Evidence map›Paper›PMID 29755714›Full record

ArticleJournal of healthcare engineering2018

Identification of Cerebral Artery Stenosis Using Bilateral Photoplethysmography.

Hyun Goo Kang, Seogki Lee, Han Uk Ryu, Youngsuk Shin

Open access · hybridAbstract read
In one paragraph

Article in Journal of healthcare engineering, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 44% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. 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

4 authors at 1 institution in 1 country.

Hyun Goo KangDepartment of Neurology, Chosun University School of Medicine and Hospital, No. 375 Seosuk-dong, Dong-gu, Gwangju 501-759, Republic of Korea.
Seogki LeeDepartment of Thoracic Surgery, Chosun University School of Medicine and Hospital, No. 375 Seosuk-dong, Dong-gu, Gwangju 501-759, Republic of Korea.
Han Uk RyuDepartment of Neurology, Chunbuk National University School of Medicine and Hospital, San 2-20, Geumam-dong, Deokjin-gu, Jeonbuk 561-180, Republic of Korea.
Youngsuk ShinSchool of Information and Communication Engineering, Chosun University, No. 309 Pilmun-daero, Dong-gu, Gwangju 61452, Republic of Korea.ORCID 0000-0001-8031-5392
Chosun University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cerebral artery stenosis is currently diagnosed by transcranial Doppler (TCD), computed tomographic angiography (CTA), or magnetic resonance angiography (MRA). CTA exposes a patient to radiation, while CTA and MRA are invasive and side effects were related to contrast medium use. This study aims to provide a technique that can simply discriminate between people with normal blood vessels and those with cerebral artery stenosis using photoplethysmography (PPG), which is noninvasive and inexpensive. Moreover, the measurement takes only 120 seconds and is conducted on the fingers. The technique projects the light of a specific wavelength and analyzes the pulse waves which are generated when the blood passes through the blood vessels according to one's heartbeat using the transmitted light. Normalization was performed after dividing the extracted pulse waveform into windows, and maximum positive and negative amplitudes (MPA, MNA) were extracted from the detected pulse waves as features. The extracted features were used to identify normal subjects and those with cerebral artery stenosis using a linear discriminant analysis. The study results showed that the recognition rate using MPA was 92.2%, MNA was 90.6%, and combined MPA + MNA was 90.6%. The technique proposed is expected to detect early stage asymptomatic cerebral artery stenosis and help prevent ischemic stroke.

Indexed as

Signal Processing, Computer-AssistedAgedAlgorithmsCerebral Arterial DiseasesCerebral ArteriesHumansMiddle AgedPhotoplethysmographySensitivity and Specificity

Identifiers

PMID29755714
PMCPMC5884199
OpenAlexW2789641034

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.