KNOWME: a case study in wireless body area sensor network design

Mitra, Urbashi; Emken, B. Adar; Lee, Sang‐Won; Li, Ming; Rozgić, Viktor; Thatte, Gautam; Vathsangam, Harshvardhan; Zois, Daphney–Stavroula; Annavaram, Murali; Narayanan, Shrikanth; Levorato, Marco; Spruijt‐Metz, Donna; Sukhatme, Gaurav S.

doi:10.1109/mcom.2012.6194391

Cited by 77 publications

(45 citation statements)

References 11 publications

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“…In the same direction, [14] and [15] describe identification of basic activities using multiple on-body accelerometers and gyroscopes. KNOWME [16] consists of a network of multiple on-body sensors, including accelerometers and an electrocardiogram sensor, that are streaming on a smart phone which estimates the user's energy expenditure. Many of these platforms do not pay the necessary attention to the energy consumption of the hardware used, resulting in wearable devices that require regular recharging, similarly to commercial products.…”

Section: Related Workmentioning

confidence: 99%

A residential maintenance-free long-term activity monitoring system for healthcare applications

Fafoutis

Tsimbalo

Mellios

et al. 2016

J Wireless Com Network

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Demographic changes such as the ageing population and the continuous rise of chronic medical conditions such as obesity, diabetes and depression make our healthcare systems economically unsustainable. Sensing technologies are promising solutions that can provide cost-effective answers to these challenges. In this paper, we focus on long-term in-house activity monitoring that aims at early detection and prevention of such conditions. In this context, we present and experimentally evaluate an ultra low-power (less than 100-μW long-term average power consumption) on-body activity sensing prototype system that is based on Bluetooth low energy (BLE). As part of a larger smart home monitoring architecture, the role of the presented system is to collect and reliably deliver acceleration data to the upper layers of the architecture. The system evaluation incorporates a thorough power consumption study that facilitates meaningful battery lifetime estimations, an insightful coverage study in an actual residential environment, and the investigation of energy-efficient packet loss mitigation techniques.

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Section: Related Workmentioning

confidence: 99%

A residential maintenance-free long-term activity monitoring system for healthcare applications

Fafoutis

Tsimbalo

Mellios

et al. 2016

J Wireless Com Network

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“…The constraints (3)(4)(5) are flow conservation constraints essentially expressing the balance between ingoing and outgoing flows in any node of the graph. Note that we distinguish three flow balance cases, one for each type of device/vertex: 1) biosensors b ∈ B, which only transmit data, have a negative flow balance; 2) relays r ∈ R, which are transit vertices and thus retransmit all the received data, have a null flow balance; 3) sinks s ∈ S, which only receive data, have a positive flow balance.…”

Section: ⊓ ⊔mentioning

confidence: 99%

A Fast ILP-Based Heuristic for the Robust Design of Body Wireless Sensor Networks

D’Andreagiovanni¹,

Nardin²,

Natalizio³

2017

Applications of Evolutionary Computation

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Abstract. We consider the problem of optimally designing a body wireless sensor network, while taking into account the uncertainty of data generation of biosensors. Since the related min-max robustness Integer Linear Programming (ILP) problem can be difficult to solve even for state-of-the-art commercial optimization solvers, we propose an original heuristic for its solution. The heuristic combines deterministic and probabilistic variable fixing strategies, guided by the information coming from strengthened linear relaxations of the ILP robust model, and includes a very large neighborhood search for reparation and improvement of generated solutions, formulated as an ILP problem solved exactly. Computational tests on realistic instances show that our heuristic finds solutions of much higher quality than a state-of-the-art solver and than an effective benchmark heuristic.

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“…However, these systems are so diverse; and integrate different communication technologies depending on the target application. In a BAN network, sensors can interact with each other and with the hub via wired or short-range wireless communication suchas Bluetooth [4], IEEE802.15.4/Zigbee [5], MICS [6], ANT [7]. WBAN Networks focus on the latest advances in technology and perfectly meet the medical surveillance systems requirements.…”

Section: Introductionmentioning

confidence: 99%

“…The biggest challenge in the design of IoT is connectivity. The creation of large-scale communicating smart object networks has become the goal of many recent and diverse research activities [4], [6]- [18]. Several systems allows direct sensors networks connection with the Internet network have been proposed [19]- [21], sensors are equipped with HTTP / TCP / UDP stack.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of a Smart Remote Patient Monitoring System based Heterogeneous WSN

Eddabbah¹,

Moussaoui²,

Laaziz³

2018

ijacsa

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KNOWME: a case study in wireless body area sensor network design

Cited by 77 publications

References 11 publications

A residential maintenance-free long-term activity monitoring system for healthcare applications

A residential maintenance-free long-term activity monitoring system for healthcare applications

A Fast ILP-Based Heuristic for the Robust Design of Body Wireless Sensor Networks

Performance Evaluation of a Smart Remote Patient Monitoring System based Heterogeneous WSN

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