Accelerometer Data Collection and Processing Criteria to Assess Physical Activity and Other Outcomes: A Systematic Review and Practical Considerations

BackgroundAccelerometers are widely used to measure sedentary time, physical activity, physical activity energy expenditure (PAEE), and sleep-related behaviors, with the ActiGraph being the most frequently used brand by researchers. However, data collection and processing criteria have evolved in a myriad of ways out of the need to answer unique research questions; as a result there is no consensus.ObjectivesThe purpose of this review was to: (1) compile and classify existing studies assessing sedentary time, physical activity, energy expenditure, or sleep using the ActiGraph GT3X/+ through data collection and processing criteria to improve data comparability and (2) review data collection and processing criteria when using GT3X/+ and provide age-specific practical considerations based on the validation/calibration studies identified.MethodsTwo independent researchers conducted the search in PubMed and Web of Science. We included all original studies in which the GT3X/+ was used in laboratory, controlled, or free-living conditions published from 1 January 2010 to the 31 December 2015.ResultsThe present systematic review provides key information about the following data collection and processing criteria: placement, sampling frequency, filter, epoch length, non-wear-time, what constitutes a valid day and a valid week, cut-points for sedentary time and physical activity intensity classification, and algorithms to estimate PAEE and sleep-related behaviors. The information is organized by age group, since criteria are usually age-specific.ConclusionThis review will help researchers and practitioners to make better decisions before (i.e., device placement and sampling frequency) and after (i.e., data processing criteria) data collection using the GT3X/+ accelerometer, in order to obtain more valid and comparable data.PROSPERO registration numberCRD42016039991.

[1]  Lars Bo Andersen,et al.  Mechanical and free living comparisons of four generations of the Actigraph activity monitor , 2012, International Journal of Behavioral Nutrition and Physical Activity.

[2]  J. Sallis,et al.  Using accelerometers in youth physical activity studies: a review of methods. , 2013, Journal of physical activity & health.

[3]  J. Sallis Self-report measures of children's physical activity. , 1991, The Journal of school health.

[4]  Edward M. Winter,et al.  JUMPING: POWER OR IMPULSE? , 2005 .

[5]  Stewart G Trost,et al.  Conducting accelerometer-based activity assessments in field-based research. , 2005, Medicine and science in sports and exercise.

[6]  Matthew P Buman,et al.  Twenty-four Hours of Sleep, Sedentary Behavior, and Physical Activity with Nine Wearable Devices. , 2016, Medicine and science in sports and exercise.

[7]  Greet Cardon,et al.  Feasibility and validity of accelerometer measurements to assess physical activity in toddlers , 2011, The international journal of behavioral nutrition and physical activity.

[8]  Maciej S Buchowski,et al.  Validation of the ActiGraph two-regression model for predicting energy expenditure. , 2010, Medicine and science in sports and exercise.

[9]  F. Gottrand,et al.  New validated thresholds for various intensities of physical activity in adolescents using the Actigraph accelerometer , 2011, International journal of rehabilitation research. Internationale Zeitschrift fur Rehabilitationsforschung. Revue internationale de recherches de readaptation.

[10]  Roland Seiler,et al.  Development and validation of GT3X accelerometer cut-off points in 5- to 9-year-old children based on indirect calorimetry measurements , 2013 .

[11]  Dinesh John,et al.  Validation and comparison of ActiGraph activity monitors. , 2011, Journal of science and medicine in sport.

[12]  Leonard A Kaminsky,et al.  Intermonitor reliability of the GT3X+ accelerometer at hip, wrist and ankle sites during activities of daily living , 2014, Physiological measurement.

[13]  Kenneth A Loparo,et al.  Performance evaluation of an automated single-channel sleep–wake detection algorithm , 2014, Nature and science of sleep.

[14]  Ulf Ekelund,et al.  Assessment of physical activity – a review of methodologies with reference to epidemiological research: a report of the exercise physiology section of the European Association of Cardiovascular Prevention and Rehabilitation , 2010, European journal of cardiovascular prevention and rehabilitation : official journal of the European Society of Cardiology, Working Groups on Epidemiology & Prevention and Cardiac Rehabilitation and Exercise Physiology.

