Evidence map›Paper›PMID 35884267›Full record

ArticleBiosensors2022

Mental Stress Assessment Using Ultra Short Term HRV Analysis Based on Non-Linear Method.

Seungjae Lee, Ho Bin Hwang, Seongryul Park, Sanghag Kim, Jung Hee Ha, Yoojin Jang, Sejin Hwang, Hoon-Ki Park, Jongshill Lee, In Young Kim

Open access · goldAbstract read
In one paragraph

Article in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
9.2field-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.

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

20 citing papers in PubMed, 59 citations in OpenAlex.

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  17. Interactive Cardio System for Healthcare Improvement.Sensors (Basel, Switzerland) · 2023
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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

10 authors at 1 institution in 1 country.

Seungjae LeeDepartment of Biomedical Engineering, Hanyang University, Seoul 04763, Korea.ORCID 0000-0002-7798-7347
Ho Bin HwangDepartment of Biomedical Engineering, Hanyang University, Seoul 04763, Korea.ORCID 0000-0002-8809-1597
Seongryul ParkDepartment of Biomedical Engineering, Hanyang University, Seoul 04763, Korea.ORCID 0000-0002-3272-0913
Sanghag KimDepartment of Sociology, Hanyang University, Seoul 04763, Korea.
Jung Hee HaGraduate School of Counseling Psychology, Hanyang University, Seoul 04763, Korea.
Yoojin JangGraduate School of Counseling Psychology, Hanyang University, Seoul 04763, Korea.ORCID 0000-0001-9762-1070
Sejin HwangDepartment Anatomy and Cell Biology, College of Medicine, Hanyang University, Seoul 04763, Korea.ORCID 0000-0002-8031-9980
Hoon-Ki ParkDepartment of Family Medicine, Hanyang University, Seoul 04763, Korea.
Jongshill LeeDepartment of Biomedical Engineering, Hanyang University, Seoul 04763, Korea.ORCID 0000-0002-9884-9672
In Young KimDepartment of Biomedical Engineering, Hanyang University, Seoul 04763, Korea.ORCID 0000-0001-9580-7074
Hanyang University · KR

Funding

National Research Foundation of Korea No. 2018R1A5A7025522
6 · The paper itself

Abstract

Mental stress is on the rise as one of the major health problems in modern society. It is important to detect and manage mental stress to prevent various diseases caused by stress and to maintain a healthy life. The purpose of this paper is to present new heart rate variability (HRV) features based on empirical mode decomposition and to detect acute mental stress through short-term HRV (5 min) and ultra-short-term HRV (under 5 min) analysis. HRV signals were acquired from 74 young police officers using acute stressors, including the Trier Social Stress Test and horror movie viewing, and a total of 26 features, including the proposed IMF energy features and general HRV features, were extracted. A support vector machine (SVM) classification model is used to classify the stress and non-stress states through leave-one-subject-out cross-validation. The classification accuracies of short-term HRV and ultra-short-term HRV analysis are 86.5% and 90.5%, respectively. In the results of ultra-short-term HRV analysis using various time lengths, we suggest the optimal duration to detect mental stress, which can be applied to wearable devices or healthcare systems.

Indexed as

ElectrocardiographyStress, PsychologicalFemaleHeart RateHumansPregnancyResearch DesignSupport Vector Machineempirical mode decomposition (EMD)heart rate variability (HRV)non-linear featuresstress assessmentultra-short-term HRV analysis

Identifiers

PMID35884267
PMCPMC9313333
OpenAlexW4283644173

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.