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Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

302 related items for PubMed ID: 24393233

  • 1. A universal, accurate intensity-based classification of different physical activities using raw data of accelerometer.
    Vähä-Ypyä H, Vasankari T, Husu P, Suni J, Sievänen H.
    Clin Physiol Funct Imaging; 2015 Jan; 35(1):64-70. PubMed ID: 24393233
    [Abstract] [Full Text] [Related]

  • 2. Validation of Cut-Points for Evaluating the Intensity of Physical Activity with Accelerometry-Based Mean Amplitude Deviation (MAD).
    Vähä-Ypyä H, Vasankari T, Husu P, Mänttäri A, Vuorimaa T, Suni J, Sievänen H.
    PLoS One; 2015 Jan; 10(8):e0134813. PubMed ID: 26292225
    [Abstract] [Full Text] [Related]

  • 3. 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]

  • 4. Single-accelerometer-based daily physical activity classification.
    Long X, Yin B, Aarts RM.
    Annu Int Conf IEEE Eng Med Biol Soc; 2009 Jan; 2009():6107-10. PubMed ID: 19965261
    [Abstract] [Full Text] [Related]

  • 5. Estimation of accelerometer orientation for activity recognition.
    Friedman A, Hajj Chehade N, Chien C, Pottie G.
    Annu Int Conf IEEE Eng Med Biol Soc; 2012 Jan; 2012():2076-9. PubMed ID: 23366329
    [Abstract] [Full Text] [Related]

  • 6. Mean amplitude deviation calculated from raw acceleration data: a novel method for classifying the intensity of adolescents' physical activity irrespective of accelerometer brand.
    Aittasalo M, Vähä-Ypyä H, Vasankari T, Husu P, Jussila AM, Sievänen H.
    BMC Sports Sci Med Rehabil; 2015 Jan; 7():18. PubMed ID: 26251724
    [Abstract] [Full Text] [Related]

  • 7. The application of EMD in activity recognition based on a single triaxial accelerometer.
    Liao M, Guo Y, Qin Y, Wang Y.
    Biomed Mater Eng; 2015 Jan; 26 Suppl 1():S1533-9. PubMed ID: 26405917
    [Abstract] [Full Text] [Related]

  • 8. Intensity Thresholds on Raw Acceleration Data: Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD) Approaches.
    Bakrania K, Yates T, Rowlands AV, Esliger DW, Bunnewell S, Sanders J, Davies M, Khunti K, Edwardson CL.
    PLoS One; 2016 Jan; 11(10):e0164045. PubMed ID: 27706241
    [Abstract] [Full Text] [Related]

  • 9. Comparing accelerometer, pedometer and a questionnaire for measuring physical activity in bronchiectasis: a validity and feasibility study?
    O'Neill B, McDonough SM, Wilson JJ, Bradbury I, Hayes K, Kirk A, Kent L, Cosgrove D, Bradley JM, Tully MA.
    Respir Res; 2017 Jan 14; 18(1):16. PubMed ID: 28088206
    [Abstract] [Full Text] [Related]

  • 10. Objective diagnosis of ADHD using IMUs.
    O'Mahony N, Florentino-Liano B, Carballo JJ, Baca-García E, Rodríguez AA.
    Med Eng Phys; 2014 Jul 14; 36(7):922-6. PubMed ID: 24657100
    [Abstract] [Full Text] [Related]

  • 11. Exploratory data analysis of acceleration signals to select light-weight and accurate features for real-time activity recognition on smartphones.
    Khan AM, Siddiqi MH, Lee SW.
    Sensors (Basel); 2013 Sep 27; 13(10):13099-122. PubMed ID: 24084108
    [Abstract] [Full Text] [Related]

  • 12. Estimating intensity of physical activity: a comparison of wearable accelerometer and gyro sensors and 3 sensor locations.
    Pärkkä J, Ermes M, Antila K, van Gils M, Mänttäri A, Nieminen H.
    Annu Int Conf IEEE Eng Med Biol Soc; 2007 Sep 27; 2007():1511-4. PubMed ID: 18002254
    [Abstract] [Full Text] [Related]

  • 13. Separating bedtime rest from activity using waist or wrist-worn accelerometers in youth.
    Tracy DJ, Xu Z, Choi L, Acra S, Chen KY, Buchowski MS.
    PLoS One; 2014 Sep 27; 9(4):e92512. PubMed ID: 24727999
    [Abstract] [Full Text] [Related]

  • 14. Where to wear accelerometers to measure physical activity in people?
    Thaler-Kall K, Tusker F, Hermsdörfer J, Gorzelniak L, Horsch A.
    Stud Health Technol Inform; 2013 Sep 27; 192():1045. PubMed ID: 23920819
    [Abstract] [Full Text] [Related]

  • 15. Performance of thigh-mounted triaxial accelerometer algorithms in objective quantification of sedentary behaviour and physical activity in older adults.
    Wullems JA, Verschueren SMP, Degens H, Morse CI, Onambélé GL.
    PLoS One; 2017 Sep 27; 12(11):e0188215. PubMed ID: 29155839
    [Abstract] [Full Text] [Related]

  • 16. Activity recognition with smartphone support.
    Guiry JJ, van de Ven P, Nelson J, Warmerdam L, Riper H.
    Med Eng Phys; 2014 Jun 27; 36(6):670-5. PubMed ID: 24641812
    [Abstract] [Full Text] [Related]

  • 17. Optimal placement of accelerometers for the detection of everyday activities.
    Cleland I, Kikhia B, Nugent C, Boytsov A, Hallberg J, Synnes K, McClean S, Finlay D.
    Sensors (Basel); 2013 Jul 17; 13(7):9183-200. PubMed ID: 23867744
    [Abstract] [Full Text] [Related]

  • 18. Long-term activity recognition from wristwatch accelerometer data.
    Garcia-Ceja E, Brena RF, Carrasco-Jimenez JC, Garrido L.
    Sensors (Basel); 2014 Nov 27; 14(12):22500-24. PubMed ID: 25436652
    [Abstract] [Full Text] [Related]

  • 19. The use of accelerometers and gyroscopes to estimate hip and knee angles on gait analysis.
    Alonge F, Cucco E, D'Ippolito F, Pulizzotto A.
    Sensors (Basel); 2014 May 13; 14(5):8430-46. PubMed ID: 24828578
    [Abstract] [Full Text] [Related]

  • 20. 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 13; 45(10):2012-9. PubMed ID: 23584403
    [Abstract] [Full Text] [Related]

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