Evidence map›Paper›PMID 37508837›Full record

ArticleBioengineering (Basel, Switzerland)2023

An Isolated CNN Architecture for Classification of Finger-Tapping Tasks Using Initial Dip Images: A Functional Near-Infrared Spectroscopy Study.

Muhammad Umair Ali, Amad Zafar, Karam Dad Kallu, M Atif Yaqub, Haris Masood, Keum-Shik Hong, Muhammad Raheel Bhutta

Open access · goldAbstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2023. 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
0.5field-weighted citation impact, top 34% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

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

7 authors at 5 institutions in 4 countries.

Muhammad Umair AliDepartment of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, Republic of Korea.ORCID 0000-0002-7326-1813
Amad ZafarDepartment of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, Republic of Korea.ORCID 0000-0002-0716-3932
Karam Dad KalluDepartment of Robotics and Intelligent Machine Engineering (RIME), School of Mechanical and Manufacturing Engineering (SMME), National University of Sciences and Technology (NUST), H-12, Islamabad 44000, Pakistan.
M Atif YaqubICFO-Institut de Ciències Fotòniques the Barcelona Institute of Science and Technology, 08860 Castelldefels, Spain.ORCID 0000-0002-9885-7891
Haris MasoodElectrical Engineering Department, Wah Engineering College, University of Wah, Wah Cantt 47040, Pakistan.
Keum-Shik HongSchool of Mechanical Engineering, Pusan National University, 2 Busandaehak-ro, Geumjeong-gu, Busan 46241, Republic of Korea.ORCID 0000-0002-8528-4457
Muhammad Raheel BhuttaDepartment of Electrical and Computer Engineering, University of UTAH Asia Campus, Incheon 21985, Republic of Korea.ORCID 0000-0002-3213-7154
Sejong University · KRInstitute of Photonic Sciences · ESNational University of Sciences and Technology · PKQingdao University · CNUniversity of Wah · PK

Funding

National Research Foundation 2020R1G1A1012741
6 · The paper itself

Abstract

This work investigates the classification of finger-tapping task images constructed for the initial dip duration of hemodynamics (HR) associated with the small brain area of the left motor cortex using functional near-infrared spectroscopy (fNIRS). Different layers (i.e., 16-layers, 19-layers, 22-layers, and 25-layers) of isolated convolutional neural network (CNN) designed from scratch are tested to classify the right-hand thumb and little finger-tapping tasks. Functional

Indexed as

deep learningdesigned HRFfNIRSinitial dipmotor cortexneuronal firing

Identifiers

PMID37508837
PMCPMC10376657
OpenAlexW4383369046

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.