Prediction of activity type in preschool children using machine learning techniques

Journal of Science and Medicine in Sport

Volumn 18, Issue 4, 2015, Pages 426-431

  Hagenbuchner, Markus ^a   Cliff, Dylan P ^a   Trost, Stewart G ^b   Van Tuc, Nguyen ^a   Peoples, Gregory E ^a  

^a UNIVERSITY OF WOLLONGONG   (Australia)

^b QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

Author keywords

Accelerometry; Exercise; Neural networks; Pattern recognition; Physical activity; Validity

Indexed keywords

ACCELEROMETER; ACCELEROMETRY; ART; ARTICLE; ARTIFICIAL NEURAL NETWORK; CHILD; CLEANING; COMPARATIVE STUDY; CONTROLLED STUDY; CYCLING; DEEP LEARNING ENSEMBLE NETWORK; FEMALE; GAME; HIP; HUMAN; HUMAN EXPERIMENT; LABORATORY; MACHINE LEARNING; MALE; MEASUREMENT ACCURACY; NORMAL HUMAN; PHYSICAL ACTIVITY; PLAY; PREDICTION; PREDICTIVE VALUE; PRESCHOOL CHILD; READING; RUNNING; SITTING; SPORT; WALKING; DAILY LIFE ACTIVITY; MOTOR ACTIVITY; RECREATION; THEORETICAL MODEL;

ACCELEROMETRY; ACTIVITIES OF DAILY LIVING; BICYCLING; CHILD; CHILD, PRESCHOOL; FEMALE; HUMANS; MACHINE LEARNING; MALE; MODELS, THEORETICAL; MOTOR ACTIVITY; NEURAL NETWORKS (COMPUTER); PLAY AND PLAYTHINGS; RUNNING; WALKING;

EID: 84946475689     PISSN: 14402440     EISSN: 18781861     Source Type: Journal    
DOI: 10.1016/j.jsams.2014.06.003     Document Type: Article

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