Body Area Sensor Networks: Challenges and Opportunities

Hanson, Mark; Powell, Harry C.; Barth, Adam T.; Ringgenberg, Kyle; Calhoun, Benton H.; Aylor, J.H.; Lach, John

doi:10.1109/mc.2009.5

Cited by 444 publications

(219 citation statements)

References 6 publications

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“…This system monitors body motion and heart activities using multiple sensor nodes and personal server. In [16], WBAN challenges and opportunities are discussed in details regarding application areas, communication, storage, energy harvesting and compatibility issues. Another body area network survey is presented in [17].…”

Section: Multi-radio Multi-channel Mechanismmentioning

confidence: 99%

Multi-Channel Framework for Body Area Network in Health Monitoring

Alrajeh¹,

Khan²,

Campbell³

et al. 2013

Appl. Math. Inf. Sci.

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Increasing use of wireless networks has empowered the facility of ubiquitous health monitoring especially in advanced countries. Various small devices are attached to human body forming personalized wireless body area network (WBAN). These small devices interact with each other using different radios and antennas schemes proposed by many researchers around the globe. However, most of these schemes are facing problem of inefficiency due to fading and shadowing effects. We propose a novel multi-radio multichannel framework for efficient communication among devices in WBAN. The focus of this research is to ensure energy efficient and reliable communication in WBAN.

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Section: Multi-radio Multi-channel Mechanismmentioning

confidence: 99%

Multi-Channel Framework for Body Area Network in Health Monitoring

Alrajeh¹,

Khan²,

Campbell³

et al. 2013

Appl. Math. Inf. Sci.

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“…The demand for similar sensor-embedded devices in the medical domain has spawned a new subclass of WSNs known as wearable or body area sensor networks (BASNs), the challenges and opportunities for which are surveyed in [2]. BASNs have been applied to host of medical problems from geriatric assistance [10] to emotional health monitoring [24].…”

Section: Related Workmentioning

confidence: 99%

Fault-Tolerant and Low-Power Sampling Schedules for Localized BASNs

Goudar

Potkonjak

2013

IEEE J. Emerg. Sel. Topics Circuits Syst.

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Abstract-Recent advances in the scope of wearable devices and networks make body area sensor networks (BASNs) an extremely attractive tool to the fields of mobile and tele-health, owing to the range of medical applications they can serve and the diagnostic richness of patient data they can offer. However, for BASNs to achieve true ubiquity, they must be scalable in their support of automated patient data collection, making usability and reliability key considerations. Its designers must wrestle with the tradeoff between usability, hindered by device intrusiveness into the behaviors it measures, and lifetime, enhanced by large power supplies and expensive, sturdy components. Furthermore, the validity and reliability of the collected data are paramount. In this paper, we consider these issues in the context of localized multi-sensory wearable networks and present a method to generate low-power sampling schedules that are resilient to sensor faults while achieving high diagnostic fidelity. We jointly formulate this as a power-constrained sampling problem wherein the number of sensors sampled per epoch are limited, and, a fault tolerant scheduling problem wherein the sampling scheme offers enough redundancy to endure up to a predefined number of sensor faults while maintaining diagnostic accuracy. This formulation is based on, 1) the localized scope of BASNs that engenders strong spatio-temporal interactions in the samples, and, 2) the periodic nature of human behaviors measured. We present our algorithm in the context of gait diagnostics derived from a foot plantar pressure measurement platform and illustrate its performance based on real datasets collected by it.Index Terms-Body area sensor networks, energy-efficient sampling, fault-tolerant sampling, power-constrained sampling.

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“…For instance, in critical professional applications, SFIT systems enable monitoring, localization and coordination of first responders during emergencies. Employing SFIT systems in health-care applications facilitates wireless monitoring of A major issue of current-generation SFIT and other IoT related systems concerns the limited system autonomy [1] [3]. Lots of research efforts were already devoted to increase efficiency of the embedded electronic circuitry in order to increase system autonomy without using large and obtrusive batteries.…”

Section: Introductionmentioning

confidence: 99%

SIW antennas as hybrid energy harvesting and power management platforms for the internet of things

Caytan

Agneessens

Rogier

2016

Int. J. Microw. Wireless Technol.

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A novel antenna-harvester co-design paradigm is presented for wireless nodes operating in an Internet of Things context. The strategy leads to compact and highly-integrated units, which are able to set up a reliable and energy-efficient wireless communication link, and to simultaneously harvest energy from up to three different sources, including thermal body energy, solar and artificial light. The core of the unit consists of a substrate-integrated-waveguide (SIW) antenna. Its surface serves as a platform for the flexible energy harvesting hardware, which also comprises the power management system. To demonstrate the approach, two different SIW cavity-backed slot antennas and a novel compact dual linearly polarized SIW antenna are presented. These topologies facilitate the integration of additional hardware without degrading performance. In the meantime, they enable comfortable integration into garments or unobtrusive embedding into floors or walls. Measurements on prototypes validate the integration procedure by verifying that the integrated hardware has a negligible influence on the performance of all discussed SIW antennas. Finally, measurements in four well-chosen indoor scenarios demonstrate that a hybrid energy-harvesting approach is necessary to obtain a more continuous flow and a higher amount of scavenged energy, leading to a higher system autonomy and/or reduced battery size.

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Body Area Sensor Networks: Challenges and Opportunities

Cited by 444 publications

References 6 publications

Multi-Channel Framework for Body Area Network in Health Monitoring

Multi-Channel Framework for Body Area Network in Health Monitoring

Fault-Tolerant and Low-Power Sampling Schedules for Localized BASNs

SIW antennas as hybrid energy harvesting and power management platforms for the internet of things

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