Machine Learning and Statistical Analyses of Sensor Data Reveal Variability Between Repeated Trials in Parkinson’s Disease Mobility Assessments

Machine Learning and Statistical Analyses of Sensor Data Reveal Variability Between Repeated Trials in Parkinson’s Disease Mobility Assessments

Mobility tasks like the Timed Up and Go test (TUG), cognitive TUG (cogTUG), and walking with turns provide insights into the impact of Parkinson’s disease (PD) on motor control, balance, and cognitive function. We assess the test–retest reliability of these tasks in 262 PD participants and 50 contro...

Full description

Saved in:
Bibliographic Details
Main Authors: Rana M. Khalil, Lisa M. Shulman, Ann L. Gruber-Baldini, Sunita Shakya, Jeffrey M. Hausdorff, Rainer von Coelln, Michael P. Cummings
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Sensors
Subjects:
Parkinson’s disease
mobility tasks
wearable sensors
test–retest reliability
intraclass correlation coefficient
machine learning
Online Access:https://www.mdpi.com/1424-8220/24/24/8096
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/1424-8220/24/24/8096

Similar Items