A User-Adaptive Algorithm for Activity Recognition Based on K-Means Clustering, Local Outlier Factor, and Multivariate Gaussian Distribution

Mobile activity recognition is significant to the development of human-centric pervasive applications including elderly care, personalized recommendations, etc. Nevertheless, the distribution of inertial sensor data can be influenced to a great extent by varying users. This means that the performanc...

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Detalles Bibliográficos
Autores principales: Zhao, Shizhen, Li, Wenfeng, Cao, Jingjing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022149/
https://www.ncbi.nlm.nih.gov/pubmed/29882788
http://dx.doi.org/10.3390/s18061850

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022149/
https://www.ncbi.nlm.nih.gov/pubmed/29882788
http://dx.doi.org/10.3390/s18061850

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