Potential of Internet of Medical Things (IoMT) applications in building a smart healthcare system: A systematic review

Dwivedi, Ruby; Mehrotra, Divya; Chandra, Shaleen

doi:10.1016/j.jobcr.2021.11.010

Cited by 170 publications

(88 citation statements)

References 145 publications

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“…Eko is a company that makes digital health tools. They are based in the US and their tools assist health and clinicians providers in assessing cardiac complications associated with COVID-19 [ 96 , 97 ]. Eko makes it simpler for healthcare practitioners during ECG recordings to save, analyze, and communicate patient heart and lung sounds.…”

Section: Regulations and Procedures For Iot During Pandemicmentioning

confidence: 99%

IoT Adoption and Application for Smart Healthcare: A Systematic Review

Alrawashdeh

Keikhosrokiani

Belaton

et al. 2022

Sensors

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In general, the adoption of IoT applications among end users in healthcare is very low. Healthcare professionals present major challenges to the successful implementation of IoT for providing healthcare services. Many studies have offered important insights into IoT adoption in healthcare. Nevertheless, there is still a need to thoroughly review the effective factors of IoT adoption in a systematic manner. The purpose of this study is to accumulate existing knowledge about the factors that influence medical professionals to adopt IoT applications in the healthcare sector. This study reviews, compiles, analyzes, and systematically synthesizes the relevant data. This review employs both automatic and manual search methods to collect relevant studies from 2015 to 2021. A systematic search of the articles was carried out on nine major scientific databases: Google Scholar, Science Direct, Emerald, Wiley, PubMed, Springer, MDPI, IEEE, and Scopus. A total of 22 articles were selected as per the inclusion criteria. The findings show that TAM, TPB, TRA, and UTAUT theories are the most widely used adoption theories in these studies. Furthermore, the main perceived adoption factors of IoT applications in healthcare at the individual level are: social influence, attitude, and personal inattentiveness. The IoT adoption factors at the technology level are perceived usefulness, perceived ease of use, performance expectancy, and effort expectations. In addition, the main factor at the security level is perceived privacy risk. Furthermore, at the health level, the main factors are perceived severity and perceived health risk, respectively. Moreover, financial cost, and facilitating conditions are considered as the main factors at the environmental level. Physicians, patients, and health workers were among the participants who were involved in the included publications. Various types of IoT applications in existing studies are as follows: a wearable device, monitoring devices, rehabilitation devices, telehealth, behavior modification, smart city, and smart home. Most of the studies about IoT adoption were conducted in France and Pakistan in the year 2020. This systematic review identifies the essential factors that enable an understanding of the barriers and possibilities for healthcare providers to implement IoT applications. Finally, the expected influence of COVID-19 on IoT adoption in healthcare was evaluated in this study.

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Section: Regulations and Procedures For Iot During Pandemicmentioning

confidence: 99%

IoT Adoption and Application for Smart Healthcare: A Systematic Review

Alrawashdeh

Keikhosrokiani

Belaton

et al. 2022

Sensors

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“…The Internet of Things can be characterized as the pervasiveness of cyber-physical systems with communication and sensing capabilities, which have been widely implemented in the medical profession, and the Internet of Medical Things (IoMT) idea was formed (14). IoMT primarily employs mobile sensors to collect medically relevant human data, and then supports clinical diagnosis and treatment with good economy, usability, and access (15).…”

Section: Internet Of Medical Things (Iomt)mentioning

confidence: 99%

Artificial Intelligence and Medicine

Vanak

2022

Sci Insights

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The introduction of artificial intelligence (AI) has resulted in numerous technological advancements in the medical profession and a radical transformation of the old medical model. Artificial intelligence in medicine consists mostly of machine learning, deep learning, expert systems, intelligent robotics, the internet of medical things, and other prevalent and new AI technology. The primary applications of AI in the medical industry are intelligent screening, intelligent diagnosis, risk prediction, and supplemental treatment. Presently, medical AI has achieved significant advances, and big data quality management, new technology empowerment innovation, multi-domain knowledge integration, and personalized medical decision-making will exhibit greater growth potential in the clinical arena.

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“…IoT is emerging as one of the most important technologies, and it has gained ground globally, being integrated steadily with applications in every industry, including healthcare. Already, IoT devices have been utilized in healthcare systems for continuous blood glucose monitoring, diagnosing apnea, and transmitting vital laboratory data from home to the hospital, documenting heart rate, skin temperature, movement monitoring, monitoring general health conditions, nutritional status, and analyzing elderly or infected patients [ 12 , 13 , 14 , 15 , 16 ]. There is uncertainty regarding the IoT and its utility and impact since it is in the early stages of implementation [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

“…Dwivedi et al [ 13 ] systematically reviewed IoT applications in healthcare. Different technologies integrated with IoT are virtual reality, mixed reality, augmented reality, parallel fog, edge, cloud computing, 5G networking, big data visualization and analytics (BDVA), artificial intelligence, and blockchain.…”

Section: Introductionmentioning

confidence: 99%

A Systematic Review of Internet of Things in Clinical Laboratories: Opportunities, Advantages, and Challenges

Munir

Akbar

Ahmed

et al. 2022

Sensors

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The Internet of Things (IoT) is the network of physical objects embedded with sensors, software, electronics, and online connectivity systems. This study explores the role of IoT in clinical laboratory processes; this systematic review was conducted adhering to the PRISMA Statement 2020 guidelines. We included IoT models and applications across preanalytical, analytical, and postanalytical laboratory processes. PubMed, Cochrane Central, CINAHL Plus, Scopus, IEEE, and A.C.M. Digital library were searched between August 2015 to August 2022; the data were tabulated. Cohen’s coefficient of agreement was calculated to quantify inter-reviewer agreements; a total of 18 studies were included with Cohen’s coefficient computed to be 0.91. The included studies were divided into three classifications based on availability, including preanalytical, analytical, and postanalytical. The majority (77.8%) of the studies were real-tested. Communication-based approaches were the most common (83.3%), followed by application-based approaches (44.4%) and sensor-based approaches (33.3%) among the included studies. Open issues and challenges across the included studies included scalability, costs and energy consumption, interoperability, privacy and security, and performance issues. In this study, we identified, classified, and evaluated IoT applicability in clinical laboratory systems. This study presents pertinent findings for IoT development across clinical laboratory systems, for which it is essential that more rigorous and efficient testing and studies be conducted in the future.

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Potential of Internet of Medical Things (IoMT) applications in building a smart healthcare system: A systematic review

Cited by 170 publications

References 145 publications

IoT Adoption and Application for Smart Healthcare: A Systematic Review

IoT Adoption and Application for Smart Healthcare: A Systematic Review

Artificial Intelligence and Medicine

A Systematic Review of Internet of Things in Clinical Laboratories: Opportunities, Advantages, and Challenges

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