Machine learning algorithms for activity recognition in ambulant children and adolescents with cerebral palsy

Machine learning algorithms for activity recognition in ambulant children and adolescents with cerebral palsy

Abstract Background Cerebral palsy (CP) is the most common physical disability among children (2.5 to 3.6 cases per 1000 live births). Inadequate physical activity (PA) is a major problem effecting the health and well-being of children with CP. Practical, yet accurate measures of PA are needed to ev...

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Bibliographic Details
Main Authors: Matthew Ahmadi, Margaret O’Neil, Maria Fragala-Pinkham, Nancy Lennon, Stewart Trost
Format: Article
Language:English
Published: BMC 2018-11-01
Series:Journal of NeuroEngineering and Rehabilitation
Subjects:
Accelerometers
Wearable sensors
Placement
Feature fusion
Habitual physical activity
GMFCS level
Online Access:http://link.springer.com/article/10.1186/s12984-018-0456-x

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http://link.springer.com/article/10.1186/s12984-018-0456-x

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