Smart Technology Applications for Supporting Medicine and Healthcare after the COVID-19 Pandemic

A special issue of Healthcare (ISSN 2227-9032). This special issue belongs to the section "Artificial Intelligence in Medicine".

Deadline for manuscript submissions: closed (31 January 2023) | Viewed by 37684

Special Issue Editor

Special Issue Information

Dear Colleagues, 

With the increasing popularity of vaccination, many countries and regions are gradually lifting restrictions on isolation periods and travel. The COVID-19 pandemic seems to be entering its final stages; however, the impacts of the COVID-19 pandemic will not disappear quickly. For the restoration of normal life, application of smart technologies are necessary. The smart technology applications which will support healthcare after the COVID-19 pandemic are different from those used before the pandemic. Some smart technologies will be used more commonly, while others have lost public attention.

With the end stages of the COVID-19 pandemic in sight, an increasingly strong motivation for applying smart technologies is the drive to restore freedom of mobility. The widespread use of vaccine passports is an clear example. Only those travelers who have been vaccinated are permitted entry by some countries and regions. In addition, to promote safe cross-border travel, global establishments are using websites and apps for booking rooms, seats, or restaurants, which consider the requirements for vaccination in tourist destinations. However, there are some regions that have released their control over the movement of people, with relaxed restriction surrounding vaccine passports allowing populations to return to their pre-pandemic life.

In addition, the demand for some smart technology applications may disappear. For example, after widespread vaccination, the need to avoid human contact using smart technologies, such as robots and drones, is no longer as present as it has been. In addition, the costs of widespread deployment of robots are infeasible for long-term use. For these reasons, uses of robots and drones may fade after the pandemic. In addition, some hospital staff have expressed concerns surrounding the potential of being replaced by robots.

Furthermore, the performances of some existing smart technology applications are not sufficiently high. For example, the blood oxygen level detected by a smart bracelet is usually lower than the actual value. In addition, smart bracelets, smart watches, and smart body temperature monitors (i.e., infrared cameras/thermometers) are subject to the same limitation—that is, a patient is often contagious two days before the onset of obvious symptoms, and pre-symptomatic or asymptomatic patients cause more than half of infections. During the COVID-19 pandemic, most users can tolerate this problem; however, after the pandemic has passed, users of these applications will have higher expectations for the effectiveness of smart technology applications.

This Special Issue aims to summarize and collate the technical details of smart technology applications in medicine and in healthcare after the COVID-19 pandemic. These details will hold great interest for researchers in medicine, healthcare, technology management, ambient intelligence, information engineering, artificial intelligence, and computational intelligence, as well as for practicing managers and engineers. This Special Issue features a balance between state-of-the-art research and practical applications—providing a forum for researchers and practitioners to review and disseminate quality research work on smart technology applications for medicine and healthcare, and to present critical issues for further development.

Prof. Dr. Tin-Chih Chen
Guest Editor

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Keywords

  • smart robot (drone)
  • wearable devices
  • smart phone
  • smart bracelet
  • applications
  • location-based services
  • smart surveillance system
  • smart temperature monitoring system
  • 3D printer
  • others to medical and health care after the COVID-19 pandemic

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Published Papers (6 papers)

