Smart Annotation of Cyclic Data Using Hierarchical Hidden Markov Models

Cyclic signals are an intrinsic part of daily life, such as human motion and heart activity. The detailed analysis of them is important for clinical applications such as pathological gait analysis and for sports applications such as performance analysis. Labeled training data for algorithms that ana...

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Detalles Bibliográficos
Autores principales: Martindale, Christine F., Hoenig, Florian, Strohrmann, Christina, Eskofier, Bjoern M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5676753/
https://www.ncbi.nlm.nih.gov/pubmed/29027973
http://dx.doi.org/10.3390/s17102328

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5676753/
https://www.ncbi.nlm.nih.gov/pubmed/29027973
http://dx.doi.org/10.3390/s17102328

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