Deep Convolutional and LSTM Networks on Multi-Channel Time Series Data for Gait Phase Recognition

Deep Convolutional and LSTM Networks on Multi-Channel Time Series Data for Gait Phase Recognition

With an ageing society comes the increased prevalence of gait disorders. The restriction of mobility leads to a considerable reduction in the quality of life, because associated falls increase morbidity and mortality. Consideration of gait analysis data often alters surgical recommendations. For tha...

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Bibliographic Details
Main Authors: David Kreuzer, Michael Munz
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Sensors
Subjects:
gait analysis
deep learning
LSTM networks
convolutional neural networks
ConvLSTM networks
gait phase detection
Online Access:https://www.mdpi.com/1424-8220/21/3/789

Internet

https://www.mdpi.com/1424-8220/21/3/789

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