Evidence map›Paper›PMID 36252972›Full record

ReviewNeurosciences (Riyadh, Saudi Arabia)2022

Review of electroencephalography signals approaches for mental stress assessment.

Eyad T Attar

Open access · diamondAbstract readReview
In one paragraph

Review in Neurosciences (Riyadh, Saudi Arabia), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
7.8field-weighted citation impact, top 2% 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

29 citing papers in PubMed, 1 synthesis or guideline pooled it, 75 citations in OpenAlex.

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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

1 author at 1 institution in 1 country.

Eyad T AttarFrom the Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah, kingdom of Saudi Arabia.
King Abdulaziz University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The innovation of electroencephalography (EEG) more than a century ago supports the technique to assess brain structure and function in clinical health and research applications. The EEG signals were identified on their frequency ranges as delta (from 0.5 to 4 Hz), theta (from 4 to 7 Hz), alpha (from 8 to 12 Hz), beta (from 16 to 31 Hz), and gamma (from 36 to 90 Hz). Stress is a sense of emotional tension caused by several life events. For example, worrying about something, being under pressure, and facing significant challenges are causes of stress. The human body is affected by stress in various ways. It promotes inflammation, which affects cardiac health. The autonomic nervous system is activated during mental stress. Posttraumatic stress disorder and Alzheimer's disease are common brain stress disorders. Several methods have been used previously to identify stress, for instance, magnetic resonance imaging, single-photon emission computed tomography and EEG. The EEG identifies the electrical activity in the human brain by applying small electrodes positioned on the scalp of the brain. It is a useful non-invasive method and collects feedback from stress hormones. In addition, it can serve as a reliable tool for measuring stress. Furthermore, evaluating human stress in real-time is complicated and challenging. This review demonstrates the power of frequency bands for mental stress and the behaviors of frequency bands based on medical and research experiencebands based on medical and research experience.

Indexed as

Alzheimer DiseaseElectroencephalographyBrainBrain MappingHormonesHumansHormones

Identifiers

PMID36252972
PMCPMC9749579
OpenAlexW4306731466

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.