[15]  Ulf Ekelund,et al.  Age group comparability of raw accelerometer output from wrist- and hip-worn monitors. , 2014, Medicine and science in sports and exercise.

[16]  Roger G. Eston,et al.  Children's physical activity assessed with wrist- and hip-worn accelerometers. , 2014, Medicine and science in sports and exercise.

[17]  Vincent Onywera,et al.  Improving wear time compliance with a 24-hour waist-worn accelerometer protocol in the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE) , 2015, International Journal of Behavioral Nutrition and Physical Activity.

[18]  S. Grant,et al.  An objective method for measurement of sedentary behavior in 3- to 4-year olds. , 2003, Obesity research.

[19]  Margarita Treuth,et al.  Predicting energy expenditure from accelerometry counts in adolescent girls. , 2005, Medicine and science in sports and exercise.

[20]  U. Ekelund,et al.  Physical activity and clustered cardiovascular risk in children: a cross-sectional study (The European Youth Heart Study) , 2006, The Lancet.

[21]  P. D. Watson,et al.  Validity of the computer science and applications (CSA) activity monitor in children. , 1998, Medicine and science in sports and exercise.

[22]  D. Nemet,et al.  Health-related knowledge and preferences in low socio-economic kindergarteners , 2012, International Journal of Behavioral Nutrition and Physical Activity.

[23]  D. J. Mullaney,et al.  Automatic sleep/wake identification from wrist activity. , 1992, Sleep.

[24]  D. Moher,et al.  The nuts and bolts of PROSPERO: an international prospective register of systematic reviews , 2012, Systematic Reviews.

[25]  Wendy J Brown,et al.  Is the pain of activity log-books worth the gain in precision when distinguishing wear and non-wear time for tri-axial accelerometers? , 2013, Journal of science and medicine in sport.

[26]  T Paillard,et al.  Do epoch lengths affect adolescents' compliance with physical activity guidelines? , 2014, The Journal of sports medicine and physical fitness.

[27]  G. Cavagna,et al.  The determinants of the step frequency in walking in humans. , 1986, The Journal of physiology.

[28]  Catrine Tudor-Locke,et al.  Comparison of step outputs for waist and wrist accelerometer attachment sites. , 2015, Medicine and science in sports and exercise.

[29]  Knut-Inge Klepp,et al.  Correlates of weight status among Norwegian 11-year-olds: The HEIA study , 2012, BMC Public Health.

[30]  Jennifer H. Walsh,et al.  Assessing sleep using hip and wrist actigraphy , 2015 .

[31]  D. Moher,et al.  Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement , 2009, BMJ.

[32]  Kate Ridley,et al.  Agreement between activPAL and ActiGraph for assessing children's sedentary time , 2012, International Journal of Behavioral Nutrition and Physical Activity.

[33]  Eivind Aadland,et al.  Reliability of the Actigraph GT3X+ Accelerometer in Adults under Free-Living Conditions , 2015, PloS one.

[34]  S. Going,et al.  Defining accelerometer thresholds for activity intensities in adolescent girls. , 2004, Medicine and science in sports and exercise.

[35]  R. Mcmurray,et al.  Calibration of two objective measures of physical activity for children , 2008, Journal of sports sciences.

[36]  Tom Baranowski,et al.  Reliability and Validity of Self Report of Aerobic Activity: Family Health Project , 1984 .

[37]  Robert Williams,et al.  Fully proportional actigraphy: A new instrument , 1996 .

[38]  Leena Choi,et al.  Assessment of wear/nonwear time classification algorithms for triaxial accelerometer. , 2012, Medicine and science in sports and exercise.

[39]  P S Freedson,et al.  Calibration of the Computer Science and Applications, Inc. accelerometer. , 1998, Medicine and science in sports and exercise.

[40]  Maurice R Puyau,et al.  Cross-sectional time series and multivariate adaptive regression splines models using accelerometry and heart rate predict energy expenditure of preschoolers. , 2013, The Journal of nutrition.

[41]  Scott E Crouter,et al.  Estimating physical activity in youth using a wrist accelerometer. , 2015, Medicine and science in sports and exercise.

[42]  Nicole Probst-Hensch,et al.  Effects of filter choice in GT3X accelerometer assessments of free-living activity. , 2013, Medicine and science in sports and exercise.

