8,916 research outputs found
Wireless body sensor networks for health-monitoring applications
This is an author-created, un-copyedited version of an article accepted for publication in
Physiological Measurement. The publisher is
not responsible for any errors or omissions in this version of the manuscript or any version
derived from it. The Version of Record is available online at http://dx.doi.org/10.1088/0967-3334/29/11/R01
An Adaptive Fault-Tolerant Communication Scheme for Body Sensor Networks
A high degree of reliability for critical data transmission is required in
body sensor networks (BSNs). However, BSNs are usually vulnerable to channel
impairments due to body fading effect and RF interference, which may
potentially cause data transmission to be unreliable. In this paper, an
adaptive and flexible fault-tolerant communication scheme for BSNs, namely
AFTCS, is proposed. AFTCS adopts a channel bandwidth reservation strategy to
provide reliable data transmission when channel impairments occur. In order to
fulfill the reliability requirements of critical sensors, fault-tolerant
priority and queue are employed to adaptively adjust the channel bandwidth
allocation. Simulation results show that AFTCS can alleviate the effect of
channel impairments, while yielding lower packet loss rate and latency for
critical sensors at runtime.Comment: 10 figures, 19 page
Timely and reliable packets delivery over Internet of Vehicles (IoVs) for road accidents prevention: a cross-layer approach
With the envisioned era of Internet of Things (IoTs), all aspects of Intelligent Transportation Systems (ITS) will be connected to improve transport safety, relieve traffic congestion, reduce air pollution, enhance the comfort of transportation and significantly reduce road accidents. In IoVs, regular exchange of current position, direction, velocity, etc., enables mobile vehicles to predict an upcoming accident and alert the human drivers in time or proactively take precautionary actions to avoid the accident. The actualization of this concept requires the use of channel access protocols that can guarantee reliable and timely broadcast of safety messages. This paper investigates the application of network coding concept to increase content of every transmission and achieve improved broadcast reliability with less number of retransmission. In particular, we proposed Code Aided Retransmission-based Error Recovery (CARER) scheme, introduced an RTB/CTB handshake to overcome hidden node problem and reduce packets collision rate. In order to avoid broadcast storm problem associated with the use of RTB/CTB packet in a broadcast transmission, we developed a rebroadcasting metric used to successfully select a vehicle to rebroadcast the encoded message. The performance of CARER protocol is clearly shown with detailed theoretical analysis and further validated with simulation experiments
Spatiotemporal Sparse Bayesian Learning with Applications to Compressed Sensing of Multichannel Physiological Signals
Energy consumption is an important issue in continuous wireless
telemonitoring of physiological signals. Compressed sensing (CS) is a promising
framework to address it, due to its energy-efficient data compression
procedure. However, most CS algorithms have difficulty in data recovery due to
non-sparsity characteristic of many physiological signals. Block sparse
Bayesian learning (BSBL) is an effective approach to recover such signals with
satisfactory recovery quality. However, it is time-consuming in recovering
multichannel signals, since its computational load almost linearly increases
with the number of channels.
This work proposes a spatiotemporal sparse Bayesian learning algorithm to
recover multichannel signals simultaneously. It not only exploits temporal
correlation within each channel signal, but also exploits inter-channel
correlation among different channel signals. Furthermore, its computational
load is not significantly affected by the number of channels. The proposed
algorithm was applied to brain computer interface (BCI) and EEG-based driver's
drowsiness estimation. Results showed that the algorithm had both better
recovery performance and much higher speed than BSBL. Particularly, the
proposed algorithm ensured that the BCI classification and the drowsiness
estimation had little degradation even when data were compressed by 80%, making
it very suitable for continuous wireless telemonitoring of multichannel
signals.Comment: Codes are available at:
https://sites.google.com/site/researchbyzhang/stsb
Physiology-Aware Rural Ambulance Routing
In emergency patient transport from rural medical facility to center tertiary
hospital, real-time monitoring of the patient in the ambulance by a physician
expert at the tertiary center is crucial. While telemetry healthcare services
using mobile networks may enable remote real-time monitoring of transported
patients, physiologic measures and tracking are at least as important and
requires the existence of high-fidelity communication coverage. However, the
wireless networks along the roads especially in rural areas can range from 4G
to low-speed 2G, some parts with communication breakage. From a patient care
perspective, transport during critical illness can make route selection patient
state dependent. Prompt decisions with the relative advantage of a longer more
secure bandwidth route versus a shorter, more rapid transport route but with
less secure bandwidth must be made. The trade-off between route selection and
the quality of wireless communication is an important optimization problem
which unfortunately has remained unaddressed by prior work.
In this paper, we propose a novel physiology-aware route scheduling approach
for emergency ambulance transport of rural patients with acute, high risk
diseases in need of continuous remote monitoring. We mathematically model the
problem into an NP-hard graph theory problem, and approximate a solution based
on a trade-off between communication coverage and shortest path. We profile
communication along two major routes in a large rural hospital settings in
Illinois, and use the traces to manifest the concept. Further, we design our
algorithms and run preliminary experiments for scalability analysis. We believe
that our scheduling techniques can become a compelling aid that enables an
always-connected remote monitoring system in emergency patient transfer
scenarios aimed to prevent morbidity and mortality with early diagnosis
treatment.Comment: 6 pages, The Fifth IEEE International Conference on Healthcare
Informatics (ICHI 2017), Park City, Utah, 201
A Study of Medium Access Control Protocols for Wireless Body Area Networks
The seamless integration of low-power, miniaturised, invasive/non-invasive
lightweight sensor nodes have contributed to the development of a proactive and
unobtrusive Wireless Body Area Network (WBAN). A WBAN provides long-term health
monitoring of a patient without any constraint on his/her normal dailylife
activities. This monitoring requires low-power operation of
invasive/non-invasive sensor nodes. In other words, a power-efficient Medium
Access Control (MAC) protocol is required to satisfy the stringent WBAN
requirements including low-power consumption. In this paper, we first outline
the WBAN requirements that are important for the design of a low-power MAC
protocol. Then we study low-power MAC protocols proposed/investigated for WBAN
with emphasis on their strengths and weaknesses. We also review different
power-efficient mechanisms for WBAN. In addition, useful suggestions are given
to help the MAC designers to develop a low-power MAC protocol that will satisfy
the stringent WBAN requirements.Comment: 13 pages, 8 figures, 7 table
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