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Machine Learning to Quantify Physical Activity in Children with Cerebral Palsy: Comparison of Group, Group-Personalized, and Fully-Personalized Activity Classification Models

Pattern recognition methodologies, such as those utilizing machine learning (ML) approaches, have the potential to improve the accuracy and versatility of accelerometer-based assessments of physical activity (PA). Children with cerebral palsy (CP) exhibit significant heterogeneity in relation to imp...

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書誌詳細
出版年:Sensors (Basel)
主要な著者: Ahmadi, Matthew N., O’Neil, Margaret E., Baque, Emmah, Boyd, Roslyn N., Trost, Stewart G.
フォーマット: Artigo
言語:Inglês
出版事項: MDPI 2020
主題:
オンライン・アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC7411900/
https://ncbi.nlm.nih.gov/pubmed/32708963
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s20143976
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