[43]  Gert R. G. Lanckriet,et al.  A random forest classifier for the prediction of energy expenditure and type of physical activity from wrist and hip accelerometers , 2014, Physiological measurement.

[44]  SHAOPENG LIU,et al.  Computational methods for estimating energy expenditure in human physical activities. , 2012, Medicine and science in sports and exercise.

[45]  Sun Ha Jee,et al.  Population-Attributable Causes of Cancer in Korea: Obesity and Physical Inactivity , 2014, PloS one.

[46]  Catrine Tudor-Locke,et al.  Fully automated waist-worn accelerometer algorithm for detecting children's sleep-period time separate from 24-h physical activity or sedentary behaviors. , 2014, Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme.

[47]  Leena Choi,et al.  Validation of accelerometer wear and nonwear time classification algorithm. , 2011, Medicine and science in sports and exercise.

[48]  A. Sadeh,et al.  Activity-based sleep-wake identification: an empirical test of methodological issues. , 1994, Sleep.

[49]  D. Warburton,et al.  Health benefits of physical activity: the evidence , 2006, Canadian Medical Association Journal.

[50]  J. Staudenmayer,et al.  Methods to estimate aspects of physical activity and sedentary behavior from high-frequency wrist accelerometer measurements. , 2015, Journal of applied physiology.

[51]  Patty Freedson,et al.  Calibration of accelerometer output for children. , 2005, Medicine and science in sports and exercise.

[52]  J. Staudenmayer,et al.  Validity of two wearable monitors to estimate breaks from sedentary time. , 2012, Medicine and science in sports and exercise.

[53]  Jie Zhuang,et al.  Predicting Chinese Children and Youth's Energy Expenditure Using ActiGraph Accelerometers: A Calibration and Cross-Validation Study , 2013, Research quarterly for exercise and sport.

[54]  Kelly R Evenson,et al.  Patterns of objectively measured physical activity in the United States. , 2008, Medicine and science in sports and exercise.

[55]  Thomas Penzel,et al.  Agreement of different methods for assessing sleep characteristics: a comparison of two actigraphs, wrist and hip placement, and self-report with polysomnography. , 2014, Sleep medicine.

[56]  Scott Duncan,et al.  Accelerometer data reduction in adolescents: effects on sample retention and bias , 2013, International Journal of Behavioral Nutrition and Physical Activity.

[57]  S. Blair,et al.  Calibration of an accelerometer during free-living activities in children. , 2007, International journal of pediatric obesity : IJPO : an official journal of the International Association for the Study of Obesity.

[58]  A. Rowlands,et al.  Validation of the GT3X ActiGraph in children and comparison with the GT1M ActiGraph. , 2013, Journal of science and medicine in sport.

[59]  I. Piña,et al.  Statement on exercise. Benefits and recommendations for physical activity programs for all Americans. A statement for health professionals by the Committee on Exercise and Cardiac Rehabilitation of the Council on Clinical Cardiology, American Heart association. , 1992, Circulation.

[60]  I-Min Lee,et al.  Impact of accelerometer data processing decisions on the sample size, wear time and physical activity level of a large cohort study , 2014, BMC Public Health.

[61]  L. Mâsse,et al.  Physical activity in the United States measured by accelerometer. , 2008, Medicine and science in sports and exercise.

[62]  Catrine Tudor-Locke,et al.  Comparison of older adults' Steps per day using an NL-1000 pedometer and two GT3X+ accelerometer Filters , 2013 .

[63]  Matthew P. Buman,et al.  Direct comparison of two actigraphy devices with polysomnographically recorded naps in healthy young adults , 2013, Chronobiology international.

[64]  Eivind Aadland,et al.  Reliability of Objectively Measured Sedentary Time and Physical Activity in Adults , 2015, PloS one.

[65]  D. Bassett,et al.  Use of a two-regression model for estimating energy expenditure in children. , 2011, Medicine and science in sports and exercise.

[66]  G. Cardon,et al.  Actigraph GT3X: Validation and Determination of Physical Activity Intensity Cut Points , 2013, International Journal of Sports Medicine.

[67]  Michael W. Beets,et al.  Classification of physical activity intensities using a wrist‐worn accelerometer in 8–12‐year‐old children , 2016, Pediatric obesity.

