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Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

308 related items for PubMed ID: 28107205

  • 1. Comparison of linear and non-linear models for predicting energy expenditure from raw accelerometer data.
    Montoye AHK, Begum M, Henning Z, Pfeiffer KA.
    Physiol Meas; 2017 Feb; 38(2):343-357. PubMed ID: 28107205
    [Abstract] [Full Text] [Related]

  • 2. Wrist-independent energy expenditure prediction models from raw accelerometer data.
    Montoye AH, Pivarnik JM, Mudd LM, Biswas S, Pfeiffer KA.
    Physiol Meas; 2016 Oct; 37(10):1770-1784. PubMed ID: 27653642
    [Abstract] [Full Text] [Related]

  • 3. Energy Expenditure Prediction Using Raw Accelerometer Data in Simulated Free Living.
    Montoye AH, Mudd LM, Biswas S, Pfeiffer KA.
    Med Sci Sports Exerc; 2015 Aug; 47(8):1735-46. PubMed ID: 25494392
    [Abstract] [Full Text] [Related]

  • 4. Investigating optimal accelerometer placement for energy expenditure prediction in children using a machine learning approach.
    Mackintosh KA, Montoye AH, Pfeiffer KA, McNarry MA.
    Physiol Meas; 2016 Oct; 37(10):1728-1740. PubMed ID: 27653339
    [Abstract] [Full Text] [Related]

  • 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. Use of a Wireless Network of Accelerometers for Improved Measurement of Human Energy Expenditure.
    Montoye AH, Dong B, Biswas S, Pfeiffer KA.
    Electronics (Basel); 2014 Nov; 3(2):205-220. PubMed ID: 25530874
    [Abstract] [Full Text] [Related]

  • 7. Evaluation of the activPAL accelerometer for physical activity and energy expenditure estimation in a semi-structured setting.
    Montoye AHK, Pivarnik JM, Mudd LM, Biswas S, Pfeiffer KA.
    J Sci Med Sport; 2017 Nov; 20(11):1003-1007. PubMed ID: 28483558
    [Abstract] [Full Text] [Related]

  • 8. Validation of a wireless accelerometer network for energy expenditure measurement.
    Montoye AH, Dong B, Biswas S, Pfeiffer KA.
    J Sports Sci; 2016 Nov; 34(21):2130-9. PubMed ID: 26942316
    [Abstract] [Full Text] [Related]

  • 9. Validation and Comparison of Accelerometers Worn on the Hip, Thigh, and Wrists for Measuring Physical Activity and Sedentary Behavior.
    Montoye AHK, Pivarnik JM, Mudd LM, Biswas S, Pfeiffer KA.
    AIMS Public Health; 2016 Nov; 3(2):298-312. PubMed ID: 29546164
    [Abstract] [Full Text] [Related]

  • 10. Wrist-worn triaxial accelerometry predicts the energy expenditure of non-vigorous daily physical activities.
    Sirichana W, Dolezal BA, Neufeld EV, Wang X, Cooper CB.
    J Sci Med Sport; 2017 Aug; 20(8):761-765. PubMed ID: 28159535
    [Abstract] [Full Text] [Related]

  • 11. Comparison of different prediction models for estimation of walking and running energy expenditure based on a wristwear three-axis accelerometer.
    Xu L, Zhang J, Li Z, Liu Y, Jia Z, Han X, Liu C, Zhou Z.
    Front Physiol; 2023 Aug; 14():1202737. PubMed ID: 38028785
    [Abstract] [Full Text] [Related]

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  • 13. Estimation of energy expenditure using CSA accelerometers at hip and wrist sites.
    Swartz AM, Strath SJ, Bassett DR, O'Brien WL, King GA, Ainsworth BE.
    Med Sci Sports Exerc; 2000 Sep; 32(9 Suppl):S450-6. PubMed ID: 10993414
    [Abstract] [Full Text] [Related]

  • 14. Ngram time series model to predict activity type and energy cost from wrist, hip and ankle accelerometers: implications of age.
    Strath SJ, Kate RJ, Keenan KG, Welch WA, Swartz AM.
    Physiol Meas; 2015 Nov; 36(11):2335-51. PubMed ID: 26449155
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  • 16. Estimating energy expenditure using body-worn accelerometers: a comparison of methods, sensors number and positioning.
    Altini M, Penders J, Vullers R, Amft O.
    IEEE J Biomed Health Inform; 2015 Jan; 19(1):219-26. PubMed ID: 24691168
    [Abstract] [Full Text] [Related]

  • 17. Comparison of four Fitbit and Jawbone activity monitors with a research-grade ActiGraph accelerometer for estimating physical activity and energy expenditure.
    Imboden MT, Nelson MB, Kaminsky LA, Montoye AH.
    Br J Sports Med; 2018 Jul; 52(13):844-850. PubMed ID: 28483930
    [Abstract] [Full Text] [Related]

  • 18. Using GPS, accelerometry and heart rate to predict outdoor graded walking energy expenditure.
    de Müllenheim PY, Chaudru S, Emily M, Gernigon M, Mahé G, Bickert S, Prioux J, Noury-Desvaux B, Le Faucheur A.
    J Sci Med Sport; 2018 Feb; 21(2):166-172. PubMed ID: 29110991
    [Abstract] [Full Text] [Related]

  • 19. The Effect of Sensor Placement and Number on Physical Activity Recognition and Energy Expenditure Estimation in Older Adults: Validation Study.
    Davoudi A, Mardini MT, Nelson D, Albinali F, Ranka S, Rashidi P, Manini TM.
    JMIR Mhealth Uhealth; 2021 May 03; 9(5):e23681. PubMed ID: 33938809
    [Abstract] [Full Text] [Related]

  • 20. Distributed lag and spline modeling for predicting energy expenditure from accelerometry in youth.
    Choi L, Chen KY, Acra SA, Buchowski MS.
    J Appl Physiol (1985); 2010 Feb 03; 108(2):314-27. PubMed ID: 19959770
    [Abstract] [Full Text] [Related]

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