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Improving Accelerometry-Based Measurement of Functional Use of the Upper Extremity After Stroke: Machine Learning Versus Counts Threshold Method
BACKGROUND: Wrist-worn accelerometry provides objective monitoring of upper-extremity functional use, such as reaching tasks, but also detects nonfunctional movements, leading to ambiguity in monitoring results. OBJECTIVE: Compare machine learning algorithms with standard methods (counts ratio) to i...
שמור ב:
| הוצא לאור ב: | Neurorehabil Neural Repair |
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| Main Authors: | , , , , , , |
| פורמט: | Artigo |
| שפה: | Inglês |
| יצא לאור: |
SAGE Publications
2020
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| נושאים: | |
| גישה מקוונת: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7704838/ https://ncbi.nlm.nih.gov/pubmed/33150830 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1177/1545968320962483 |
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