Automatic extraction and detection of characteristic movement patterns in children with ADHD based on a Convolutional Neural Network (CNN) and acceleration images

Munoz-Organero, M., Powell, L.A. orcid.org/0000-0003-0230-8722, Heller, B. et al. (2 more authors) (2018) Automatic extraction and detection of characteristic movement patterns in children with ADHD based on a Convolutional Neural Network (CNN) and acceleration images. Sensors, 18 (11). 3924. ISSN 1424-8220

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Keywords: ADHD; tri-axial accelerometers; deep learning; convolutional neural networks (CNN)
Dates:
  • Accepted: 12 November 2018
  • Published (online): 14 November 2018
  • Published: 14 November 2018
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) > ScHARR - Sheffield Centre for Health and Related Research
Depositing User: Symplectic Sheffield
Date Deposited: 15 Nov 2018 16:23
Last Modified: 25 Jun 2023 21:35
Published Version: https://doi.org/10.3390/s18113924
Status: Published
Publisher: MDPI
Refereed: Yes
Identification Number: https://doi.org/10.3390/s18113924

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