Evidence map›Paper›PMID 34513342›Full record

ArticleIEEE journal of translational engineering in health and medicine2021

Stress Analysis Based on Simultaneous Heart Rate Variability and EEG Monitoring.

Eyad Talal Attar, Vignesh Balasubramanian, Ersoy Subasi, Mehmet Kaya

2 registry-linked trialsOpen access · goldAbstract read
In one paragraph

Article in IEEE journal of translational engineering in health and medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
10.4field-weighted citation impact, top 1% 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.

NCT07591935 nacompletednot on this mapstarted 2024, after this paper: background citation

Artificial Intelligence and Mindfulness Meditation: Innovative Methods to Reduce Stress Amongst Medical School Students

TypeinterventionalSponsorSaint James School of MedicineRan2024 to 2024Enrolled20ConditionsStressArmsMindfulness-Based Stress Reduction Course, Apollo Neuro Wearable
NCT07745335 nanot yet recruitingnot on this mapstarted 2026, after this paper: background citation

Efficacy of a Multisensory Audiovisual Entrainment Neurofeedback for Academic Anxiety Regulation and Divergent Thinking: A Randomized Controlled Trial Study

TypeinterventionalSponsorDaniswara Raditya SupraptoRan2026 to 2027Enrolled240ConditionsAcademic Anxiety, Test Anxiety, Divergent ThinkingArmsAudiovisual Entrainment Neurofeedback (AVE-NFB), Neurofeedback Only, Audiovisual Entrainment, Sham Control
3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 115 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

4 authors at 1 institution in 2 countries.

Eyad Talal AttarDepartment of Biomedical and Chemical Engineering and SciencesFlorida Institute of Technology Melbourne FL 32901 USA.
Vignesh BalasubramanianDepartment of Biomedical and Chemical Engineering and SciencesFlorida Institute of Technology Melbourne FL 32901 USA.
Ersoy SubasiDepartment of Computer Engineering and SciencesFlorida Institute of Technology Melbourne FL 32901 USA.
Mehmet KayaDepartment of Biomedical and Chemical Engineering and SciencesFlorida Institute of Technology Melbourne FL 32901 USA.
Florida Institute of Technology · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveStress is a significant risk factor for various diseases such as hypertension, heart attack, stroke, and even sudden death. Stress can also lead to psychological and behavioral disorders. Heart rate variability (HRV) can reflect changes in stress levels while other physiological factors, like blood pressure, are within acceptable ranges. Electroencephalogram (EEG) is a vital technique for studying brain activities and provides useful data regarding changes in mental status. This study incorporates EEG and a detailed HRV analysis to have a better understanding and analysis of stress. Investigating the correlation between EEG and HRV under stress conditions is valuable since they provide complementary information regarding stress.

methodsSimultaneous electrocardiogram (ECG) and EEG recordings were obtained from fifteen subjects. HRV /EEG features were analyzed and compared in rest, stress, and meditation conditions. A one-way ANOVA and correlation coefficient were used for statistical analysis to explore the correlation between HRV features and features extracted from EEG.

resultsThe HRV features LF (low frequency), HF (high frequency), LF/HF, and rMSSD (root mean square of the successive differences) correlated with EEG features, including alpha power band in the left hemisphere and alpha band power asymmetry.

conclusionThis study demonstrated five significant relationships between EEG and HRV features associated with stress. The ability to use stress-related EEG features in combination with correlated HRV features could help improve detecting stress and monitoring the progress of stress treatments/therapies. The outcomes of this study could enhance the efficiency of stress management technologies such as meditation studies and bio-feedback training.

Indexed as

ElectroencephalographyStrokeBrainElectrocardiographyHeart RateHumansECGEEGHRVmeditationStress

Identifiers

PMID34513342
PMCPMC8407658
OpenAlexW3195539947

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

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.