Evidence map›Paper›PMID 36616687›Full record

ArticleSensors (Basel, Switzerland)2022

Can Microsaccades Be Used for Biometrics?

Kiril Alexiev, Teodor Vakarelski

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Kiril AlexievInstitute of Information and Communication Technologies, Bulgarian Academy of Science, 25A Acad. G. Bonchev Str., 1113 Sofia, Bulgaria.ORCID 0000-0003-0940-2631
Teodor VakarelskiInstitute of Information and Communication Technologies, Bulgarian Academy of Science, 25A Acad. G. Bonchev Str., 1113 Sofia, Bulgaria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human eyes are in constant motion. Even when we fix our gaze on a certain point, our eyes continue to move. When looking at a point, scientists have distinguished three different fixational eye movements (FEM)-microsaccades, drift and tremor. The main goal of this paper is to investigate one of these FEMs-microsaccades-as a source of information for biometric analysis. The paper argues why microsaccades are preferred for biometric analysis over the other two fixational eye movements. The process of microsaccades' extraction is described. Thirteen parameters are defined for microsaccade analysis, and their derivation is given. A gradient algorithm was used to solve the biometric problem. An assessment of the weights of the different pairs of parameters in solving the biometric task was made.

Indexed as

SaccadesVisual PerceptionBiometryEye MovementsFixation, OcularHumansTremorbiometricseye trackingfixational eye movements feature selectionmicrosaccade

Identifiers

PMID36616687
PMCPMC9824634

What OpenQuestion holds

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LicenceCC BY
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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.