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Research

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16 pages, 3216 KiB  
Article
Development and Testing of the Smart Healthcare Prototype System through COVID-19 Patient Innovation
by Po-Chih Chiu, Kuo-Wei Su, Chao-Hung Wang, Cong-Wen Ruan, Zong-Peng Shiao, Chien-Han Tsao and Hsin-Hsin Huang
Healthcare 2023, 11(6), 847; https://doi.org/10.3390/healthcare11060847 - 13 Mar 2023
Cited by 2 | Viewed by 2056
Abstract
Since the outbreak of the novel coronavirus disease 2019 (COVID-19), the epidemic has gradually slowed down in various countries and people’s lives have gradually returned to normal. To monitor the spread of the epidemic, studies discussing the design of related healthcare information systems [...] Read more.
Since the outbreak of the novel coronavirus disease 2019 (COVID-19), the epidemic has gradually slowed down in various countries and people’s lives have gradually returned to normal. To monitor the spread of the epidemic, studies discussing the design of related healthcare information systems have been increasing recently. However, these studies might not consider the aspect of user-centric design when developing healthcare information systems. This study examined these innovative technology applications and rapidly built prototype systems for smart healthcare through a systematic literature review and a study of patient innovation. The design guidelines for the Smart Healthcare System (SHS) were then compiled through an expert review process. This will provide a reference for future research and similar healthcare information system development. Full article
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14 pages, 2043 KiB  
Article
Genetic Algorithm for Solving the No-Wait Three-Stage Surgery Scheduling Problem
by Yang-Kuei Lin and Chen-Hao Yen
Healthcare 2023, 11(5), 739; https://doi.org/10.3390/healthcare11050739 - 2 Mar 2023
Cited by 5 | Viewed by 1920
Abstract
In this research, we consider a deterministic three-stage operating room surgery scheduling problem. The three successive stages are pre-surgery, surgery, and post-surgery. The no-wait constraint is considered among the three stages. Surgeries are known in advance (elective). Multiple resources are considered throughout the [...] Read more.
In this research, we consider a deterministic three-stage operating room surgery scheduling problem. The three successive stages are pre-surgery, surgery, and post-surgery. The no-wait constraint is considered among the three stages. Surgeries are known in advance (elective). Multiple resources are considered throughout the surgical process: PHU (preoperative holding unit) beds in the first stage, ORs (operating rooms) in the second stage, and PACU (post-anesthesia care unit) beds in the third stage. The objective is to minimize the makespan. The makespan is defined as the maximum end time of the last activity in stage 3. Minimizing the makespan not only maximizes the utilization of ORs but also improves patient satisfaction by allowing treatments to be delivered to patients in a timely manner. We proposed a genetic algorithm (GA) for solving the operating room scheduling problem. Randomly generated problem instances were tested to evaluate the performance of the proposed GA. The computational results show that overall, the GA deviated from the lower bound (LB) by 3.25% on average, and the average computation time of the GA was 10.71 s. We conclude that the GA can efficiently find near-optimal solutions to the daily three-stage operating room surgery scheduling problem. Full article
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14 pages, 846 KiB  
Article
Emotion Detection Based on Pupil Variation
by Ching-Long Lee, Wen Pei, Yu-Cheng Lin, Anders Granmo and Kang-Hung Liu
Healthcare 2023, 11(3), 322; https://doi.org/10.3390/healthcare11030322 - 21 Jan 2023
Cited by 5 | Viewed by 2843
Abstract
Emotion detection is a fundamental component in the field of Affective Computing. Proper recognition of emotions can be useful in improving the interaction between humans and machines, for instance, with regard to designing effective user interfaces. This study aims to understand the relationship [...] Read more.
Emotion detection is a fundamental component in the field of Affective Computing. Proper recognition of emotions can be useful in improving the interaction between humans and machines, for instance, with regard to designing effective user interfaces. This study aims to understand the relationship between emotion and pupil dilation. The Tobii Pro X3-120 eye tracker was used to collect pupillary responses from 30 participants exposed to content designed to evoke specific emotions. Six different video scenarios were selected and presented to participants, whose pupillary responses were measured while watching the material. In total, 16 data features (8 features per eye) were extracted from the pupillary response distribution during content exposure. Through logistical regression, a maximum of 76% classification accuracy was obtained through the measurement of pupillary response in predicting emotions classified as fear, anger, or surprise. Further research is required to precisely calculate pupil size variations in relation to emotionally evocative input in affective computing applications. Full article
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13 pages, 2386 KiB  
Article
Efficacy of Aromatherapy at Relieving the Work-Related Stress of Nursing Staff from Various Hospital Departments during COVID-19
by Chi-Lun Hung, Yun-Ling Lin, Chin-Mei Chou and Ching-Ju Wang
Healthcare 2023, 11(2), 157; https://doi.org/10.3390/healthcare11020157 - 4 Jan 2023
Cited by 3 | Viewed by 4045
Abstract
This study aimed to evaluate the efficacy of aromatherapy in relieving the stress of nursing staff working in different departments during COVID-19. A total of 26 nursing staff from Taiwan were recruited for this study. Bergamot essential oil was diffused for over a [...] Read more.
This study aimed to evaluate the efficacy of aromatherapy in relieving the stress of nursing staff working in different departments during COVID-19. A total of 26 nursing staff from Taiwan were recruited for this study. Bergamot essential oil was diffused for over a four-week period in four different hospital departments. We assessed heart rate variability indicators, Nurse Stress Checklist, and Copenhagen Burnout Inventory before and after the intervention. The results of the analysis showed that during a high workload period, aromatherapy had no significant effect on regulating physical stress. Subjective measurements showed a significant impact on work concern and personal fatigue. Moreover, there were large differences among the four departments; the aromatherapy treatment had a weak effect on those with a heavy workload, whereas those with a lighter workload showed a stronger effect. Finally, this study provides practical results about aromatherapy stress reduction applied during the pandemic on first-line medical staff. Full article
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16 pages, 410 KiB  
Article
Increase the Number of Views and Shares of COVID-19 Videos: Content Relevance and Emotional Consistency with Virus Variant Topics
by Jingfang Liu, Caiying Lu and Shuangjinhua Lu
Healthcare 2023, 11(1), 119; https://doi.org/10.3390/healthcare11010119 - 30 Dec 2022
Viewed by 1733
Abstract
(1) Background: The coronavirus variants have posed serious challenges for the prevention and control of the COVID-19 pandemic. Individuals selectively watch and forward videos that help them reduce the damage caused by the virus. Therefore, the factors influencing video viewing and sharing in [...] Read more.
(1) Background: The coronavirus variants have posed serious challenges for the prevention and control of the COVID-19 pandemic. Individuals selectively watch and forward videos that help them reduce the damage caused by the virus. Therefore, the factors influencing video viewing and sharing in the context of the COVID-19 pandemic caused by virus variation must be explored. (2) Method: Based on a combination of uncertainty reduction theory and functional emotion theory, this paper designed hypotheses regarding how content relevance and emotional consistency affect video views and shares. We used the support vector machine (SVM) classification algorithm to measure the content relevance between videos and virus variant topics. We performed sentiment analysis of video text to evaluate the emotional consistency between videos and virus variant topics. Then, we used empirical analysis to build the model. (3) Results: The trained SVM classifier was effective in judging whether the video text was related to virus variant topics (F = 88.95%). The content relevance between COVID-19 videos and virus variant topics was generally low. The results showed that the higher the content relevance, the more views (IRR = 1.005, p = 0.017) and shares (IRR = 1.008, p = 0.009) the video received. Individuals were more willing to view (IRR = 1.625, p < 0.001) and share (IRR = 1.761, p < 0.001) COVID-19 videos with high emotional consistency with virus variant topics. (4) Conclusions: The results of empirical analysis showed that content relevance and emotional consistency between videos and virus variant topics significantly positively impacted video views and shares. The trained SVM classifier can support public health departments in monitoring and assessing the COVID-19 pandemic. Our study provides management advice while helping individuals reduce harm and inform next-step decisions. Full article
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Review

