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Detection and Classification of Stroke Gaits by Deep Neural Networks Employing Inertial Measurement Units
This paper develops Deep Neural Network (DNN) models that can recognize stroke gaits. Stroke patients usually suffer from partial disability and develop abnormal gaits that can vary widely and need targeted treatments. Evaluation of gait patterns is crucial for clinical experts to make decisions abo...
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| Publicado no: | Sensors (Basel) |
|---|---|
| Main Authors: | , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI
2021
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7962128/ https://ncbi.nlm.nih.gov/pubmed/33800061 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s21051864 |
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