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Quantifying normal and parkinsonian gait features from home movies: Practical application of a deep learning–based 2D pose estimator
OBJECTIVE: Gait movies recorded in daily clinical practice are usually not filmed with specific devices, which prevents neurologists benefitting from leveraging gait analysis technologies. Here we propose a novel unsupervised approach to quantifying gait features and to extract cadence from normal a...
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| Publicat a: | PLoS One |
|---|---|
| Autors principals: | , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Public Library of Science
2019
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6855634/ https://ncbi.nlm.nih.gov/pubmed/31725754 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0223549 |
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