Evidence map›Paper›PMID 32423090›Full record

ArticleSensors (Basel, Switzerland)2020

Optimal Design of Switchable Wearable Antenna Array for Wireless Sensor Networks.

Łukasz Januszkiewicz, Paolo Di Barba, Sławomir Hausman

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
4.7field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Łukasz JanuszkiewiczInstitute of Electronics, Lodz University of Technology, Wólczańska 211/215 Street, 93-005 Łódź, Poland.ORCID 0000-0001-6693-1009
Paolo Di BarbaDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, via Ferrata 5, 27100 Pavia, Italy.ORCID 0000-0001-5293-1809
Sławomir HausmanInstitute of Electronics, Lodz University of Technology, Wólczańska 211/215 Street, 93-005 Łódź, Poland.ORCID 0000-0003-3891-4214
Lodz University of Technology · PLUniversity of Pavia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the paper, we present a novel approach to the optimum design of wearable antenna arrays intended for off-body links of wireless body area networks. Specifically, we investigate a four-element array that has a switchable radiation pattern able to direct its higher gain towards a signal source and a lower gain towards an interference. The aim is to increase the signal to interference ratio. We apply a genetic algorithm to optimize both the spatial placement and the feed phasing of the elementary on-body antennas. We propose a simplified, computationally efficient model for the simulation of the array radiation pattern. The model is based on full-wave simulations obtained with a simplified cylindrical model of the human body. We also propose, implement, and evaluate four objective functions based on signal to interference ratio, i.e., min-max, nadir point distance maximization, utopia point distance minimization, and full Pareto-like. Our optimized design obtained with this approach exhibits a significant performance improvement in comparison to the initial heuristic design.

Indexed as

Wearable Electronic DevicesWireless TechnologyComputer SimulationHeuristicsHumansevolutionary computingFDTDfinite-difference time-domaingenetic algorithmshuman body modelinterference rejectionoptimizationradiation pattern synthesissignal-to-interference ratioSIRswitchable antennaWBANwireless body area network

Identifiers

PMID32423090
PMCPMC7287774
OpenAlexW3025588001

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.