Body Area Networks in Healthcare: A Brief State of the Art

Vera, Daniel; Costa, Nuno; Roda-Sánchez, Luis; Olivares, Teresa; Fernández-Caballero, Antonio; Pereira, António

doi:10.3390/app9163248

Cited by 9 publications

(6 citation statements)

References 52 publications

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“…With the advent of lightweight IoT technologies and wireless body area networks [41], wearable-based approaches are increasingly being adopted as a costeffective alternative to computer-vision systems. Motion capture devices are typically based on IMUs which have a low demand of hardware resources and energy consumption.…”

Section: Gesture Recognition For Hrimentioning

confidence: 99%

Comparison of RGB-D and IMU-based gesture recognition for human-robot interaction in remanufacturing

Roda-Sánchez

Garrido-Hidalgo

García

et al. 2021

Int J Adv Manuf Technol

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With product life-cycles getting shorter and limited availability of natural resources, the paradigm shift towards the circular economy is being impulsed. In this domain, the successful adoption of remanufacturing is key. However, its associated process efficiency is to date limited given high flexibility requirements for product disassembly. With the emergence of Industry 4.0, natural human-robot interaction is expected to provide numerous benefits in terms of (re)manufacturing efficiency and cost. In this regard, vision-based and wearable-based approaches are the most extended when it comes to establishing a gesture-based interaction interface. In this work, an experimental comparison of two different movement-estimation systems—(i) position data collected from Microsoft Kinect RGB-D cameras and (ii) acceleration data collected from inertial measurement units (IMUs)—is addressed. The results point to our IMU-based proposal, OperaBLE, having recognition accuracy rates up to 8.5 times higher than these of Microsoft Kinect, which proved to be dependent on the movement’s execution plane, subject’s posture, and focal distance.

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Section: Gesture Recognition For Hrimentioning

confidence: 99%

Comparison of RGB-D and IMU-based gesture recognition for human-robot interaction in remanufacturing

Roda-Sánchez

Garrido-Hidalgo

García

et al. 2021

Int J Adv Manuf Technol

Self Cite

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“…Step 6. Use employed bees to update the food source in (6) and convert to binary code in (7) Step 7. The onlookers are selected according to the probability Possibility n to produce a new solution…”

Section: Journal Of Sensorsmentioning

confidence: 99%

“…Medical sensor nodes are evenly distributed in different areas of the human body, including the head, limbs, and trunk. In addition, in order to transmit the collected vital data effectively, the transmission distance, transmission rate, and residual energy of each node must also be fully considered [7,8]. A BAN consists of distributed autonomous sensor nodes, and each sensing unit consists of sensing boards, processor, short-range radio transmitter unit, and battery.…”

Section: Introductionmentioning

confidence: 99%

A Biologically Inspired Algorithm for Low Energy Clustering Problem in Body Area Network

Zhou

2021

Journal of Sensors

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The growing application of body area networks (BANs) in different fields makes the low energy clustering a paramount issue. A clustering optimization algorithm in BANs is a fundamental scheme to guarantee that the essential collected data can be forwarded in a reliable path and improve the lifetime of BANs. Low energy clustering is a technique, which provides a method that shows how to reduce network communication costs in BANs. A careful low energy clustering scheme is one of the most critical means in the research of BANs, which has attracted considerable attention, comprising monitoring capability constraints. However, the classical clustering method leads to high cost when constraints such as large overall energy consumption are undertaken. Hence, a binary immune hybrid artificial bee colony algorithm (BIHABCA), a randomized swarm intelligent scheme applied in BANs, motivated by immune theory and hybrid scheme is introduced. Furthermore, we designed the formulation that considers both distances between two nodes and the length of bits. Finally, we have compared the energy cost optimized by BIHABCA with a shuffled frog leaping algorithm, ant colony optimization, and simulated annealing in the simulation with different quantity of nodes in terms of energy cost. Results show that the energy cost of the network optimized by the proposed BIHABCA method decreased compared to those by the other three methods which mean that the proposed BIHABCA finds the global optima and reduces the energy cost of transmitting and receiving data in BANs.

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“…One example of such applications is (remote) healthcare [38][39][40][41][42][43], where WBANs are considered a key technology to help facing the side effects of an aging population on healthcare systems and society in general.This special issue is devoted to collecting contributions from researchers on the realization of real-world and reliable wireless body area networks, platforms and applications, addressing the major associated challenges. Nine papers have been selected for this special issue, beginning with a paper [44] that gives the reader a general overview of the WBAN research field and highlights its main features and requirements, sensor types and contributions to healthcare, concluding with the main current challenges. The other eight research papers are segmented into three main application areas: energy harvesting, communications and applications in the research field of wireless body area networks.Energy harvesting: Under the assumption that a single energy harvester from a human body is not enough to reliably drive an electronic device, propose energy harvesting by combining multiple energy harvesters in wireless body area network applications.…”

mentioning

confidence: 99%

“…This special issue is devoted to collecting contributions from researchers on the realization of real-world and reliable wireless body area networks, platforms and applications, addressing the major associated challenges. Nine papers have been selected for this special issue, beginning with a paper [44] that gives the reader a general overview of the WBAN research field and highlights its main features and requirements, sensor types and contributions to healthcare, concluding with the main current challenges. The other eight research papers are segmented into three main application areas: energy harvesting, communications and applications in the research field of wireless body area networks.…”

mentioning

confidence: 99%