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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Detalles Bibliográficos
Autores principales: Wang, Fu-Cheng, Chen, Szu-Fu, Lin, Chin-Hsien, Shih, Chih-Jen, Lin, Ang-Chieh, Yuan, Wei, Li, You-Chi, Kuo, Tien-Yun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7962128/
https://www.ncbi.nlm.nih.gov/pubmed/33800061
http://dx.doi.org/10.3390/s21051864

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7962128/
https://www.ncbi.nlm.nih.gov/pubmed/33800061
http://dx.doi.org/10.3390/s21051864

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