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Evaluation Of Artificial Neural Network Algorithms For Predicting Mets And Activity Type From Accelerometer Data: Validation On An Independent Sample, Patty S. Freedson, Kate Lyden, Sarah Kozey-Keadle, John Staudenmayer
Evaluation Of Artificial Neural Network Algorithms For Predicting Mets And Activity Type From Accelerometer Data: Validation On An Independent Sample, Patty S. Freedson, Kate Lyden, Sarah Kozey-Keadle, John Staudenmayer
Patty S. Freedson
Previous work from our laboratory provided a “proof of concept” for use of artificial neural networks (nnets) to estimate metabolic equivalents (METs) and identify activity type from accelerometer data (Staudenmayer J, Pober D, Crouter S, Bassett D, Freedson P, J Appl Physiol 107: 1330–1307, 2009). The purpose of this study was to develop new nnets based on a larger, more diverse, training data set and apply these nnet prediction models to an independent sample to evaluate the robustness and flexibility of this machine-learning modeling technique. The nnet training data set (University of Massachusetts) included 277 participants who each completed 11 …
A Comprehensive Evaluation Of Commonly Used Accelerometer Energy Expenditure And Met Prediction Equations, Kate Lyden, Sarah L. Kozey, John W. Staudenmayer, Patty S. Freedson
A Comprehensive Evaluation Of Commonly Used Accelerometer Energy Expenditure And Met Prediction Equations, Kate Lyden, Sarah L. Kozey, John W. Staudenmayer, Patty S. Freedson
Patty S. Freedson
Numerous accelerometers and prediction methods are used to estimate energy expenditure (EE). Validation studies have been limited to small sample sizes in which participants complete a narrow range of activities and typically validate only one or two prediction models for one particular accelerometer. Purpose—To evaluate the validity of nine published and two proprietary EE prediction equations for three different accelerometers. Methods—277 participants completed an average of 6 treadmill (TRD) (1.34, 1.56, 2.23 m・sec−1 each at 0% and 3% grade) and 5 self-paced activities of daily living (ADLs). EE estimates were compared to indirect calorimetry. Accelerometers were worn while EE was …
A Comprehensive Evaluation Of Commonly Used Accelerometer Energy Expenditure And Met Prediction Equations, Kate Lyden, Sarah L. Kozey, John W. Staudenmayer, Patty S. Freedson
A Comprehensive Evaluation Of Commonly Used Accelerometer Energy Expenditure And Met Prediction Equations, Kate Lyden, Sarah L. Kozey, John W. Staudenmayer, Patty S. Freedson
Patty S. Freedson
Numerous accelerometers and prediction methods are used to estimate energy expenditure (EE). Validation studies have been limited to small sample sizes in which participants complete a narrow range of activities and typically validate only one or two prediction models for one particular accelerometer. Purpose—To evaluate the validity of nine published and two proprietary EE prediction equations for three different accelerometers. Methods—277 participants completed an average of 6 treadmill (TRD) (1.34, 1.56, 2.23 m・sec−1 each at 0% and 3% grade) and 5 self-paced activities of daily living (ADLs). EE estimates were compared to indirect calorimetry. Accelerometers were worn while EE was …