Detection and Classification of Stroke Gaits by Deep Neural Networks Employing Inertial Measurement Units

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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Bibliographic Details
Main Authors: Fu-Cheng Wang, Szu-Fu Chen, Chin-Hsien Lin, Chih-Jen Shih, Ang-Chieh Lin, Wei Yuan, You-Chi Li, Tien-Yun Kuo
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Sensors
Subjects:
gait recognition
deep learning
neural network
stroke gait
IMU (inertial measurement unit)
Online Access:https://www.mdpi.com/1424-8220/21/5/1864

Internet

https://www.mdpi.com/1424-8220/21/5/1864

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