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Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

524 related items for PubMed ID: 21988935

  • 1. Physical activity classification using the GENEA wrist-worn accelerometer.
    Zhang S, Rowlands AV, Murray P, Hurst TL.
    Med Sci Sports Exerc; 2012 Apr; 44(4):742-8. PubMed ID: 21988935
    [Abstract] [Full Text] [Related]

  • 2. Accelerometer counts and raw acceleration output in relation to mechanical loading.
    Rowlands AV, Stiles VH.
    J Biomech; 2012 Feb 02; 45(3):448-54. PubMed ID: 22218284
    [Abstract] [Full Text] [Related]

  • 3. Validation of the GENEA Accelerometer.
    Esliger DW, Rowlands AV, Hurst TL, Catt M, Murray P, Eston RG.
    Med Sci Sports Exerc; 2011 Jun 02; 43(6):1085-93. PubMed ID: 21088628
    [Abstract] [Full Text] [Related]

  • 4. Classification accuracy of the wrist-worn gravity estimator of normal everyday activity accelerometer.
    Welch WA, Bassett DR, Thompson DL, Freedson PS, Staudenmayer JW, John D, Steeves JA, Conger SA, Ceaser T, Howe CA, Sasaki JE, Fitzhugh EC.
    Med Sci Sports Exerc; 2013 Oct 02; 45(10):2012-9. PubMed ID: 23584403
    [Abstract] [Full Text] [Related]

  • 5. A novel approach to measuring activity in chronic obstructive pulmonary disease: using 2 activity monitors to classify daily activity.
    Cohen MD, Cutaia M.
    J Cardiopulm Rehabil Prev; 2010 Oct 02; 30(3):186-94. PubMed ID: 20216326
    [Abstract] [Full Text] [Related]

  • 6. Activity classification using the GENEA: optimum sampling frequency and number of axes.
    Zhang S, Murray P, Zillmer R, Eston RG, Catt M, Rowlands AV.
    Med Sci Sports Exerc; 2012 Nov 02; 44(11):2228-34. PubMed ID: 22617400
    [Abstract] [Full Text] [Related]

  • 7. Field evaluation of a random forest activity classifier for wrist-worn accelerometer data.
    Pavey TG, Gilson ND, Gomersall SR, Clark B, Trost SG.
    J Sci Med Sport; 2017 Jan 02; 20(1):75-80. PubMed ID: 27372275
    [Abstract] [Full Text] [Related]

  • 8. Calibration of the GENEA accelerometer for assessment of physical activity intensity in children.
    Phillips LR, Parfitt G, Rowlands AV.
    J Sci Med Sport; 2013 Mar 02; 16(2):124-8. PubMed ID: 22770768
    [Abstract] [Full Text] [Related]

  • 9. Cross-validation of waist-worn GENEA accelerometer cut-points.
    Welch WA, Bassett DR, Freedson PS, John D, Steeves JA, Conger SA, Ceaser TG, Howe CA, Sasaki JE.
    Med Sci Sports Exerc; 2014 Sep 02; 46(9):1825-30. PubMed ID: 24496118
    [Abstract] [Full Text] [Related]

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  • 11. Identifying types of physical activity with a single accelerometer: evaluating laboratory-trained algorithms in daily life.
    Gyllensten IC, Bonomi AG.
    IEEE Trans Biomed Eng; 2011 Sep 02; 58(9):2656-63. PubMed ID: 21712150
    [Abstract] [Full Text] [Related]

  • 12. Hip and Wrist Accelerometer Algorithms for Free-Living Behavior Classification.
    Ellis K, Kerr J, Godbole S, Staudenmayer J, Lanckriet G.
    Med Sci Sports Exerc; 2016 May 02; 48(5):933-40. PubMed ID: 26673126
    [Abstract] [Full Text] [Related]

  • 13. Real-time estimation of daily physical activity intensity by a triaxial accelerometer and a gravity-removal classification algorithm.
    Ohkawara K, Oshima Y, Hikihara Y, Ishikawa-Takata K, Tabata I, Tanaka S.
    Br J Nutr; 2011 Jun 02; 105(11):1681-91. PubMed ID: 21262061
    [Abstract] [Full Text] [Related]

  • 14. Actigraph accelerometer interinstrument reliability during free-living in adults.
    McClain JJ, Sisson SB, Tudor-Locke C.
    Med Sci Sports Exerc; 2007 Sep 02; 39(9):1509-14. PubMed ID: 17805082
    [Abstract] [Full Text] [Related]

  • 15. Comparison of raw acceleration from the GENEA and ActiGraph™ GT3X+ activity monitors.
    John D, Sasaki J, Staudenmayer J, Mavilia M, Freedson PS.
    Sensors (Basel); 2013 Oct 30; 13(11):14754-63. PubMed ID: 24177727
    [Abstract] [Full Text] [Related]

  • 16. Performance of Activity Classification Algorithms in Free-Living Older Adults.
    Sasaki JE, Hickey AM, Staudenmayer JW, John D, Kent JA, Freedson PS.
    Med Sci Sports Exerc; 2016 May 30; 48(5):941-50. PubMed ID: 26673129
    [Abstract] [Full Text] [Related]

  • 17. Energy expenditure prediction using a miniaturized ear-worn sensor.
    Atallah L, Leong JJ, Lo B, Yang GZ.
    Med Sci Sports Exerc; 2011 Jul 30; 43(7):1369-77. PubMed ID: 21200349
    [Abstract] [Full Text] [Related]

  • 18. Cross-validation and out-of-sample testing of physical activity intensity predictions with a wrist-worn accelerometer.
    Montoye AHK, Westgate BS, Fonley MR, Pfeiffer KA.
    J Appl Physiol (1985); 2018 May 01; 124(5):1284-1293. PubMed ID: 29369742
    [Abstract] [Full Text] [Related]

  • 19. Aspects of activity behavior as a determinant of the physical activity level.
    Bonomi AG, Plasqui G, Goris AH, Westerterp KR.
    Scand J Med Sci Sports; 2012 Feb 01; 22(1):139-45. PubMed ID: 20536909
    [Abstract] [Full Text] [Related]

  • 20. Detection of type, duration, and intensity of physical activity using an accelerometer.
    Bonomi AG, Goris AH, Yin B, Westerterp KR.
    Med Sci Sports Exerc; 2009 Sep 01; 41(9):1770-7. PubMed ID: 19657292
    [Abstract] [Full Text] [Related]

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