Connection between Biomedical Telemetry and Telemedicine

Nikita, Konstantina S.

doi:10.1002/9781118893715.ch14

Cited by 2 publications

(2 citation statements)

References 30 publications

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“…These devices include smart watches, fitness trackers, and smart glasses. As a direct consequence of this, IoMT is eventually accountable for advancing the fields of remote patient monitoring, intelligent prosthetics, telemedicine, and the treatment of chronic illnesses [22][23][24][25]. As a direct consequence of these advancements, we have entered a new era in which patient care is getting more individualised, early therapies are now within the realm of possibility, and healthcare is becoming simpler and more readily available to more people.…”

Section: Introductionmentioning

confidence: 99%

Security and Privacy in Machine Learning for IoHT and IoMT: A Review

Priyadarshi,

Gheisari

2024

Preprint

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The emergence of Internet of Things (IoT) devices is revolutionizing healthcare. This dynamic healthcare environment relies on Internet of Healthcare Things (IoHT) and Internet of Medical Things (IoMT) technologies. Economic, social, and technological opportunities from the IoHT are transforming healthcare systems. This article covers the history, present condition, and future prospects of IoHT, as well as its topologies, platforms, services, applications, market trends, and solution types. It examines security issues, requirements, and a threat taxonomy, studying smart healthcare privacy and security. It explores future research and the challenges IoHT-based solutions face. International health rules and regulations based on the IoT and their social and economic effects on long-term development are also examined. Integrating IoMT into healthcare infrastructures enhances scalability, efficiency, reliability, and accuracy. Through communication networks and data-processing algorithms, IoMT creates smart hardware and software platforms that enhance decision-making. IoMT devices' low resources raise privacy and security concerns. Security and privacy issues are organised by healthcare IoMT adoption in this study. We give an extensive attack taxonomy against the IoMT infrastructure, encompassing devices, security mechanisms, and their pros and cons. Furthermore, it describes the privacy and security requirements for any unique security solutions against IoMT's multiple attack vectors. This article explains the complicated difficulties, security concerns, and future research pathways needed to safeguard and ensure the long-term expansion of these game-changing technologies in the healthcare ecosystem.

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Section: Introductionmentioning

confidence: 99%

Security and Privacy in Machine Learning for IoHT and IoMT: A Review

Priyadarshi,

Gheisari

2024

Preprint

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“…to collect health related information (e.g., blood oxygen saturation, blood pressure, weight, glucose level, respiratory and heart rate, etc.) [17], [18] over an extended period of time and save as electronic health records (eHR).…”

Section: Introductionmentioning

confidence: 99%

Toward a Heterogeneous Mist, Fog, and Cloud-Based Framework for the Internet of Healthcare Things

Asif-Ur-Rahman

Afsana

Mahmud

et al. 2019

IEEE Internet Things J.

180

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Rapid developments in the fields of information and communication technology and microelectronics allowed seamless interconnection among various devices letting them to communicate with each other. This technological integration opened up new possibilities in many disciplines including healthcare and well-being. With the aim of reducing healthcare costs and providing improved and reliable services, several healthcare frameworks based on Internet of Healthcare Things (IoHT) have been developed. However, due to the critical and heterogeneous nature of healthcare data, maintaining high quality of service (QoS) -in terms of faster responsiveness and data-specific complex analytics -has always been the main challenge in designing such systems. Addressing these issues, this paper proposes a five-layered heterogeneous mist, fog, and cloud based IoHT framework capable of efficiently handling and routing (near-)real-time as well as offline/batch mode data. Also, by employing software defined networking and link adaptation based load balancing, the framework ensures optimal resource allocation and efficient resource utilization. The results, obtained by simulating the framework, indicate that the designed network via its various components can achieve high QoS, with reduced end-to-end latency and packet drop rate, which is essential for developing next generation e-healthcare systems.

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Connection between Biomedical Telemetry and Telemedicine

Cited by 2 publications

References 30 publications

Security and Privacy in Machine Learning for IoHT and IoMT: A Review

Security and Privacy in Machine Learning for IoHT and IoMT: A Review

Toward a Heterogeneous Mist, Fog, and Cloud-Based Framework for the Internet of Healthcare Things

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