Intelligent Healthcare: Integration of Emerging Technologies and Internet of Things for Humanity

Dang, Van Anh; Quy, Vu Khanh; Nguyen, Van-Hau; Nguyen, Tien Van; Nguyen, Dinh C.

doi:10.3390/s23094200

Cited by 27 publications

(12 citation statements)

References 93 publications

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“…Digital exclusion, which is the lack of access to or ability to use information and communication technologies, is also common among the elderly [ 5 ]. In the context of the rapid development of the Internet, the act of seeking health information and receiving medical services online has become increasingly common [ 6 , 7 ], but many older adults do not have access to the internet or the skills to use it [ 8 ], this can lead to negative health outcomes, including cognitive impairment. Therefore, this study is dedicated to investigate the relationship between digital exclusion and cognitive impairment.…”

Section: Introductionmentioning

confidence: 99%

Digital exclusion and cognitive impairment in older people: findings from five longitudinal studies

Wang,

Wu,

Duan

et al. 2024

BMC Geriatr

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Objectives Older people are more likely to have digital exclusion, which is associated with poor health. This study investigated the relationship between digital exclusion and cognitive impairment in older adults from 23 countries across five longitudinal surveys. Design and measurements Digital exclusion is defined as self-reported non-use of the Internet. We assessed cognitive impairment on three dimensions: orientation, memory, and executive function. We used generalized estimation equations fitting binary logistic regression with exchangeable correlations to study the relationship between digital exclusion and cognitive impairment, and apply the minimum sufficiently adjusted set of causally directed acyclic graphs as the adjusted variable. Setting and participants We pooled a nationally representative sample of older adults from five longitudinal studies, including the China Health and Retirement Longitudinal study (CHARLS), the English Longitudinal Study of Ageing (ELSA), the Health and Retirement Study (HRS), the Mexican Health and Ageing Study (MHAS) and the Survey of Health, Ageing and Retirement in European (SHARE). Results We included 62,413 participants from five longitudinal studies. Digital exclusion varied by country, ranging from 21.69% (SHARE) in Denmark to 97.15% (CHARLS) in China. In the original model, digital exclusion was significantly associated with cognitive impairment in all five studies. In the adjusted model, these associations remained statistically significant: CHARLS (Odds ratio [OR] = 2.81, 95% confidence interval [CI] 1.84–4.28, ELSA (1.92 [1.70–2.18]), HRS(2.48[2.28–2.71), MHAS (1.92 [1.74–2.12]), and SHARE (2.60 [2.34–2.88]). Conclusion Our research shows that a significant proportion of older people suffer from digital exclusion, especially in China. Digital exclusion was positively correlated with cognitive impairment. These findings suggest that digital inclusion could be an important strategy to improve cognitive function and reduce the risk of cognitive impairment in older adults.

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Section: Introductionmentioning

confidence: 99%

Digital exclusion and cognitive impairment in older people: findings from five longitudinal studies

Wang,

Wu,

Duan

et al. 2024

BMC Geriatr

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“…For instance, it was essential to routinely check patients' oxygen levels during the COVID-19 pandemic. These difficulties drove researchers and organizations to create intelligent IoHT devices that continuously track patients' oxygen levels [32].…”

Section: Monitoring Of Oxygen Levelsmentioning

confidence: 99%

Privacy-Enhancing Technologies in Federated Learning for the Internet of Healthcare Things: A Survey

et al. 2023

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Advancements in wearable medical devices using the IoT technology are shaping the modern healthcare system. With the emergence of the Internet of Healthcare Things (IoHT), efficient healthcare services can be provided to patients. Healthcare professionals have effectively used AI-based models to analyze the data collected from IoHT devices to treat various diseases. Data must be processed and analyzed while avoiding privacy breaches, in compliance with legal rules and regulations, such as the HIPAA and GDPR. Federated learning (FL) is a machine learning-based approach allowing multiple entities to train an ML model collaboratively without sharing their data. It is particularly beneficial in healthcare, where data privacy and security are substantial concerns. Even though FL addresses some privacy concerns, there is still no formal proof of privacy guarantees for IoHT data. Privacy-enhancing technologies (PETs) are tools and techniques designed to enhance the privacy and security of online communications and data sharing. PETs provide a range of features that help protect users’ personal information and sensitive data from unauthorized access and tracking. This paper comprehensively reviews PETs concerning FL in the IoHT scenario and identifies several key challenges for future research.

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“…It is expected that, by overcoming these challenges [ 30 ], digital twins will be widely embraced to facilitate connected care and alter healthcare management in the future. The Internet of Things, artificial intelligence, machine learning, deep learning, and cloud computing are among the essential technologies for designing fully functional intelligent digital twins [ 31 , 32 , 33 , 34 , 35 , 36 ]. According to IBM, “ the Internet of Things is a network of physical devices, vehicles, appliances, and other physical objects that are embedded with sensors, software, and network connectivity that allows them to collect and share data ”.…”

Section: The Digital Twin Concept Within Healthcarementioning

confidence: 99%

Intelligent Digital Twins for Personalized Migraine Care

Gazerani

2023

JPM

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Intelligent digital twins closely resemble their real-life counterparts. In health and medical care, they enable the real-time monitoring of patients, whereby large amounts of data can be collected to produce actionable information. These powerful tools are constructed with the aid of artificial intelligence, machine learning, and deep learning; the Internet of Things; and cloud computing to collect a diverse range of digital data (e.g., from digital patient journals, wearable sensors, and digitized monitoring equipment or processes), which can provide information on the health conditions and therapeutic responses of their physical twins. Intelligent digital twins can enable data-driven clinical decision making and advance the realization of personalized care. Migraines are a highly prevalent and complex neurological disorder affecting people of all ages, genders, and geographical locations. It is ranked among the top disabling diseases, with substantial negative personal and societal impacts, but the current treatment strategies are suboptimal. Personalized care for migraines has been suggested to optimize their treatment. The implementation of intelligent digital twins for migraine care can theoretically be beneficial in supporting patient-centric care management. It is also expected that the implementation of intelligent digital twins will reduce costs in the long run and enhance treatment effectiveness. This study briefly reviews the concept of digital twins and the available literature on digital twins for health disorders such as neurological diseases. Based on these, the potential construction and utility of digital twins for migraines will then be presented. The potential and challenges when implementing intelligent digital twins for the future management of migraines are also discussed.

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Intelligent Healthcare: Integration of Emerging Technologies and Internet of Things for Humanity

Cited by 27 publications

References 93 publications

Digital exclusion and cognitive impairment in older people: findings from five longitudinal studies

Digital exclusion and cognitive impairment in older people: findings from five longitudinal studies

Privacy-Enhancing Technologies in Federated Learning for the Internet of Healthcare Things: A Survey

Intelligent Digital Twins for Personalized Migraine Care

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