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Gait Analysis with Wearables Can Accurately Classify Fallers from Non-Fallers: A Step toward Better Management of Neurological Disorders
Falls are the leading cause of mortality, morbidity and poor quality of life in older adults with or without neurological conditions. Applying machine learning (ML) models to gait analysis outcomes offers the opportunity to identify individuals at risk of future falls. The aim of this study was to d...
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| Опубликовано в: : | Sensors (Basel) |
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| Главные авторы: | , , , , , , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
MDPI
2020
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7729621/ https://ncbi.nlm.nih.gov/pubmed/33297395 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s20236992 |
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