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Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

237 related items for PubMed ID: 25340887

  • 1. Machine learning for activity recognition: hip versus wrist data.
    Trost SG, Zheng Y, Wong WK.
    Physiol Meas; 2014 Nov; 35(11):2183-9. PubMed ID: 25340887
    [Abstract] [Full Text] [Related]

  • 2. Sensor-enabled Activity Class Recognition in Preschoolers: Hip versus Wrist Data.
    Trost SG, Cliff DP, Ahmadi MN, Tuc NV, Hagenbuchner M.
    Med Sci Sports Exerc; 2018 Mar; 50(3):634-641. PubMed ID: 29059107
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  • 3. 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; 20(1):75-80. PubMed ID: 27372275
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  • 4. 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; 48(5):933-40. PubMed ID: 26673126
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  • 5. A random forest classifier for the prediction of energy expenditure and type of physical activity from wrist and hip accelerometers.
    Ellis K, Kerr J, Godbole S, Lanckriet G, Wing D, Marshall S.
    Physiol Meas; 2014 Nov; 35(11):2191-203. PubMed ID: 25340969
    [Abstract] [Full Text] [Related]

  • 6. Machine learning algorithms for activity recognition in ambulant children and adolescents with cerebral palsy.
    Ahmadi M, O'Neil M, Fragala-Pinkham M, Lennon N, Trost S.
    J Neuroeng Rehabil; 2018 Nov 15; 15(1):105. PubMed ID: 30442154
    [Abstract] [Full Text] [Related]

  • 7. Hip and Wrist-Worn Accelerometer Data Analysis for Toddler Activities.
    Kwon S, Zavos P, Nickele K, Sugianto A, Albert MV.
    Int J Environ Res Public Health; 2019 Jul 21; 16(14):. PubMed ID: 31330889
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  • 11. 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
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  • 14. Age group comparability of raw accelerometer output from wrist- and hip-worn monitors.
    Hildebrand M, VAN Hees VT, Hansen BH, Ekelund U.
    Med Sci Sports Exerc; 2014 Sep 01; 46(9):1816-24. PubMed ID: 24887173
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  • 16. Activity recognition with smartphone support.
    Guiry JJ, van de Ven P, Nelson J, Warmerdam L, Riper H.
    Med Eng Phys; 2014 Jun 01; 36(6):670-5. PubMed ID: 24641812
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  • 17. Free-living Evaluation of Laboratory-based Activity Classifiers in Preschoolers.
    Ahmadi MN, Brookes D, Chowdhury A, Pavey T, Trost SG.
    Med Sci Sports Exerc; 2020 May 01; 52(5):1227-1234. PubMed ID: 31764460
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  • 18. Effect of sampling rate on acceleration and counts of hip- and wrist-worn ActiGraph accelerometers in children.
    Clevenger KA, Pfeiffer KA, Mackintosh KA, McNarry MA, Brønd J, Arvidsson D, Montoye AHK.
    Physiol Meas; 2019 Sep 30; 40(9):095008. PubMed ID: 31518999
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  • 19. Reliable recognition of lying, sitting, and standing with a hip-worn accelerometer.
    Vähä-Ypyä H, Husu P, Suni J, Vasankari T, Sievänen H.
    Scand J Med Sci Sports; 2018 Mar 30; 28(3):1092-1102. PubMed ID: 29144567
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