[68]  Catrine Tudor-Locke,et al.  Comparison of older adults' steps per day using NL-1000 pedometer and two GT3X+ accelerometer filters. , 2013, Journal of aging and physical activity.

[69]  S. Clemes,et al.  Calibration and validation of the ActiGraph GT3X+ in 2-3 year olds. , 2014, Journal of science and medicine in sport.

[70]  Maurice R Puyau,et al.  A longitudinal study of fitness and activity in girls predisposed to obesity. , 2004, Medicine and science in sports and exercise.

[71]  Wendy J Brown,et al.  ActiGraph GT3X+ cut-points for identifying sedentary behaviour in older adults in free-living environments. , 2014, Journal of science and medicine in sport.

[72]  Michael J Stec,et al.  Estimation of Resistance Exercise Energy Expenditure Using Triaxial Accelerometry , 2012, Journal of strength and conditioning research.

[73]  Kenneth R Fox,et al.  Physical activity patterns assessed by accelerometry in older people , 2007, European Journal of Applied Physiology.

[74]  Elin Kolle,et al.  Comparison of three generations of ActiGraph activity monitors under free-living conditions: do they provide comparable assessments of overall physical activity in 9-year old children? , 2014, BMC Sports Science, Medicine and Rehabilitation.

[75]  Dinesh John,et al.  Comment on "estimating activity and sedentary behavior from an accelerometer on the hip and wrist". , 2013, Medicine and science in sports and exercise.

[76]  Jie Zhuang,et al.  Intensity Classification Accuracy of Accelerometer-Measured Physical Activities in Chinese Children and Youth , 2013, Research quarterly for exercise and sport.

[77]  Bernard F Fuemmeler,et al.  Accelerometer data reduction: a comparison of four reduction algorithms on select outcome variables. , 2005, Medicine and science in sports and exercise.

[78]  R. Pate,et al.  Physical Activity Assessment in Children and Adolescents , 2001, Sports medicine.

[79]  Dale W Esliger,et al.  Accelerometer assessment of physical activity in active, healthy older adults. , 2009, Journal of aging and physical activity.

[80]  J. Staudenmayer,et al.  Validation of wearable monitors for assessing sedentary behavior. , 2011, Medicine and science in sports and exercise.

[81]  Maurice R. Puyau,et al.  Prediction of energy expenditure and physical activity in preschoolers. , 2014, Medicine and science in sports and exercise.

[82]  U. Ekelund,et al.  Calibration and cross‐validation of a wrist‐worn Actigraph in young preschoolers , 2015, Pediatric obesity.

[83]  T. Vasankari,et al.  A universal, accurate intensity‐based classification of different physical activities using raw data of accelerometer , 2015, Clinical physiology and functional imaging.

[84]  Greet Cardon,et al.  Calibration and comparison of accelerometer cut points in preschool children. , 2011, International journal of pediatric obesity : IJPO : an official journal of the International Association for the Study of Obesity.

[85]  Scott E Crouter,et al.  Refined two-regression model for the ActiGraph accelerometer. , 2010, Medicine and science in sports and exercise.

[86]  James F Sallis,et al.  Comparison of older and newer generations of ActiGraph accelerometers with the normal filter and the low frequency extension , 2013, International Journal of Behavioral Nutrition and Physical Activity.

[87]  Daniel Arvidsson,et al.  Sampling frequency affects the processing of Actigraph raw acceleration data to activity counts. , 2016, Journal of applied physiology.

[88]  PATTY S. FREEDSON,et al.  Utilization and Harmonization of Adult Accelerometry Data: Review and Expert Consensus , 2015, Medicine and science in sports and exercise.

[89]  Dinesh John,et al.  Biomechanical examination of the ‘plateau phenomenon’ in ActiGraph vertical activity counts , 2012, Physiological measurement.

[90]  Takemi Sugiyama,et al.  Perceived neighbourhood environmental attributes and prospective changes in TV viewing time among older Australian adults , 2015, International Journal of Behavioral Nutrition and Physical Activity.

[91]  Gregory J. Welk,et al.  Examination of Different Accelerometer Cut-Points for Assessing Sedentary Behaviors in Children , 2014, PloS one.

[92]  S. Trost,et al.  Calibration and Evaluation of an Objective Measure of Physical Activity in Preschool Children , 2005 .

