. (2023). Smart Technology Applications in Healthcare Before, During, and After the COVID-19 Pandemic. In: Sustainable Smart Healthcare. SpringerBriefs in Applied Sciences and Technology. Springer, Cham. https://doi.org/10.1007/978-3-031-37146-2_2

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