Evidence map›Paper›PMID 40034836›Full record

ArticleIEEE open journal of engineering in medicine and biology2025

BandFocusNet: A Lightweight Model for Motor Imagery Classification of a Supernumerary Thumb in Virtual Reality.

Haneen Alsuradi, Joseph Hong, Alireza Sarmadi, Robert Volcic, Hanan Salam, S Farokh Atashzar, Farshad Khorrami, Mohamad Eid

Abstract read
In one paragraph

Article in IEEE open journal of engineering in medicine and biology, 2025. 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

8 authors.

Haneen AlsuradiEngineering DivisionNew York University Abu Dhabi Abu Dhabi 129188 UAE.ORCID https://orcid.org/0000-0001-7396-444X
Joseph HongEngineering DivisionNew York University Abu Dhabi Abu Dhabi 129188 UAE.ORCID https://orcid.org/0009-0005-0128-7220
Alireza SarmadiDepartment of Electrical and Computer EngineeringNew York University New York NY 10012 USA.ORCID https://orcid.org/0000-0002-3028-4230
Robert VolcicDivision of ScienceNew York University Abu Dhabi Abu Dhabi 129188 UAE.ORCID https://orcid.org/0000-0002-0170-4136
Hanan SalamDivision of ScienceNew York University Abu Dhabi Abu Dhabi 129188 UAE.
S Farokh AtashzarDepartment of Electrical and Computer EngineeringNew York University New York NY 10012 USA.ORCID https://orcid.org/0000-0001-8495-8440
Farshad KhorramiDepartment of Electrical and Computer EngineeringNew York University New York NY 10012 USA.ORCID https://orcid.org/0000-0002-8418-004X
Mohamad EidEngineering DivisionNew York University Abu Dhabi Abu Dhabi 129188 UAE.ORCID https://orcid.org/0000-0002-6940-7891

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Brain-computer interfacedeep learningEEGhuman augmentationmotor imagerysupernumerary robotic limbs

Identifiers

PMID40034836
PMCPMC11875636

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.