[93]  Virginie Nicaise,et al.  Convergent Validity of Four Accelerometer Cutpoints With Direct Observation of Preschool Children's Outdoor Physical Activity , 2013, Research quarterly for exercise and sport.

[94]  D. Moher,et al.  Reprint--preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. , 2009, Physical therapy.

[95]  M. Puyau,et al.  Validation and calibration of physical activity monitors in children. , 2002, Obesity research.

[96]  Gert R. G. Lanckriet,et al.  Hip and Wrist Accelerometer Algorithms for Free-Living Behavior Classification. , 2016, Medicine and science in sports and exercise.

[97]  Charles E Matthew,et al.  Calibration of accelerometer output for adults. , 2005, Medicine and science in sports and exercise.

[98]  Nancy W Glynn,et al.  Use of accelerometry to measure physical activity in older adults at risk for mobility disability. , 2008, Journal of aging and physical activity.

[99]  Øyvind Salvesen,et al.  New relative intensity ambulatory accelerometer thresholds for elderly men and women: the Generation 100 study , 2015, BMC Geriatrics.

[100]  James Dunbar,et al.  Waste the waist: a pilot randomised controlled trial of a primary care based intervention to support lifestyle change in people with high cardiovascular risk , 2015, International Journal of Behavioral Nutrition and Physical Activity.

[101]  Leonard A Kaminsky,et al.  Variability of Objectively Measured Sedentary Behavior. , 2016, Medicine and science in sports and exercise.

[102]  Stewart G Trost,et al.  Comparison of three generations of ActiGraph™ activity monitors in children and adolescents , 2012, Journal of sports sciences.

[103]  Harri Sievänen,et al.  Mean amplitude deviation calculated from raw acceleration data: a novel method for classifying the intensity of adolescents’ physical activity irrespective of accelerometer brand , 2015, BMC Sports Science, Medicine and Rehabilitation.

[104]  Marcelo Romanzini,et al.  Calibration of ActiGraph GT3X, Actical and RT3 accelerometers in adolescents , 2014, European journal of sport science.

[105]  Vincent Onywera,et al.  The International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE): design and methods , 2013, BMC Public Health.

[106]  P. Freedson,et al.  Amount of time spent in sedentary behaviors in the United States, 2003-2004. , 2008, American journal of epidemiology.

[107]  Ulf Ekelund,et al.  Predictive Validity and Classification Accuracy of ActiGraph Energy Expenditure Equations and Cut-Points in Young Children , 2013, PloS one.

[108]  David R Bassett,et al.  Calibration and validation of wearable monitors. , 2012, Medicine and science in sports and exercise.

[109]  Alex V Rowlands,et al.  Wear Compliance and Activity in Children Wearing Wrist- and Hip-Mounted Accelerometers. , 2016, Medicine and science in sports and exercise.

[110]  Inge Tetens,et al.  Measure of sleep and physical activity by a single accelerometer: Can a waist-worn Actigraph adequately measure sleep in children? , 2012 .

[111]  D. Bassett,et al.  Estimating energy expenditure using accelerometers , 2006, European Journal of Applied Physiology.

[112]  I. Janssen,et al.  Systematic review of the health benefits of physical activity and fitness in school-aged children and youth , 2010, The international journal of behavioral nutrition and physical activity.

[113]  K. Maleta,et al.  Feasibility and validity of the ActiGraph GT3X accelerometer in measuring physical activity of Malawian toddlers , 2013, Acta paediatrica.

[114]  C. Tudor-Locke,et al.  Identifying children's nocturnal sleep using 24-h waist accelerometry. , 2015, Medicine and science in sports and exercise.

[115]  Gavin Kennedy,et al.  24 h Accelerometry: impact of sleep-screening methods on estimates of sedentary behaviour and physical activity while awake , 2016, Journal of sports sciences.

[116]  J. Sirard,et al.  Validation of Accelerometer Thresholds and Inclinometry for Measurement of Sedentary Behavior in Young Adult University Students. , 2015, Research in nursing & health.

[117]  G. Cavagna,et al.  The two power limits conditioning step frequency in human running. , 1991, The Journal of physiology.

[118]  Russell R. Pate,et al.  Validation and Calibration of an Accelerometer in Preschool Children , 2006, Obesity.