View in EDS

Prediction of knee loads during activities of daily living using custom instrumented insoles and machine learning.

Saved in:
Bibliographic Details
Title: Prediction of knee loads during activities of daily living using custom instrumented insoles and machine learning.
Authors: Snyder SJ; Orthopedics and Sports Medicine, MedStar Health Research Institute, Baltimore, United States; Department of Kinesiology, University of Maryland, College Park, United States. Electronic address: samantha.snyder@medstar.net., Fakhar M; Department of Kinesiology, University of Maryland, College Park, United States. Electronic address: mfakhar@umd.edu., Miller RH; Department of Kinesiology, University of Maryland, College Park, United States; Neuroscience and Cognitive Science Program, University of Maryland, United States. Electronic address: rosshm@umd.edu., Bera A; Department of Computer Science, Purdue University, West Lafayette, United States; Department of Computer Science, University of Maryland, College Park, United States. Electronic address: ab@cs.purdue.edu., Shim JK; Department of Kinesiology, University of Maryland, College Park, United States; Neuroscience and Cognitive Science Program, University of Maryland, United States. Electronic address: jkshim@umd.edu.
Source: Journal of biomechanics [J Biomech] 2025 Oct; Vol. 191, pp. 112921. Date of Electronic Publication: 2025 Aug 19.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Science Country of Publication: United States NLM ID: 0157375 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-2380 (Electronic) Linking ISSN: 00219290 NLM ISO Abbreviation: J Biomech Subsets: MEDLINE
Database: MEDLINE Ultimate
FullText Text:
  Availability: 0
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 40885049
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Prediction of knee loads during activities of daily living using custom instrumented insoles and machine learning.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Snyder+SJ%22">Snyder SJ</searchLink>; Orthopedics and Sports Medicine, MedStar Health Research Institute, Baltimore, United States; Department of Kinesiology, University of Maryland, College Park, United States. Electronic address: samantha.snyder@medstar.net.<br /><searchLink fieldCode="AU" term="%22Fakhar+M%22">Fakhar M</searchLink>; Department of Kinesiology, University of Maryland, College Park, United States. Electronic address: mfakhar@umd.edu.<br /><searchLink fieldCode="AU" term="%22Miller+RH%22">Miller RH</searchLink>; Department of Kinesiology, University of Maryland, College Park, United States; Neuroscience and Cognitive Science Program, University of Maryland, United States. Electronic address: rosshm@umd.edu.<br /><searchLink fieldCode="AU" term="%22Bera+A%22">Bera A</searchLink>; Department of Computer Science, Purdue University, West Lafayette, United States; Department of Computer Science, University of Maryland, College Park, United States. Electronic address: ab@cs.purdue.edu.<br /><searchLink fieldCode="AU" term="%22Shim+JK%22">Shim JK</searchLink>; Department of Kinesiology, University of Maryland, College Park, United States; Neuroscience and Cognitive Science Program, University of Maryland, United States. Electronic address: jkshim@umd.edu.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%220157375%22">Journal of biomechanics</searchLink> [J Biomech] 2025 Oct; Vol. 191, pp. 112921. <i>Date of Electronic Publication: </i>2025 Aug 19.
– 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="%22Elsevier+Science%22">Elsevier Science </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>0157375 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1873-2380 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2200219290%22">00219290 </searchLink><i>NLM ISO Abbreviation: </i>J Biomech <i>Subsets: </i>MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=40885049
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.jbiomech.2025.112921
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: 112921
    Titles:
      – TitleFull: Prediction of knee loads during activities of daily living using custom instrumented insoles and machine learning.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Snyder SJ
      – PersonEntity:
          Name:
            NameFull: Fakhar M
      – PersonEntity:
          Name:
            NameFull: Miller RH
      – PersonEntity:
          Name:
            NameFull: Bera A
      – PersonEntity:
          Name:
            NameFull: Shim JK
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 10
              Text: 2025 Oct
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-electronic
              Value: 1873-2380
          Numbering:
            – Type: volume
              Value: 191
          Titles:
            – TitleFull: Journal of biomechanics
              Type: main
ResultId 1