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Accepted (AM)Open Access (License Unspecified), Open
Journal article
Decision Trees for Detection of Activity Intensity in Youth with Cerebral Palsy
Medicine and science in sports and exercise, v 48(5), pp 958-966
01 May 2016
PMID: 26673127
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Purpose To develop and test decision tree (DT) models to classify physical activity (PA) intensity from accelerometer output and Gross Motor Function Classification System (GMFCS) classification level in ambulatory youth with cerebral palsy (CP) and compare the classification accuracy of the new DT models to that achieved by previously published cut points for youth with CP.
Methods Youth with CP (GMFCS levels I-III) (N = 51) completed seven activity trials with increasing PA intensity while wearing a portable metabolic system and ActiGraph GT3X accelerometers. DT models were used to identify vertical axis (VA) and vector magnitude (VM) count thresholds corresponding to sedentary (SED) (<1.5 METs), light-intensity PA (LPA) (1.5 and <3 METs) and moderate-to-vigorous PA (MVPA) (3 METs). Models were trained and cross-validated using the rpart and caret packages within R.
Results For the VA (VA_DT) and VM DT (VM_DT), a single threshold differentiated LPA from SED, whereas the threshold for differentiating MVPA from LPA decreased as the level of impairment increased. The average cross-validation accuracies for the VC_DT were 81.1%, 76.7%, and 82.9% for GMFCS levels I, II, and III. The corresponding cross-validation accuracies for the VM_DT were 80.5%, 75.6%, and 84.2%. Within each GMFCS level, the DT models achieved better PA intensity recognition than previously published cut points. The accuracy differential was greatest among GMFCS level III participants, in whom the previously published cut points misclassified 40% of the MVPA activity trials.
Conclusions The GMFCS-specific cut points provide more accurate assessments of MVPA levels in youth with CP across the full spectrum of ambulatory ability.
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Details
- Title
- Decision Trees for Detection of Activity Intensity in Youth with Cerebral Palsy
- Creators
- Stewart G. Trost - Queensland University of TechnologyMaria Fragala-Pinkham - Franciscan Hospital for ChildrenNancy Lennon - Dupont HospitalMargaret E. O'Neil - Drexel University
- Publication Details
- Medicine and science in sports and exercise, v 48(5), pp 958-966
- Publisher
- Lippincott Williams & Wilkins
- Number of pages
- 9
- Grant note
- R24 HD065688-01 / NIH; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA R24HD065688 / EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Physical Therapy (and Rehabilitation Sciences)
- Web of Science ID
- WOS:000374782200025
- Scopus ID
- 2-s2.0-84950144699
- Other Identifier
- 991019169011604721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Sport Sciences