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Articles 1 - 9 of 9

Full-Text Articles in Life Sciences

Validation Of A Previous Day Recall For Measuring The Location And Purpose Of Active And Sedentary Behaviors Compared To Direct Observation, Sarah Kozey Keadle, Kate Lyden, Amanda Hickey, Evan L. Ray, Jay H. Fowke, Patty S. Freedson, Charles E. Matthews Dec 2013

Validation Of A Previous Day Recall For Measuring The Location And Purpose Of Active And Sedentary Behaviors Compared To Direct Observation, Sarah Kozey Keadle, Kate Lyden, Amanda Hickey, Evan L. Ray, Jay H. Fowke, Patty S. Freedson, Charles E. Matthews

Patty S. Freedson

Purpose Gathering contextual information (i.e., location and purpose) about active and sedentary behaviors is an advantage of self-report tools such as previous day recalls (PDR). However, the validity of PDR’s for measuring context has not been empirically tested. The purpose of this paper was to compare PDR estimates of location and purpose to direct observation (DO). Methods Fifteen adult (18–75 y) and 15 adolescent (12–17 y) participants were directly observed during at least one segment of the day (i.e., morning, afternoon or evening). Participants completed their normal daily routine while trained observers recorded the location ...


Validation Of A Previous-Day Recall Measure Of Active And Sedentary Behaviors, Charles E. Matthews, Sarah Kozey Keadle, Joshua Sampson, Kate Lyden, Heather R. Bowles, Stephen C. Moore, Amanda Libertine, Patty S. Freedson, Jay H. Fowke Jul 2013

Validation Of A Previous-Day Recall Measure Of Active And Sedentary Behaviors, Charles E. Matthews, Sarah Kozey Keadle, Joshua Sampson, Kate Lyden, Heather R. Bowles, Stephen C. Moore, Amanda Libertine, Patty S. Freedson, Jay H. Fowke

Patty S. Freedson

Purpose—A previous-day recall (PDR) may be a less error prone alternative to traditional questionnaire-based estimates of physical activity and sedentary behavior (e.g., past year), but validity of the method is not established. We evaluated the validity of an interviewer administered PDR in adolescents (12–17 years) and adults (18–71 years). Methods—In a 7-day study, participants completed three PDRs, wore two activity monitors, and completed measures of social desirability and body mass index (BMI). PDR measures of active and sedentary time was contrasted against an accelerometer (ActiGraph) by comparing both to a valid reference measure (activPAL) using ...


Tissue Artifact Removal From Respiratory Signals Based On Empirical Mode Decomposition, Shaopeng Liu, Robert X. Gao, Dinesh John, John Staudenmayer, Patty S. Freedson Apr 2013

Tissue Artifact Removal From Respiratory Signals Based On Empirical Mode Decomposition, Shaopeng Liu, Robert X. Gao, Dinesh John, John Staudenmayer, Patty S. Freedson

Patty S. Freedson

On-line measurement of respiration plays an important role in monitoring human physical activities. Such measurement commonly employs sensing belts secured around the rib cage and abdomen of the test object. Affected by the movement of body tissues, respiratory signals typically have a low signal-to-noise ratio. Removing tissue artifacts therefore is critical to ensuring effective respiration analysis. This paper presents a signal decomposition technique for tissue artifact removal from respiratory signals, based on the empirical mode decomposition (EMD). An algorithm based on the mutual information and power criteria was devised to automatically select appropriate intrinsic mode functions (IMFs) for tissue artifact ...


Energy Cost Of Common Activities In Children And Adolescents, Kate Lyden, Sarah Kozey Keadle, John Staudenmayer, Patty S. Freedson, Sofiya Alhassan Dec 2012

Energy Cost Of Common Activities In Children And Adolescents, Kate Lyden, Sarah Kozey Keadle, John Staudenmayer, Patty S. Freedson, Sofiya Alhassan

Patty S. Freedson

Background—The Compendium of Energy Expenditures for Youth assigns MET values to a wide range of activities. However, only 35% of activity MET values were derived from energy cost data measured in youth; the remaining activities were estimated from adult values. Purpose—To determine the energy cost of common activities performed by children and adolescents and compare these data to similar activities reported in the compendium. Methods—Thirty-two children (8–11 years old) and 28 adolescents (12–16 years) completed 4 locomotion activities on a treadmill (TRD) and 5 age-specific activities of daily living (ADL). Oxygen consumption was measured using ...


Assessment Of Physical Activity Using Wearable Monitors: Recommendations For Monitor Calibration And Use In The Field, Patty S. Freedson, Heather R. Bowles, Richard Troiano, William Haskell Dec 2011

Assessment Of Physical Activity Using Wearable Monitors: Recommendations For Monitor Calibration And Use In The Field, Patty S. Freedson, Heather R. Bowles, Richard Troiano, William Haskell

Patty S. Freedson

This paper provides recommendations for the use of wearable monitors for assessing physical activity. We have provided recommendations for measurement researchers, end users, and developers of activity monitors. We discuss new horizons and future directions in the field of objective measurement of physical activity and present challenges that remain for the future. These recommendations are based on the proceedings from the workshop, “Objective Measurement of Physical Activity: Best Practices & Future Direction,” July 20-21, 2009, and also on data and information presented since the workshop.


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 Nov 2011

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 ...


A Comprehensive Evaluation Of Commonly Used Accelerometer Energy Expenditure And Met Prediction Equations, Kate Lyden, Sarah L. Kozey, John W. Staudenmayer, Patty S. Freedson Jan 2011

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 ...


A Comprehensive Evaluation Of Commonly Used Accelerometer Energy Expenditure And Met Prediction Equations, Kate Lyden, Sarah L. Kozey, John W. Staudenmayer, Patty S. Freedson Jan 2011

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 ...


An Artificial Neural Network To Estimate Physical Activity Energy Expenditure And Identify Physical Activity Type From An Accelerometer, John Staudenmayer, David Pober, Scott Crouter, David Bassett, Patty S. Freedson Sep 2009

An Artificial Neural Network To Estimate Physical Activity Energy Expenditure And Identify Physical Activity Type From An Accelerometer, John Staudenmayer, David Pober, Scott Crouter, David Bassett, Patty S. Freedson

Patty S. Freedson

The aim of this investigation was to develop and test two artificial neural networks (ANN) to apply to physical activity data collected with a commonly used uniaxial accelerometer. The first ANN model estimated physical activity metabolic equivalents (METs), and the second ANN identified activity type. Subjects (n = 24 men and 24 women, mean age = 35 yr) completed a menu of activities that included sedentary, light, moderate, and vigorous intensities, and each activity was performed for 10 min. There were three different activity menus, and 20 participants completed each menu. Oxygen consumption (in ml•kg •min ) was measured continuously, and the ...