Comparison of End-to-End Neural Network Architectures and Data Augmentation Methods for Automatic Infant Motility Assessment Using Wearable Sensors

Comparison of End-to-End Neural Network Architectures and Data Augmentation Methods for Automatic Infant Motility Assessment Using Wearable Sensors

Infant motility assessment using intelligent wearables is a promising new approach for assessment of infant neurophysiological development, and where efficient signal analysis plays a central role. This study investigates the use of different end-to-end neural network architectures for processing in...

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Bibliographic Details
Main Authors: Manu Airaksinen, Sampsa Vanhatalo, Okko Räsänen
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Sensors
Subjects:
human activity recognition
classifier architectures
wearable technology
infant motility
Online Access:https://www.mdpi.com/1424-8220/23/7/3773

Internet

https://www.mdpi.com/1424-8220/23/7/3773

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