Deep Learning to Predict Falls in Older Adults Based on Daily-Life Trunk Accelerometry

Early detection of high fall risk is an essential component of fall prevention in older adults. Wearable sensors can provide valuable insight into daily-life activities; biomechanical features extracted from such inertial data have been shown to be of added value for the assessment of fall risk. Bod...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Ahmed Nait Aicha, Gwenn Englebienne, Kimberley S. van Schooten, Mirjam Pijnappels, Ben Kröse
Format: Artigo
Sprache:Inglês
Veröffentlicht: MDPI AG 2018-05-01
Schriftenreihe:Sensors
Schlagworte:
accidental falls
older adults
machine learning
neural networks
convolutional neural network
long short-term memory
accelerometry
Online Zugang:http://www.mdpi.com/1424-8220/18/5/1654
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge