View in EDS HTML Full Text PDF Full Text

Machine learning-based fatigue classification using heart rate variability and cortisol: A multimodal approach to wearable health monitoring.

Saved in:
Bibliographic Details
Title: Machine learning-based fatigue classification using heart rate variability and cortisol: A multimodal approach to wearable health monitoring.
Authors: Kim JE; Department of Family Medicine, Seoul National University Bundang Hospital, Seongnam, Korea., Kim NH; Center for Artificial Intelligence in Healthcare, Seoul National University Bundang Hospital, Seongnam, Korea.; Department of Data Science, Inha University, Incheon, Korea., Choi SK; Center for Artificial Intelligence in Healthcare, Seoul National University Bundang Hospital, Seongnam, Korea., Lee JY; Center for Artificial Intelligence in Healthcare, Seoul National University Bundang Hospital, Seongnam, Korea., Lee K; Department of Family Medicine, Seoul National University Bundang Hospital, Seongnam, Korea., Han JS; Health Promotion Center, Seoul National University Bundang Hospital, Seongnam, Korea.
Source: Digital health [Digit Health] 2025 Nov 07; Vol. 11, pp. 20552076251395570. Date of Electronic Publication: 2025 Nov 07 (Print Publication: 2025).
Publication Type: Journal Article
Journal Info: Publisher: SAGE Publications Ltd Country of Publication: United States NLM ID: 101690863 Publication Model: eCollection Cited Medium: Print ISSN: 2055-2076 (Print) Linking ISSN: 20552076 NLM ISO Abbreviation: Digit Health Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 41229925
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Machine learning-based fatigue classification using heart rate variability and cortisol: A multimodal approach to wearable health monitoring.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Kim+JE%22">Kim JE</searchLink>; Department of Family Medicine, Seoul National University Bundang Hospital, Seongnam, Korea.<br /><searchLink fieldCode="AU" term="%22Kim+NH%22">Kim NH</searchLink>; Center for Artificial Intelligence in Healthcare, Seoul National University Bundang Hospital, Seongnam, Korea.; Department of Data Science, Inha University, Incheon, Korea.<br /><searchLink fieldCode="AU" term="%22Choi+SK%22">Choi SK</searchLink>; Center for Artificial Intelligence in Healthcare, Seoul National University Bundang Hospital, Seongnam, Korea.<br /><searchLink fieldCode="AU" term="%22Lee+JY%22">Lee JY</searchLink>; Center for Artificial Intelligence in Healthcare, Seoul National University Bundang Hospital, Seongnam, Korea.<br /><searchLink fieldCode="AU" term="%22Lee+K%22">Lee K</searchLink>; Department of Family Medicine, Seoul National University Bundang Hospital, Seongnam, Korea.<br /><searchLink fieldCode="AU" term="%22Han+JS%22">Han JS</searchLink>; Health Promotion Center, Seoul National University Bundang Hospital, Seongnam, Korea.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22101690863%22">Digital health</searchLink> [Digit Health] 2025 Nov 07; Vol. 11, pp. 20552076251395570. <i>Date of Electronic Publication: </i>2025 Nov 07 (<i>Print Publication: </i>2025).
– Name: TypePub
  Label: Publication Type
  Group: TypPub
  Data: Journal Article
– Name: TitleSource
  Label: Journal Info
  Group: Src
  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22SAGE+Publications+Ltd%22">SAGE Publications Ltd </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101690863 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Print <i>ISSN: </i>2055-2076 (Print) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2220552076%22">20552076 </searchLink><i>NLM ISO Abbreviation: </i>Digit Health <i>Subsets: </i>PubMed not MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41229925
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1177/20552076251395570
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: 20552076251395570
    Titles:
      – TitleFull: Machine learning-based fatigue classification using heart rate variability and cortisol: A multimodal approach to wearable health monitoring.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Kim JE
      – PersonEntity:
          Name:
            NameFull: Kim NH
      – PersonEntity:
          Name:
            NameFull: Choi SK
      – PersonEntity:
          Name:
            NameFull: Lee JY
      – PersonEntity:
          Name:
            NameFull: Lee K
      – PersonEntity:
          Name:
            NameFull: Han JS
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 07
              M: 11
              Text: 2025 Nov 07
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 2055-2076
          Numbering:
            – Type: volume
              Value: 11
          Titles:
            – TitleFull: Digital health
              Type: main
ResultId 1