A Quantitative Comparison of Overlapping and Non-Overlapping Sliding Windows for Human Activity Recognition Using Inertial Sensors

The sliding window technique is widely used to segment inertial sensor signals, i.e., accelerometers and gyroscopes, for activity recognition. In this technique, the sensor signals are partitioned into fix sized time windows which can be of two types: (1) non-overlapping windows, in which time windo...

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Detalles Bibliográficos
Autores principales: Dehghani, Akbar, Sarbishei, Omid, Glatard, Tristan, Shihab, Emad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891351/
https://www.ncbi.nlm.nih.gov/pubmed/31752158
http://dx.doi.org/10.3390/s19225026

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891351/
https://www.ncbi.nlm.nih.gov/pubmed/31752158
http://dx.doi.org/10.3390/s19225026

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