Evidence map›Paper›PMID 32824405›Full record

ArticleSensors (Basel, Switzerland)2020

Research on the Recognition Performance of Bionic Sensors Based on Active Electrolocation for Different Materials.

Wenhao Du, Yu'e Yang, Luning Liu

Abstract readLetter
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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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.

Wenhao DuSchool of Mechanical Engineering, University of Jinan, Jinan 250022, China.ORCID 0000-0003-3573-8438
Yu'e YangSchool of Mechanical Engineering, University of Jinan, Jinan 250022, China.
Luning LiuSchool of Mechanical Engineering, University of Jinan, Jinan 250022, China.

Funding

Shandong Province agricultural application technology innovation project SD2019NJ020
6 · The paper itself

Abstract

Underwater object identification by optical sensors is usually difficult in turbid or dark environments. The objective of this paper was to identify different underwater materials using active electrolocation technology. We proposed a bionic sensor inspired by the weakly electric fish. The material identification was completed by analyzing electric signal images, since the electric signal changes when different materials are identified. Firstly, the effective lift-off distance for identification was researched. The materials used in this paper can be effectively identified by the sensor at a lift-off distance of 10 mm. Furthermore, the performance of the sensor for identifying and locating was studied in the presence of multiple materials. The results indicated that the sensor can effectively identify and locate the objects when the distance between objects is greater than 30 mm, while the location error is less than 5% in most cases. Our research proves that the bionic sensor we made can effectively recognize different materials underwater in short-range, which is about 10 mm. Therefore, we expect that the bionic sensor we made can be utilized as a useful tool for underwater object identification.

Indexed as

BionicsDistance PerceptionElectric FishAnimalsRecognition, Psychologyactive electrolocationbionic sensoridentificationlift-off distance

Identifiers

PMID32824405
PMCPMC7472066

What OpenQuestion holds

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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.