Evidence map›Paper›PMID 39686331›Full record

ArticleSensors (Basel, Switzerland)2024

Improving Multiscale Fuzzy Entropy Robustness in EEG-Based Alzheimer's Disease Detection via Amplitude Transformation.

Pasquale Arpaia, Maria Cacciapuoti, Andrea Cataldo, Sabatina Criscuolo, Egidio De Benedetto, Antonio Masciullo, Marisa Pesola, Raissa Schiavoni

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. 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

8 authors.

Pasquale ArpaiaDepartment of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy.ORCID 0000-0002-5192-5922
Maria CacciapuotiDepartment of Engineering for Innovation, University of Salento, 73100 Lecce, Italy.ORCID 0009-0003-8825-3415
Andrea CataldoDepartment of Engineering for Innovation, University of Salento, 73100 Lecce, Italy.ORCID 0000-0001-9031-7690
Sabatina CriscuoloDepartment of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy.ORCID 0000-0001-7189-1339
Egidio De BenedettoDepartment of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy.ORCID 0000-0002-2792-2131
Antonio MasciulloDepartment of Engineering for Innovation, University of Salento, 73100 Lecce, Italy.ORCID 0000-0001-8715-2303
Marisa PesolaDepartment of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy.ORCID 0000-0002-5671-6433
Raissa SchiavoniDepartment of Engineering for Innovation, University of Salento, 73100 Lecce, Italy.ORCID 0000-0002-8462-5563

Funding

Ministero delle Imprese e del Made in Italy (MIMIT), Italia B69J23001290005Ministero delle Imprese e del Made in Italy (MIMIT), Italia B89J23002490005Ministero dell'Università e della Ricerca, Italy DOT19X7NYL- 446 2
6 · The paper itself

Abstract

This study investigates the effectiveness of amplitude transformation in enhancing the performance and robustness of Multiscale Fuzzy Entropy for Alzheimer's disease detection using electroencephalography signals. Multiscale Fuzzy Entropy is a complexity measure particularly sensitive to intra- and inter-subject variations in signal amplitude, as well as the selection of key parameters such as embedding dimension (

Indexed as

Alzheimer DiseaseElectroencephalographyEntropyFuzzy LogicSignal Processing, Computer-AssistedAgedAlgorithmsCluster AnalysisFemaleHumansMaleAlzheimer’s diseasebiomedical signal processingcomplexityelectroencephalographymeasurementsmeasuresmultiscale fuzzy entropy

Identifiers

PMID39686331
PMCPMC11645052

What OpenQuestion holds

Textmetadata
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.