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

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

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

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

Journals

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  2. Zhai Y, Nasseri N, Pöttgen J, Gezhelbash E, Heesen C, Stellmann J. Smartphone Accelerometry: A Smart and Reliable Measurement of Real-Life Physical Activity in Multiple Sclerosis and Healthy Individuals. Frontiers in Neurology 2020;11 View
  3. Turner M, Nieuwenhuijsen M, Anderson K, Balshaw D, Cui Y, Dunton G, Hoppin J, 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 View
  4. Aldred R. Built Environment Interventions to Increase Active Travel: a Critical Review and Discussion. Current Environmental Health Reports 2019;6(4):309 View
  5. 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 View
  6. 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 View
  7. Gascon M, Zijlema W, Vert C, White M, Nieuwenhuijsen M. Outdoor blue spaces, human health and well-being: A systematic review of quantitative studies. International Journal of Hygiene and Environmental Health 2017;220(8):1207 View
  8. Sullivan A, Lachman M. Behavior Change with Fitness Technology in Sedentary Adults: A Review of the Evidence for Increasing Physical Activity. Frontiers in Public Health 2017;4 View
  9. Jerrett M, Donaire-Gonzalez D, Popoola O, Jones R, Cohen R, 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 View
  10. Jung-Min Lee , Gregory J. Welk , Timothy R. Derrick , Young-Won Kim , 권이석 . Feasibility of Calibrating Smartphone to Access Physical Activity. The Korean Journal of Measurement and Evaluation in Physical Education and Sports Science 2015;17(3):49 View
  11. Barrett M, Humblet O, Hiatt R, Adler N. Big Data and Disease Prevention: From Quantified Self to Quantified Communities. Big Data 2013;1(3):168 View
  12. Pah A, Rasmussen-Torvik L, Goel S, Greenland P, Kho A. Big Data: What Is It and What Does It Mean for Cardiovascular Research and Prevention Policy. Current Cardiovascular Risk Reports 2015;9(1) View
  13. Aranki D, Kurillo G, Yan P, Liebovitz D, 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 View
  14. Lee W, Seto E, Lin K, Migliaccio G. An evaluation of wearable sensors and their placements for analyzing construction worker's trunk posture in laboratory conditions. Applied Ergonomics 2017;65:424 View
  15. Chapizanis D, Karakitsios S, Gotti A, Sarigiannis D. Assessing personal exposure using Agent Based Modelling informed by sensors technology. Environmental Research 2021;192:110141 View
  16. Rodriguez V, Medrano C, Plaza I, Corella C, Abarca A, Julian J. Comparison of Several Algorithms to Estimate Activity Counts with Smartphones as an Indication of Physical Activity Level. IRBM 2019;40(2):95 View
  17. Triguero-Mas M, Donaire-Gonzalez D, Seto E, Valentín A, Smith G, Martínez D, Carrasco-Turigas G, Masterson D, Van den Berg M, Ambròs A, Martínez-Íñiguez T, Dedele A, Hurst G, Ellis N, Grazulevicius T, Voorsmit M, Cirach M, Cirac-Claveras J, Swart W, Clasquin E, Maas J, Wendel-Vos W, Jerrett M, Gražulevičienė R, Kruize H, Gidlow C, Nieuwenhuijsen M. Living Close to Natural Outdoor Environments in Four European Cities: Adults’ Contact with the Environments and Physical Activity. International Journal of Environmental Research and Public Health 2017;14(10):1162 View
  18. Donaire-Gonzalez D, Valentín A, van Nunen E, Curto A, Rodriguez A, Fernandez-Nieto M, Naccarati A, Tarallo S, Tsai M, Probst-Hensch N, Vermeulen R, Hoek G, Vineis P, Gulliver J, Nieuwenhuijsen M. ExpoApp: An integrated system to assess multiple personal environmental exposures. Environment International 2019;126:494 View
  19. Dowd K, Szeklicki R, Minetto M, Murphy M, Polito A, Ghigo E, van der Ploeg H, Ekelund U, Maciaszek J, Stemplewski R, Tomczak M, Donnelly A. A systematic literature review of reviews on techniques for physical activity measurement in adults: a DEDIPAC study. International Journal of Behavioral Nutrition and Physical Activity 2018;15(1) View
  20. 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 View
  21. Pande A, Mohapatra P, Nicorici A, Han J. 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 View
