Leg Motion Classification with Artificial Neural Networks Using Wavelet-Based Features of Gyroscope Signals

We extract the informative features of gyroscope signals using the discrete wavelet transform (DWT) decomposition and provide them as input to multi-layer feed-forward artificial neural networks (ANNs) for leg motion classification. Since the DWT is based on correlating the analyzed signal with a pr...

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Detalles Bibliográficos
Autores principales: Ayrulu-Erdem, Birsel, Barshan, Billur
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2011
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3274015/
https://www.ncbi.nlm.nih.gov/pubmed/22319378
http://dx.doi.org/10.3390/s110201721

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3274015/
https://www.ncbi.nlm.nih.gov/pubmed/22319378
http://dx.doi.org/10.3390/s110201721

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