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32 pages, 1744 KiB  
Review
IoT-Based Healthcare-Monitoring System towards Improving Quality of Life: A Review
by Suliman Abdulmalek, Abdul Nasir, Waheb A. Jabbar, Mukarram A. M. Almuhaya, Anupam Kumar Bairagi, Md. Al-Masrur Khan and Seong-Hoon Kee
Healthcare 2022, 10(10), 1993; https://doi.org/10.3390/healthcare10101993 - 11 Oct 2022
Cited by 98 | Viewed by 23888
Abstract
The Internet of Things (IoT) is essential in innovative applications such as smart cities, smart homes, education, healthcare, transportation, and defense operations. IoT applications are particularly beneficial for providing healthcare because they enable secure and real-time remote patient monitoring to improve the quality [...] Read more.
The Internet of Things (IoT) is essential in innovative applications such as smart cities, smart homes, education, healthcare, transportation, and defense operations. IoT applications are particularly beneficial for providing healthcare because they enable secure and real-time remote patient monitoring to improve the quality of people’s lives. This review paper explores the latest trends in healthcare-monitoring systems by implementing the role of the IoT. The work discusses the benefits of IoT-based healthcare systems with regard to their significance, and the benefits of IoT healthcare. We provide a systematic review on recent studies of IoT-based healthcare-monitoring systems through literature review. The literature review compares various systems’ effectiveness, efficiency, data protection, privacy, security, and monitoring. The paper also explores wireless- and wearable-sensor-based IoT monitoring systems and provides a classification of healthcare-monitoring sensors. We also elaborate, in detail, on the challenges and open issues regarding healthcare security and privacy, and QoS. Finally, suggestions and recommendations for IoT healthcare applications are laid down at the end of the study along with future directions related to various recent technology trends. Full article
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