Model-based design for wireless body sensor network nodes

Beretta, Ivan; Rincon, Francisco; Khaled, N.; Grassi, Paolo Roberto; Rana, Vincenzo; Atienza, David; Sciuto, D.

doi:10.1109/latw.2012.6261244

Cited by 12 publications

(12 citation statements)

References 23 publications

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“…At the distributed computing level, the design of WBSN nodes is mainly focused on maximizing the lifetime of the node by reducing the energy consumption, although other performance requirements such as the delay and quality of the delivered data must be kept into account [7]. Energy efficiency in WBSNs has been tackled by proposing efficient MAC layer alternatives [8,9], providing stochastic approaches for traffic handling [10] or enabling compressed sensing signal acquisition/compression algorithms [11].…”

Section: Related Workmentioning

confidence: 99%

A novel energy-driven computing paradigm for e-health scenarios

Zapater

Arroba

Ayala

et al. 2014

Future Generation Computer Systems

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A first-rate e-Health system saves lives, provides better patient care, allows complex but useful epidemiologic analysis and saves money. However, there may also be concerns about the costs and complexities associated with e-health implementation, and the need to solve issues about the energy footprint of the high-demanding computing facilities. This paper proposes a novel and evolved computing paradigm that: i) provides the required computing and sensing resources; ii) allows the population-wide diffusion; iii) exploits the storage, communication and computing services provided by the Cloud; iv) tackles the energy-optimization issue as a first-class requirement, taking it into account during the whole development cycle. The novel computing concept, and the multilayer top-down energy-optimization methodology, obtain promising results in a realistic scenario for cardiovascular tracking and analysis, making the Home Assisted Living a reality.

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Section: Related Workmentioning

confidence: 99%

A novel energy-driven computing paradigm for e-health scenarios

Zapater

Arroba

Ayala

et al. 2014

Future Generation Computer Systems

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“…Figure 1 shows a schematic diagram of a typical WBSN node [17] along with an example of the central coordinator. Although the central coordinator has superior computing capabilities with respect to the node, recent work has shown that the coordinator can operate at real time on a typical smart phone [18].…”

Section: Next Generation Computing Architectures In Smart Biomedical mentioning

confidence: 99%

Design of Energy Efficient and Dependable Health Monitoring Systems under Unreliable Nanometer Technologies

Sabry¹,

Karakonstantis²,

Atienza³

et al. 2012

Proceedings of the 7th International Conference on Body Area Networks

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In this paper we investigate the impact of potential hardware misbehavior induced by reliability issues and scaled voltages in wireless body sensor network (WBSN) nodes. Our study reveals the inherent resilience of popular algorithms in cardiac monitoring applications and argues that by exploiting the unique characteristics of such algorithms the energy efficiency and reliability of such systems can be significantly improved. This is achieved by developing a cross-layer design paradigm that utilizes low cost techniques at the hardware and software layers and by optimizing the synergy between them in order to provide intelligent trade-offs between energy, performance and quality. The main idea of the proposed approach is the selective application of costly robust techniques only to the most critical tasks identified at the application layer that are detrimental for obtaining sufficient output quality. Our results show that by ensuring the correct operation of only 37% of the total computations in an electrocardiogram (ECG) monitoring WBSN node we can achieve up to 70% power savings with only 9% degradation in ECG output quality.

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“…2. In order to reduce hospitalization Q3 and to facilitate the care of humans, especially agent people who are increasing year after year (Campbell 2013), many research groups (Keong and Yuce 2011; Beretta et al, 2012;Thotahewa et al, 2014;Sun et al, 2014;Mahalle and Ingole 2013) are focusing on the concept, design, and implementation of a body network. WBANs invade different medical area applications (Zhang 1,* et al, Calhoun 1;Tartarisco et al, June 2012) which can be divided into wearable and implantable body area networks (BAN).…”

Section: Introductionmentioning

confidence: 99%