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Articles 1 - 15 of 15
Full-Text Articles in Kinesiology
Impact Of Accelerometer Data Processing Decisions On The Sample Size, Wear Time And Physical Activity Level Of A Large Cohort Study, Sarah Kozey Keadle, Eric Shiroma, Patty Freedson, I-Min Lee
Impact Of Accelerometer Data Processing Decisions On The Sample Size, Wear Time And Physical Activity Level Of A Large Cohort Study, Sarah Kozey Keadle, Eric Shiroma, Patty Freedson, I-Min Lee
Patty S. Freedson
Background Accelerometers objectively assess physical activity (PA) and are currently used in several large-scale epidemiological studies, but there is no consensus for processing the data. This study compared the impact of wear-time assessment methods and using either vertical (V)-axis or vector magnitude (VM) cut-points on accelerometer output. Methods Participants (7,650 women, mean age 71.4 y) were mailed an accelerometer (ActiGraph GT3X+), instructed to wear it for 7 days, record dates and times the monitor was worn on a log, and return the monitor and log via mail. Data were processed using three wear-time methods (logs, Troiano or Choi algorithms) and …
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
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 (i.e., home, community, work/school), purpose …
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
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 measurement error modeling and traditional …
Simple To Complex Modeling Of Breathing Volume Using A Motion Sensor, Dinesh John, John Staudenmayer, Patty Freedson
Simple To Complex Modeling Of Breathing Volume Using A Motion Sensor, Dinesh John, John Staudenmayer, Patty Freedson
Patty S. Freedson
Purpose—To compare simple and complex modeling techniques to estimate categories of low, medium, and high ventilation (VE) from ActiGraph™ activity counts. Methods—Vertical axis ActiGraph™ GT1M activity counts, oxygen consumption and VE were measured during treadmill walking and running, sports, household chores and labor-intensive employment activities. Categories of low (<19.3 l/min), medium (19.3 to 35.4 l/min) and high (>35.4 l/min) VEs were derived from activity intensity classifications (light <2.9 METs, moderate 3.0 to 5.9 METs and vigorous >6.0 METs). We examined the accuracy of two simple techniques (multiple regression and activity count cut-point analyses) and one complex (random forest technique) modeling technique in predicting VE from activity counts. Results—Prediction accuracy of the complex random forest technique was marginally …
Tissue Artifact Removal From Respiratory Signals Based On Empirical Mode Decomposition, Shaopeng Liu, Robert X. Gao, Dinesh John, John Staudenmayer, Patty S. Freedson
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 …
Sustained And Shorter Bouts Of Physical Activity Are Related To Cardiovascular Health, Nicole Glazer, Asya Lyass, Dale Esliger, Susan Blease, Patty Freedson, Joseph Massaro, Joanne Murabito, Ramachandran Vasan
Sustained And Shorter Bouts Of Physical Activity Are Related To Cardiovascular Health, Nicole Glazer, Asya Lyass, Dale Esliger, Susan Blease, Patty Freedson, Joseph Massaro, Joanne Murabito, Ramachandran Vasan
Patty S. Freedson
Purpose—Whereas greater physical activity (PA) is known to prevent cardiovascular disease (CVD), the relative importance of performing PA in sustained bouts of activity versus shorter bouts of activity on CVD risk is not known. The objective of this study was to investigate the relationship between moderate-to-vigorous physical activity (MVPA), measured in bouts ≥10 minutes and <10 minutes, and CVD risk factors in a well-characterized, community-based sample of white adults. Methods—We conducted a cross-sectional analysis of 2109 Framingham Heart Study Third Generation participants (mean age 47 years, 55% women) who underwent objective assessment of PA by accelerometry over 57 days. Total MVPA, MVPA done in bouts ≥10 minutes (MVPA10+), and MVPA done in bouts <10 minutes (MVPA<10) were calculated. MVPA exposures were related to individual CVD risk factors, including measures of adiposity and blood lipid and glucose levels, using linear and logistic regression. Results—Total MVPA was significantly associated with higher high-density lipoprotein (HDL) levels, and with lower triglycerides, BMI, waist circumference and Framingham risk score (P<0.0001). MVPA<10 showed similar statistically significant associations with these CVD risk factors (P <0.001). Compliance with national guidelines (≥150 minutes of total MVPA) was significantly related to lower BMI, triglycerides, Framingham risk score, waist circumference, higher HDL, and a lower prevalence of obesity and impaired fasting glucose (P < 0.001 for all). Conclusions—Our cross-sectional observations on a large middle-aged community-based sample confirm a positive association of MVPA with a healthier CVD risk factor profile, and indicate that accruing physical activity in bouts <10 minutes may favorably influence cardiometabolic risk. Additional investigations are warranted to confirm our findings.
