Evidence map›Paper›PMID 38811002›Full record

ArticlePsychiatry investigation2024

Clinical Implication of Maumgyeol Basic Biotypes-Electroencephalography- and Photoplethysmogram-Based Bwave State Inventory.

Yunsu Kim, Junseok Hwang, Jaehyung Lee, Seongwon Jang, Yumi Im, Sunkyung Yoon, Seung-Hwan Lee

Abstract read
In one paragraph

Article in Psychiatry investigation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Occupational Stress in the Neuroticism-Burnout Link: An Exploratory Examination of Physiological Contributions.Clinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology · 2026
    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

7 authors.

Yunsu KimDepartment of Psychology, Sungkyunkwan University, Seoul, Republic of Korea.
Junseok HwangBwave Inc., Goyang, Republic of Korea.
Jaehyung LeeBwave Inc., Goyang, Republic of Korea.
Seongwon JangBwave Inc., Goyang, Republic of Korea.
Yumi ImBwave Inc., Goyang, Republic of Korea.
Sunkyung YoonDepartment of Psychology, Sungkyunkwan University, Seoul, Republic of Korea.
Seung-Hwan LeeClinical Emotion and Cognition Research Laboratory, Department of Psychiatry, Inje University, Goyang, Republic of Korea.

Funding

Ministry of SMEs and Startups S3197996
6 · The paper itself

Abstract

objectiveThe development of individual subtypes based on biomarkers offers a cost-effective and timely avenue to comprehending individual differences pertaining to mental health, independent from individuals' subjective insights. Incorporating 2-channel electroencephalography (EEG) and photoplethysmogram (PPG), we sought to establish a subtype classification system with clinical relevance.

methodsOne hundred healthy participants and 99 patients with psychiatric disorders were recruited. Classification thresholds were determined using the EEG and PPG data from 2,278 individuals without mental disorders, serving to classify subtypes in our sample of 199 participants. Multivariate analysis of variance was applied to examine psychological distinctions among these subtypes. K-means clustering was employed to verify the classification system.

resultsThe distribution of subtypes differed between healthy participants and those with psychiatric disorders. Cognitive abilities were contingent upon brain subtypes, while mind subtypes exhibited significant differences in symptom severity, overall health, and cognitive stress. K-means clustering revealed that the results of our theory-based classification and data-driven classification are comparable. The synergistic assessment of both brain and mind subtypes was also explored.

conclusionOur subtype classification system offers a concise means to access individuals' mental health. The utilization of EEG and PPG signals for subtype classification offers potential for the future of digital mental healthcare.

Indexed as

BiotypeDigital healthcareElectroencephalographyMental healthPhotoplethysmogram

Identifiers

PMID38811002
PMCPMC11136575

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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.