Literature DB >> 21088628

Validation of the GENEA Accelerometer.

Dale W Esliger1, Ann V Rowlands, Tina L Hurst, Michael Catt, Peter Murray, Roger G Eston.   

Abstract

PURPOSE: The study aims were: 1) to assess the technical reliability and validity of the GENEA using a mechanical shaker; 2) to perform a GENEA value calibration to develop thresholds for sedentary and light-, moderate-, and vigorous-intensity physical activity; and 3) to compare the intensity classification of the GENEA with two widely used accelerometers.
METHODS: A total of 47 GENEA accelerometers were attached to a shaker and vertically accelerated, generating 15 conditions of varying acceleration and/or frequency. Reliability was calculated using SD and intrainstrument and interinstrument coefficients of variation, whereas validity was assessed using Pearson correlation with the shaker acceleration as the criterion. Next, 60 adults wore a GENEA on each wrist and on the waist (alongside an ActiGraph and RT3 accelerometer) while completing 10-12 activity tasks. A portable metabolic gas analyzer provided the criterion measure of physical activity. Analyses involved the use of Pearson correlations to establish criterion and concurrent validity and receiver operating characteristic curves to establish intensity cut points.
RESULTS: The GENEA demonstrated excellent technical reliability (CVintra = 1.4%, CVinter = 2.1%) and validity (r = 0.98, P < 0.001) using the mechanical shaker. The GENEA demonstrated excellent criterion validity using VO2 as the criterion (left wrist, r = 0.86; right wrist, r = 0.83; waist, r = 0.87), on par with the waist-worn ActiGraph and RT3. The GENEA demonstrated excellent concurrent validity compared with the ActiGraph (r = 0.92) and the RT3 (r = 0.97). The waist-worn GENEA had the greatest classification accuracy (area under the receiver operating characteristic curve (AUC) = 0.95), followed by the left (AUC = 0.93) and then the right wrist (AUC = 0.90). The accuracy of the waist-worn GENEA was virtually identical with that of the ActiGraph (AUC = 0.94) and RT3 (AUC = 0.95).
CONCLUSION: The GENEA is a reliable and valid measurement tool capable of classifying the intensity of physical activity in adults.

Entities:  

Mesh:

Year:  2011        PMID: 21088628     DOI: 10.1249/MSS.0b013e31820513be

Source DB:  PubMed          Journal:  Med Sci Sports Exerc        ISSN: 0195-9131            Impact factor:   5.411


  179 in total

1.  Establishing and evaluating wrist cutpoints for the GENEActiv accelerometer in youth.

Authors:  Christine A Schaefer; Claudio R Nigg; James O Hill; Lois A Brink; Raymond C Browning
Journal:  Med Sci Sports Exerc       Date:  2014-04       Impact factor: 5.411

2.  Self-affirmation alters the brain's response to health messages and subsequent behavior change.

Authors:  Emily B Falk; Matthew Brook O'Donnell; Christopher N Cascio; Francis Tinney; Yoona Kang; Matthew D Lieberman; Shelley E Taylor; Lawrence An; Kenneth Resnicow; Victor J Strecher
Journal:  Proc Natl Acad Sci U S A       Date:  2015-02-02       Impact factor: 11.205

3.  Accelerometry as an objective measure of upper-extremity activity.

Authors:  Samuel Larrivée; Emma Avery; Jeff Leiter; Jason Old
Journal:  Med Biol Eng Comput       Date:  2021-01-07       Impact factor: 2.602

4.  Associations among masticatory muscle activity, physical activity and self-reported oral behaviours in adult women.

Authors:  Sabarinath Prasad; Divya Ramanan; Hamza Bennani; Michael Paulin; Richard D Cannon; Sandro Palla; Mauro Farella
Journal:  Clin Oral Investig       Date:  2021-02-06       Impact factor: 3.573

Review 5.  The 24-Hour Activity Cycle: A New Paradigm for Physical Activity.

Authors:  Mary E Rosenberger; Janet E Fulton; Matthew P Buman; Richard P Troiano; Michael A Grandner; David M Buchner; William L Haskell
Journal:  Med Sci Sports Exerc       Date:  2019-03       Impact factor: 5.411

6.  Sleep estimates using microelectromechanical systems (MEMS).

Authors:  Bart H W te Lindert; Eus J W Van Someren
Journal:  Sleep       Date:  2013-05-01       Impact factor: 5.849

7.  Association Between Objectively Measured Physical Activity and Plasma BDNF in Adolescents: DADOS Study.

Authors:  M R Beltran-Valls; M Adelantado-Renau; D Moliner-Urdiales
Journal:  J Mol Neurosci       Date:  2018-07-23       Impact factor: 3.444

8.  Athletes for life: Rationale and methodology of a community- and family-based randomized controlled trial to promote cardiovascular fitness among primarily Latino families.

Authors:  Jacob Szeszulski; Sonia Vega-López; Michael Todd; Frank Ray; Alma Behar; Maria Campbell; Adrian Chavez; Ryan Eckert; Anabell Lorenzo-Quintero; Leopoldo Hartmann Manrique; Noe C Crespo
Journal:  Contemp Clin Trials       Date:  2020-02-13       Impact factor: 2.226

9.  Classification accuracy of the wrist-worn gravity estimator of normal everyday activity accelerometer.

Authors:  Whitney A Welch; David R Bassett; Dixie L Thompson; Patty S Freedson; John W Staudenmayer; Dinesh John; Jeremy A Steeves; Scott A Conger; Tyrone Ceaser; Cheryl A Howe; Jeffer E Sasaki; Eugene C Fitzhugh
Journal:  Med Sci Sports Exerc       Date:  2013-10       Impact factor: 5.411

10.  Estimating activity and sedentary behavior from an accelerometer on the hip or wrist.

Authors:  Mary E Rosenberger; William L Haskell; Fahd Albinali; Selene Mota; Jason Nawyn; Stephen Intille
Journal:  Med Sci Sports Exerc       Date:  2013-05       Impact factor: 5.411

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