Energy Cost Of Common Activities In Children And Adolescents, Kate Lyden, Sarah Kozey Keadle, John Staudenmayer, Patty S. Freedson, Sofiya Alhassan
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 a portable metabolic analyzer. Results—In …
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
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
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 …
Calibrating A Novel Multi-Sensor Physical Activity Measurement System, D. John, S. Liu, J. Saski, C. Howe, J. Staudenmayer, R. Gao, Patty Freedson
Calibrating A Novel Multi-Sensor Physical Activity Measurement System, D. John, S. Liu, J. Saski, C. Howe, J. Staudenmayer, R. Gao, Patty Freedson
Patty S. Freedson
Advancing the field of physical activity (PA) monitoring requires the development of innovative multi-sensor measurement systems that are feasible in the free-living environment. The use of novel analytical techniques to combine and process these multiple sensor signals is equally important. This paper, describes a novel multi-sensor ‘Integrated PA Measurement System’ (IMS), the lab-based methodology used to calibrate the IMS, techniques used to predict multiple variables from the sensor signals, and proposes design changes to improve the feasibility of deploying the IMS in the free-living environment. The IMS consists of hip and wrist acceleration sensors, two piezoelectric respiration sensors on the …
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 …
A Comparison Of The Actigraph 7164 And The Actigraph Gt1m During Self-Paced Locomotion, Sarah Kozey, John Staudenmayer, Richard Troiano, Patty Freedson
A Comparison Of The Actigraph 7164 And The Actigraph Gt1m During Self-Paced Locomotion, Sarah Kozey, John Staudenmayer, Richard Troiano, Patty Freedson
Patty S. Freedson
Purpose—This study compared the ActiGraph accelerometer model 7164 (AM1) to the ActiGraph GT1M (AM2) during self-paced locomotion. Methods—Participants n = 116, 18–73y, mean BMI = 26.1) walked at self-selected slow, medium, and fast speeds around an indoor circular hallway (0.47km). Both activity monitors were attached to a belt secured to the hip and simultaneously collected data in 60 second epochs. To compare differences between monitors, the average difference (bias) in count output and steps output were computed at each speed. Time spent in different activity intensities (light, moderate, vigorous) based on the Freedson et al. cut-points was compared for each …
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
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, …
Amount Of Time Spent In Sedentary Behaviors In The United States, 2003–2004, Charles Matthews, Kong Chen, Patty Freedson, Maciej Buchowski, Bettina Beech, Russell Pate, Richard Troiano
Amount Of Time Spent In Sedentary Behaviors In The United States, 2003–2004, Charles Matthews, Kong Chen, Patty Freedson, Maciej Buchowski, Bettina Beech, Russell Pate, Richard Troiano
Patty S. Freedson
Sedentary behaviors are linked to adverse health outcomes, but the total amount of time spent in these behaviors in the United States has not been objectively quantified. The authors evaluated participants from the 2003–2004 National Health and Nutrition Examination Survey aged ≥6 years who wore an activity monitor for up to 7 days. Among 6,329 participants with at least one 10-hour day of monitor wear, the average monitor-wearing time was 13.9 hours/day (standard deviation, 1.9). Overall, participants spent 54.9% of their monitored time, or 7.7 hours/day, in sedentary behaviors. The most sedentary groups in the United States were older adolescents …