A novel algorithm to detect non-wear time from raw accelerometer data using deep convolutional neural networks

A novel algorithm to detect non-wear time from raw accelerometer data using deep convolutional neural networks

Abstract To date, non-wear detection algorithms commonly employ a 30, 60, or even 90 mins interval or window in which acceleration values need to be below a threshold value. A major drawback of such intervals is that they need to be long enough to prevent false positives (type I errors), while short...

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Autores principales: Shaheen Syed, Bente Morseth, Laila A. Hopstock, Alexander Horsch
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
Medicine
R
Science
Q
Acceso en línea:https://doaj.org/article/23d4d98bfba6484ebb75713885ef5f1e
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