Sensor Data Acquisition and Multimodal Sensor Fusion for Human Activity Recognition Using Deep Learning

In this paper, we perform a systematic study about the on-body sensor positioning and data acquisition details for Human Activity Recognition (HAR) systems. We build a testbed that consists of eight body-worn Inertial Measurement Units (IMU) sensors and an Android mobile device for activity data col...

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Detalles Bibliográficos
Autores principales: Chung, Seungeun, Lim, Jiyoun, Noh, Kyoung Ju, Kim, Gague, Jeong, Hyuntae
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6479605/
https://www.ncbi.nlm.nih.gov/pubmed/30974845
http://dx.doi.org/10.3390/s19071716

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6479605/
https://www.ncbi.nlm.nih.gov/pubmed/30974845
http://dx.doi.org/10.3390/s19071716

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