Biomedical IoT: Enabling Technologies, Architectural Elements, Challenges, and Future Directions

Aledhari, Mohammed; Razzak, Rehma; Qolomany, Basheer; Al-Fuqaha, Ala; Saeed, Fahad

doi:10.1109/access.2022.3159235

Cited by 44 publications

(23 citation statements)

References 227 publications

(283 reference statements)

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“…For example, simple resonance or frequency shift implants are possible. 732 Important to note is also that, because of these simple networks, latency can be kept low (see Sections 9 "Organ Interfaces" and 10 "Infrastructure Integration"), which may be a requirement for real-time applications that necessitate precision such as neural stimulation, 107 brain−computer interfaces, 733 and prosthesis control. 734 On-body fully connected mesh networks (see Figure 24aii) refers to a communication architecture where multiple nodes form a mesh network directly in the human body, allowing individual nodes to communicate with each other, exchange data, and collaborate to provide enhanced sensing capabilities.…”

Section: Multinodal Systemsmentioning

confidence: 99%

Wireless Battery-free and Fully Implantable Organ Interfaces

Bhatia,

Hanna,

Stuart

et al. 2024

Chem. Rev.

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Advances in soft materials, miniaturized electronics, sensors, stimulators, radios, and battery-free power supplies are resulting in a new generation of fully implantable organ interfaces that leverage volumetric reduction and soft mechanics by eliminating electrochemical power storage. This device class offers the ability to provide high-fidelity readouts of physiological processes, enables stimulation, and allows control over organs to realize new therapeutic and diagnostic paradigms. Driven by seamless integration with connected infrastructure, these devices enable personalized digital medicine. Key to advances are carefully designed material, electrophysical, electrochemical, and electromagnetic systems that form implantables with mechanical properties closely matched to the target organ to deliver functionality that supports high-fidelity sensors and stimulators. The elimination of electrochemical power supplies enables control over device operation, anywhere from acute, to lifetimes matching the target subject with physical dimensions that supports imperceptible operation. This review provides a comprehensive overview of the basic building blocks of battery-free organ interfaces and related topics such as implantation, delivery, sterilization, and user acceptance. State of the art examples categorized by organ system and an outlook of interconnection and advanced strategies for computation leveraging the consistent power influx to elevate functionality of this device class over current battery-powered strategies is highlighted.

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Section: Multinodal Systemsmentioning

confidence: 99%

Wireless Battery-free and Fully Implantable Organ Interfaces

Bhatia,

Hanna,

Stuart

et al. 2024

Chem. Rev.

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“…Another advantage of using wearable IoT devices in predictive healthcare is improving the quality of early disease and fault detection in medical centres. In [12], they present a review of various biomedical IoT devices that raise the quality of diagnosis in healthcare services. The survey includes wearable sensors as one of the leading technologies that enable advancements in predictive healthcare IoT.…”

Section: A Benefits Of Using Wearable Iot Devices In Healthcarementioning

confidence: 99%

Federated Learning and Blockchain-Enabled Fog-IoT Platform for Wearables in Predictive Healthcare

Baucas

Spachos

Plataniotis

2023

IEEE Trans. Comput. Soc. Syst.

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Over the years, the popularity and usage of wearable Internet of Things (IoT) devices in several healthcare services are increased. Among the services that benefit from the usage of such devices is predictive analysis, which can improve early diagnosis in e-health. However, due to the limitations of wearable IoT devices, challenges in data privacy, service integrity, and network structure adaptability arose. To address these concerns, we propose a platform using federated learning and private blockchain technology within a fog-IoT network. These technologies have privacy-preserving features securing data within the network. We utilized the fog-IoT network's distributive structure to create an adaptive network for wearable IoT devices. We designed a testbed to examine the proposed platform's ability to preserve the integrity of a classifier. According to experimental results, the introduced implementation can effectively preserve a patient's privacy and a predictive service's integrity. We further investigated the contributions of other technologies to the security and adaptability of the IoT network. Overall, we proved the feasibility of our platform in addressing significant security and privacy challenges of wearable IoT devices in predictive healthcare through analysis, simulation, and experimentation.

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“…In recent years, wearable devices are becoming a potential candidate for the hub of IoT and WBANs [6]. Wearable devices have become famous for health monitoring tools since they can collect data from human body biosensors and transmit vital data while moving [7].…”

Section: Introductionmentioning

confidence: 99%

Distributed Energy-Efficient Clustering and Routing for Wearable IoT Enabled Wireless Body Area Networks

2023

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Recently, the wearable internet of things (WIoT) has brought a new dimension of connectivity to wireless body area networks (WBANs). For instance, the WIoT provides valuable functions, such as collecting, analyzing, and transmitting data for real-time health monitoring of medical services. However, designing a clustering and routing protocol is challenging because WIoT attributes are subject to high interference in dense deployment, social mobility, and limited energy. In a WIoT-enabled WBAN, cooperative control is the fundamental function of clustering and routing. Cluster-based routing protocols are preferred for WBAN because of their scalability. However, one-hop neighbor-based clustering approaches do not ensure connectivity and reachability owing to node mobility. The existing two-hop-based clustering protocols are mostly centralized-based approaches, which are unsuitable for dynamic WBANs. In this paper, we propose a distributed energy-efficient two-hop-based clustering and routing protocol (DECR) targeting WIoT-enabled WBAN. In DECR, in the cluster formation phase, each node obtains the information of its neighbor nodes within the two-hop range. We utilize the modified grey-wolf optimization algorithm for the cluster head (CH) selection and routing optimization. Node connectivity and residual energy were jointly considered when determining the CH in each cluster. We also developed an analytical model to determine the optimal number of clusters by considering intra-and inter-cluster transmission distances to reduce the overall transmission distance and number of transmissions. Finally, we proposed a routing algorithm to ensure energy-efficient packet delivery from CH to sink. Our simulation outcomes revealed that the proposed DECR significantly outperforms the existing clustering and routing protocols in various performance metrics.INDEX TERMS Wearable internet of things, clustering, two-hop range, distributed, cluster head, energyefficiency, grey wolf optimization, routing, wireless body area network (WBAN).

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Biomedical IoT: Enabling Technologies, Architectural Elements, Challenges, and Future Directions

Cited by 44 publications

References 227 publications

Wireless Battery-free and Fully Implantable Organ Interfaces

Wireless Battery-free and Fully Implantable Organ Interfaces

Federated Learning and Blockchain-Enabled Fog-IoT Platform for Wearables in Predictive Healthcare

Distributed Energy-Efficient Clustering and Routing for Wearable IoT Enabled Wireless Body Area Networks

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