Comparison of the Validity and Generalizability of Machine Learning Algorithms for the Prediction of Energy Expenditure: Validation Study

Improving energy expenditure estimates from wearable devices: A machine learning approach

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Laboratory-based and free-living algorithms for energy expenditure estimation in preschool children: A free-living evaluation

(2020) Matthew N. Ahmadi et al.   PLoS One

A novel scaling methodology to reduce the biases associated with missing data from commercial activity monitors

(2020) R. O’Driscoll et al.   PLoS One

Machine learning algorithm validation with a limited sample size

(2019) Andrius Vabalas et al.   PLoS One

Evaluating and Enhancing the Generalization Performance of Machine Learning Models for Physical Activity Intensity Prediction From Raw Acceleration Data

(2019) Vahid Farrahi et al.   IEEE Journal of Biomedical and Health Informatics

Cross-validation and out-of-sample testing of physical activity intensity predictions with a wrist-worn accelerometer

(2018) Alexander H. K. Montoye et al.   JOURNAL OF APPLIED PHYSIOLOGY

Energy Intake Derived from an Energy Balance Equation, Validated Activity Monitors, and Dual X-Ray Absorptiometry Can Provide Acceptable Caloric Intake Data among Young Adults

(2018) Robin P Shook et al.   JOURNAL OF NUTRITION

A review of machine learning in obesity

(2018) K. W. DeGregory et al.   Obesity Reviews

Statistical machine learning of sleep and physical activity phenotypes from sensor data in 96,220 UK Biobank participants

(2018) Matthew Willetts et al.   Scientific Reports

How well do activity monitors estimate energy expenditure? A systematic review and meta-analysis of the validity of current technologies

(2018) Ruairi O’Driscoll et al.   BRITISH JOURNAL OF SPORTS MEDICINE

Fusion of Heart Rate, Respiration and Motion Measurements from a Wearable Sensor System to Enhance Energy Expenditure Estimation

(2018) Ke Lu et al.   SENSORS

Accuracy of Fitbit Devices: Systematic Review and Narrative Syntheses of Quantitative Data

(2018) Lynne M Feehan et al.   JMIR mHealth and uHealth

Impact of physical activity level and dietary fat content on passive overconsumption of energy in non-obese adults

(2017) Kristine Beaulieu et al.   International Journal of Behavioral Nutrition and Physical Activity

Ensemble Methods for Classification of Physical Activities from Wrist Accelerometry

(2017) ALOK KUMAR CHOWDHURY et al.   MEDICINE AND SCIENCE IN SPORTS AND EXERCISE

Objectively Measured Physical Activity and Sedentary Behavior in Successful Weight Loss Maintainers

(2017) Danielle M. Ostendorf et al.   Obesity

Comparison of linear and non-linear models for predicting energy expenditure from raw accelerometer data

(2017) Alexander H K Montoye et al.   PHYSIOLOGICAL MEASUREMENT

Reliability of resting metabolic rate measurements in young adults: Impact of methods for data analysis

(2017) Guillermo Sanchez-Delgado et al.   CLINICAL NUTRITION

Comparing the standards of one metabolic equivalent of task in accurately estimating physical activity energy expenditure based on acceleration

(2016) Dohyun Kim et al.   JOURNAL OF SPORTS SCIENCES

Hip and Wrist Accelerometer Algorithms for Free-Living Behavior Classification

(2016) KATHERINE ELLIS et al.   MEDICINE AND SCIENCE IN SPORTS AND EXERCISE

Performance of Activity Classification Algorithms in Free-Living Older Adults

(2016) JEFFER EIDI SASAKI et al.   MEDICINE AND SCIENCE IN SPORTS AND EXERCISE

Comparative evaluation of features and techniques for identifying activity type and estimating energy cost from accelerometer data

(2016) Rohit J Kate et al.   PHYSIOLOGICAL MEASUREMENT

Statistical approaches to account for missing values in accelerometer data: Applications to modeling physical activity

(2016) Selene Yue Xu et al.   STATISTICAL METHODS IN MEDICAL RESEARCH

Metabolic Equivalent in Adolescents, Active Adults and Pregnant Women

(2016) Katarina Melzer et al.   Nutrients

Automatic identification of physical activity types and sedentary behaviors from triaxial accelerometer: laboratory-based calibrations are not enough

(2015) Thomas Bastian et al.   JOURNAL OF APPLIED PHYSIOLOGY

Fitting Linear Mixed-Effects Models Usinglme4

(2015) Douglas Bates et al.   Journal of Statistical Software

Building Predictive Models inRUsing thecaretPackage

(2015) Max Kuhn   Journal of Statistical Software

Validity of physical activity monitors for assessing lower intensity activity in adults

(2014) M Andr s Calabr  et al.   International Journal of Behavioral Nutrition and Physical Activity

Light-Intensity Activity Attenuates Functional Decline in Older Cancer Survivors

(2014) CINDY K. BLAIR et al.   MEDICINE AND SCIENCE IN SPORTS AND EXERCISE

A random forest classifier for the prediction of energy expenditure and type of physical activity from wrist and hip accelerometers

(2014) Katherine Ellis et al.   PHYSIOLOGICAL MEASUREMENT

Data imputation for accelerometer-measured physical activity: the combined approach

(2013) Paul H Lee   AMERICAN JOURNAL OF CLINICAL NUTRITION

Using the SenseCam to Improve Classifications of Sedentary Behavior in Free-Living Settings

(2013) Jacqueline Kerr et al.   AMERICAN JOURNAL OF PREVENTIVE MEDICINE

Physical activity and physical activity induced energy expenditure in humans: measurement, determinants, and effects

(2013) Klass R. Westerterp   Frontiers in Physiology

An evaluation of the IDEEA™ activity monitor for estimating energy expenditure

(2012) Stephen Whybrow et al.   BRITISH JOURNAL OF NUTRITION

Physical Activity Classification Using the GENEA Wrist-Worn Accelerometer

(2011) SHAOYAN ZHANG et al.   MEDICINE AND SCIENCE IN SPORTS AND EXERCISE

A comprehensive evaluation of commonly used accelerometer energy expenditure and MET prediction equations

(2010) Kate Lyden et al.   EUROPEAN JOURNAL OF APPLIED PHYSIOLOGY

Accelerometer Output and MET Values of Common Physical Activities

(2010) SARAH L. KOZEY et al.   MEDICINE AND SCIENCE IN SPORTS AND EXERCISE

An artificial neural network to estimate physical activity energy expenditure and identify physical activity type from an accelerometer

(2009) John Staudenmayer et al.   JOURNAL OF APPLIED PHYSIOLOGY