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Journal of Medical Internet Research

Citing this Article

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Published on 13.06.13 in Vol 15, No 6 (2013): June

This paper is in the following e-collection/theme issue:

Works citing "Comparison of Physical Activity Measures Using Mobile Phone-Based CalFit and Actigraph"

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.2470):

(note that this is only a small subset of citations)

  1. Jerrett M, Donaire-Gonzalez D, Popoola O, Jones R, Cohen RC, Almanza E, de Nazelle A, Mead I, Carrasco-Turigas G, Cole-Hunter T, Triguero-Mas M, Seto E, Nieuwenhuijsen M. Validating novel air pollution sensors to improve exposure estimates for epidemiological analyses and citizen science. Environmental Research 2017;158:286
    CrossRef
  2. Maddison R, Gemming L, Monedero J, Bolger L, Belton S, Issartel J, Marsh S, Direito A, Solenhill M, Zhao J, Exeter DJ, Vathsangam H, Rawstorn JC. Quantifying Human Movement Using the Movn Smartphone App: Validation and Field Study. JMIR mHealth and uHealth 2017;5(8):e122
    CrossRef
  3. Sullivan AN, Lachman ME. Behavior Change with Fitness Technology in Sedentary Adults: A Review of the Evidence for Increasing Physical Activity. Frontiers in Public Health 2017;4
    CrossRef
  4. Lee W, Lin K, Seto E, Migliaccio GC. Wearable sensors for monitoring on-duty and off-duty worker physiological status and activities in construction. Automation in Construction 2017;
    CrossRef
  5. Turner MC, Nieuwenhuijsen M, Anderson K, Balshaw D, Cui Y, Dunton G, Hoppin JA, Koutrakis P, Jerrett M. Assessing the Exposome with External Measures: Commentary on the State of the Science and Research Recommendations. Annual Review of Public Health 2017;38(1):215
    CrossRef
  6. Lee W, Seto E, Lin K, Migliaccio GC. An evaluation of wearable sensors and their placements for analyzing construction worker's trunk posture in laboratory conditions. Applied Ergonomics 2017;65:424
    CrossRef
  7. Pande A, Mohapatra P, Nicorici A, Han JJ. Machine Learning to Improve Energy Expenditure Estimation in Children With Disabilities: A Pilot Study in Duchenne Muscular Dystrophy. JMIR Rehabilitation and Assistive Technologies 2016;3(2):e7
    CrossRef
  8. Dunton GF, Dzubur E, Intille S. Feasibility and Performance Test of a Real-Time Sensor-Informed Context-Sensitive Ecological Momentary Assessment to Capture Physical Activity. Journal of Medical Internet Research 2016;18(6):e106
    CrossRef
  9. Aranki D, Kurillo G, Yan P, Liebovitz DM, Bajcsy R. Real-Time Tele-Monitoring of Patients with Chronic Heart-Failure Using a Smartphone: Lessons Learned. IEEE Transactions on Affective Computing 2016;7(3):206
    CrossRef
  10. Donaire-Gonzalez D, Valentín A, de Nazelle A, Ambros A, Carrasco-Turigas G, Seto E, Jerrett M, Nieuwenhuijsen MJ. Benefits of Mobile Phone Technology for Personal Environmental Monitoring. JMIR mHealth and uHealth 2016;4(4):e126
    CrossRef
  11. Li P, Wang Y, Tian Y, Zhou T, Li J. An Automatic User-adapted Physical Activity Classification Method Using Smartphones. IEEE Transactions on Biomedical Engineering 2016;:1
    CrossRef
  12. Seto E, Hua J, Wu L, Shia V, Eom S, Wang M, Li Y, Yao L. Models of Individual Dietary Behavior Based on Smartphone Data: The Influence of Routine, Physical Activity, Emotion, and Food Environment. PLOS ONE 2016;11(4):e0153085
    CrossRef
  13. Nieuwenhuijsen MJ, Donaire-Gonzalez D, Rivas I, de Castro M, Cirach M, Hoek G, Seto E, Jerrett M, Sunyer J. Variability in and Agreement between Modeled and Personal Continuously Measured Black Carbon Levels Using Novel Smartphone and Sensor Technologies. Environmental Science & Technology 2015;49(5):2977
    CrossRef
  14. Mimura K, Kishino H, Karino G, Nitta E, Senoo A, Ikegami K, Kunikata T, Yamanouchi H, Nakamura S, Sato K, Koshiba M. Potential of a smartphone as a stress-free sensor of daily human behaviour. Behavioural Brain Research 2015;276:181
    CrossRef
  15. Pah AR, Rasmussen-Torvik LJ, Goel S, Greenland P, Kho AN. Big Data: What Is It and What Does It Mean for Cardiovascular Research and Prevention Policy. Current Cardiovascular Risk Reports 2015;9(1)
    CrossRef
  16. Su JG, Jerrett M, Meng Y, Pickett M, Ritz B. Integrating smart-phone based momentary location tracking with fixed site air quality monitoring for personal exposure assessment. Science of The Total Environment 2015;506-507:518
    CrossRef
  17. Bort-Roig J, Gilson ND, Puig-Ribera A, Contreras RS, Trost SG. Measuring and Influencing Physical Activity with Smartphone Technology: A Systematic Review. Sports Medicine 2014;44(5):671
    CrossRef
  18. Nieuwenhuijsen M, Donaire-Gonzalez D, Foraster M, Martinez D, Cisneros A. Using Personal Sensors to Assess the Exposome and Acute Health Effects. International Journal of Environmental Research and Public Health 2014;11(8):7805
    CrossRef
  19. Barrett MA, Humblet O, Hiatt RA, Adler NE. Big Data and Disease Prevention:From Quantified Self to Quantified Communities. Big Data 2013;1(3):168
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/jmir.2470)

:
  1. Aranki D, Kurillo G, Bajcsy R. Handbook of Large-Scale Distributed Computing in Smart Healthcare. 2017. Chapter 18:473
    CrossRef