Using Recurrent Neural Networks to Compare Movement Patterns in ADHD and Normally Developing Children Based on Acceleration Signals from the Wrist and Ankle

Using Recurrent Neural Networks to Compare Movement Patterns in ADHD and Normally Developing Children Based on Acceleration Signals from the Wrist and Ankle

Attention deficit and hyperactivity disorder (ADHD) is a neurodevelopmental condition that affects, among other things, the movement patterns of children suffering it. Inattention, hyperactivity and impulsive behaviors, major symptoms characterizing ADHD, result not only in differences in the activi...

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Bibliographic Details
Main Authors: Mario Muñoz-Organero, Lauren Powell, Ben Heller, Val Harpin, Jack Parker
Format: Article
Language:English
Published: MDPI AG 2019-07-01
Series:Sensors
Subjects:
ADHD
tri-axial accelerometers
deep learning
Recurrent Neural Networks (RNN)
Long Short Term Memory (LSTM)
Online Access:https://www.mdpi.com/1424-8220/19/13/2935

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