Machine Learning-Based Classification of Dependence in Ambulation in Stroke Patients Using Smartphone Video Data

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 actio...

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Veröffentlicht in:	Journal of personalized medicine 2021-10, Vol.11 (11), p.1080
Hauptverfasser:	Lee, Jong Taek, Park, Eunhee, Jung, Tae-Du
Format:	Artikel
Sprache:	eng
Schlagworte:	Asymmetry Caregivers Classification Falls Learning algorithms Machine learning Mobility Neural networks Patients Posture Precision medicine Rehabilitation Smartphones Stroke Walking
Online-Zugang:	Volltext
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