FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3209359543> ?p ?o ?g. }

• W3209359543 endingPage "1080" @default.
• W3209359543 startingPage "1080" @default.
• W3209359543 abstract "The goal of this study was to develop a framework to classify dependence in ambulation by employing a deep model in a 3D convolutional neural network (3D-CNN) using video data recorded by a smartphone during inpatient rehabilitation therapy in stroke patients. Among 2311 video clips, 1218 walk action cases were collected from 206 stroke patients receiving inpatient rehabilitation therapy (63.24 ± 14.36 years old). As ground truth, the dependence in ambulation was assessed and labeled using the functional ambulatory categories (FACs) and Berg balance scale (BBS). The dependent ambulation was defined as a FAC score less than 4 or a BBS score less than 45. We extracted patient-centered video and patient-centered pose of the target from the tracked target's posture keypoint location information. Then, the extracted patient-centered video was input in the 3D-CNN, and the extracted patient-centered pose was used to measure swing time asymmetry. Finally, we evaluated the classification of dependence in ambulation using video data via fivefold cross-validation. When training the 3D-CNN based on FACs and BBS, the model performed with 86.3% accuracy, 87.4% precision, 94.0% recall, and 90.5% F1 score. When the 3D-CNN based on FACs and BBS was combined with swing time asymmetry, the model exhibited improved performance (88.7% accuracy, 89.1% precision, 95.7% recall, and 92.2% F1 score). The proposed framework for dependence in ambulation can be useful, as it alerts clinicians or caregivers when stroke patients with dependent ambulatory move alone without assistance. In addition, monitoring dependence in ambulation can facilitate the design of individualized rehabilitation strategies for stroke patients with impaired mobility and balance function." @default.
• W3209359543 created "2021-11-08" @default.
• W3209359543 creator A5000134514 @default.
• W3209359543 creator A5067712031 @default.
• W3209359543 creator A5074514628 @default.
• W3209359543 date "2021-10-25" @default.
• W3209359543 modified "2023-09-22" @default.
• W3209359543 title "Machine Learning-Based Classification of Dependence in Ambulation in Stroke Patients Using Smartphone Video Data" @default.
• W3209359543 cites W1763608500 @default.
• W3209359543 cites W1983364832 @default.
• W3209359543 cites W2004149082 @default.
• W3209359543 cites W2009699714 @default.
• W3209359543 cites W2034899024 @default.
• W3209359543 cites W2054107585 @default.
• W3209359543 cites W2062902497 @default.
• W3209359543 cites W2077228124 @default.
• W3209359543 cites W2082585951 @default.
• W3209359543 cites W2085892632 @default.
• W3209359543 cites W2103780294 @default.
• W3209359543 cites W2139049236 @default.
• W3209359543 cites W2161666008 @default.
• W3209359543 cites W2292714322 @default.
• W3209359543 cites W2343176363 @default.
• W3209359543 cites W2410400311 @default.
• W3209359543 cites W2513097088 @default.
• W3209359543 cites W2609286783 @default.
• W3209359543 cites W2734548032 @default.
• W3209359543 cites W2743141752 @default.
• W3209359543 cites W2767117939 @default.
• W3209359543 cites W2902800037 @default.
• W3209359543 cites W2952542297 @default.
• W3209359543 cites W2962459300 @default.
• W3209359543 cites W2962730651 @default.
• W3209359543 cites W3019313496 @default.
• W3209359543 cites W3088102655 @default.
• W3209359543 cites W3092746285 @default.
• W3209359543 cites W3125697162 @default.
• W3209359543 cites W3170889335 @default.
• W3209359543 cites W3184425660 @default.
• W3209359543 doi "https://doi.org/10.3390/jpm11111080" @default.
• W3209359543 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8623599" @default.
• W3209359543 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34834432" @default.
• W3209359543 hasPublicationYear "2021" @default.
• W3209359543 type Work @default.
• W3209359543 sameAs 3209359543 @default.
• W3209359543 citedByCount "4" @default.
• W3209359543 countsByYear W32093595432022 @default.
• W3209359543 countsByYear W32093595432023 @default.
• W3209359543 crossrefType "journal-article" @default.
• W3209359543 hasAuthorship W3209359543A5000134514 @default.
• W3209359543 hasAuthorship W3209359543A5067712031 @default.
• W3209359543 hasAuthorship W3209359543A5074514628 @default.
• W3209359543 hasBestOaLocation W32093595431 @default.
• W3209359543 hasConcept C100660578 @default.
• W3209359543 hasConcept C126322002 @default.
• W3209359543 hasConcept C127413603 @default.
• W3209359543 hasConcept C154945302 @default.
• W3209359543 hasConcept C15744967 @default.
• W3209359543 hasConcept C168031717 @default.
• W3209359543 hasConcept C180747234 @default.
• W3209359543 hasConcept C1862650 @default.
• W3209359543 hasConcept C2777611552 @default.
• W3209359543 hasConcept C2778818304 @default.
• W3209359543 hasConcept C2780645631 @default.
• W3209359543 hasConcept C35785553 @default.
• W3209359543 hasConcept C41008148 @default.
• W3209359543 hasConcept C71924100 @default.
• W3209359543 hasConcept C78519656 @default.
• W3209359543 hasConcept C81363708 @default.
• W3209359543 hasConcept C99508421 @default.
• W3209359543 hasConceptScore W3209359543C100660578 @default.
• W3209359543 hasConceptScore W3209359543C126322002 @default.
• W3209359543 hasConceptScore W3209359543C127413603 @default.
• W3209359543 hasConceptScore W3209359543C154945302 @default.
• W3209359543 hasConceptScore W3209359543C15744967 @default.
• W3209359543 hasConceptScore W3209359543C168031717 @default.
• W3209359543 hasConceptScore W3209359543C180747234 @default.
• W3209359543 hasConceptScore W3209359543C1862650 @default.
• W3209359543 hasConceptScore W3209359543C2777611552 @default.
• W3209359543 hasConceptScore W3209359543C2778818304 @default.
• W3209359543 hasConceptScore W3209359543C2780645631 @default.
• W3209359543 hasConceptScore W3209359543C35785553 @default.
• W3209359543 hasConceptScore W3209359543C41008148 @default.
• W3209359543 hasConceptScore W3209359543C71924100 @default.
• W3209359543 hasConceptScore W3209359543C78519656 @default.
• W3209359543 hasConceptScore W3209359543C81363708 @default.
• W3209359543 hasConceptScore W3209359543C99508421 @default.
• W3209359543 hasFunder F4320322093 @default.
• W3209359543 hasFunder F4320322120 @default.
• W3209359543 hasIssue "11" @default.
• W3209359543 hasLocation W32093595431 @default.
• W3209359543 hasLocation W32093595432 @default.
• W3209359543 hasLocation W32093595433 @default.
• W3209359543 hasLocation W32093595434 @default.
• W3209359543 hasOpenAccess W3209359543 @default.
• W3209359543 hasPrimaryLocation W32093595431 @default.
• W3209359543 hasRelatedWork W1995127536 @default.
• W3209359543 hasRelatedWork W2027683689 @default.

• next