  22. Wan N, Wen M, Fan J, Tavake-Pasi O, McCormick S, Elliott K, Nicolosi E. Physical Activity Barriers and Facilitators Among US Pacific Islanders and the Feasibility of Using Mobile Technologies for Intervention: A Focus Group Study With Tongan Americans. Journal of Physical Activity and Health 2018;15(4):287 View
  23. Donaire-Gonzalez D, Valentín A, de Nazelle A, Ambros A, Carrasco-Turigas G, Seto E, Jerrett M, Nieuwenhuijsen M. Benefits of Mobile Phone Technology for Personal Environmental Monitoring. JMIR mHealth and uHealth 2016;4(4):e126 View
  24. Kondo M, Triguero-Mas M, Donaire-Gonzalez D, Seto E, Valentín A, Hurst G, Carrasco-Turigas G, Masterson D, Ambròs A, Ellis N, Swart W, Davis N, Maas J, Jerrett M, Gidlow C, Nieuwenhuijsen M. Momentary mood response to natural outdoor environments in four European cities. Environment International 2020;134:105237 View
  25. Maddison R, Gemming L, Monedero J, Bolger L, Belton S, Issartel J, Marsh S, Direito A, Solenhill M, Zhao J, Exeter D, Vathsangam H, Rawstorn J. Quantifying Human Movement Using the Movn Smartphone App: Validation and Field Study. JMIR mHealth and uHealth 2017;5(8):e122 View
  26. Donaire-Gonzalez D, Curto A, Valentín A, Andrusaityte S, Basagaña X, Casas M, Chatzi L, de Bont J, de Castro M, Dedele A, Granum B, Grazuleviciene R, Kampouri M, Lyon-Caen S, Manzano-Salgado C, Aasvang G, McEachan R, Meinhard-Kjellstad C, Michalaki E, Pañella P, Petraviciene I, Schwarze P, Slama R, Robinson O, Tamayo-Uria I, Vafeiadi M, Waiblinger D, Wright J, Vrijheid M, Nieuwenhuijsen M. Personal assessment of the external exposome during pregnancy and childhood in Europe.. Environmental Research 2019;174:95 View
  27. Su J, 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 View
  28. 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 View
  29. Smith M, Standl M, Heinrich J, Schulz H, Buchowski M. Accelerometric estimates of physical activity vary unstably with data handling. PLOS ONE 2017;12(11):e0187706 View
  30. Dėdelė A, Miškinytė A, Gražulevičienė R. The impact of particulate matter on allergy risk among adults: integrated exposure assessment. Environmental Science and Pollution Research 2019;26(10):10070 View
  31. Nieuwenhuijsen M, 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 View
  32. Lee W, Lin K, Seto E, Migliaccio G. Wearable sensors for monitoring on-duty and off-duty worker physiological status and activities in construction. Automation in Construction 2017;83:341 View
  33. Triguero-Mas M, Donaire-Gonzalez D, Seto E, Valentín A, Martínez D, Smith G, Hurst G, Carrasco-Turigas G, Masterson D, van den Berg M, Ambròs A, Martínez-Íñiguez T, Dedele A, Ellis N, Grazulevicius T, Voorsmit M, Cirach M, Cirac-Claveras J, Swart W, Clasquin E, Ruijsbroek A, Maas J, Jerret M, Gražulevičienė R, Kruize H, Gidlow C, Nieuwenhuijsen M. Natural outdoor environments and mental health: Stress as a possible mechanism. Environmental Research 2017;159:629 View
  34. Dunton G, 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 View
  35. Stålesen J, Westergren T, Herman Hansen B, Berntsen S. A Mapping Review of Physical Activity Recordings Derived From Smartphone Accelerometers. Journal of Physical Activity and Health 2020;17(11):1184 View
  36. Ho J, Zijlema W, Triguero-Mas M, Donaire-Gonzalez D, Valentín A, Ballester J, Chan E, Goggins W, Mo P, Kruize H, van den Berg M, Gražuleviciene R, Gidlow C, Jerrett M, Seto E, Barrera-Gómez J, Nieuwenhuijsen M. Does surrounding greenness moderate the relationship between apparent temperature and physical activity? Findings from the PHENOTYPE project. Environmental Research 2021;197:110992 View
  37. Prado R, Knebel M, Ribeiro E, Teixeira I, Sasaki J, Araújo L, Guerra P, Florindo A. Smartphone apps for tracking physical activity and sedentary behavior: A criterion validity review. Revista Brasileira de Atividade Física & Saúde 2022;27:1 View
  38. Yao Q, Wang J, Sun Y, Zhang L, Sun S, Cheng M, Yang Q, Wang S, Huang L, Lin T, Jia Y. Accuracy of steps measured by smartphones-based WeRun compared with ActiGraph-GT3X accelerometer in free-living conditions. Frontiers in Public Health 2022;10 View
  39. Yu H, Xu T, Chen J, Yin W, Ye F. Association of inflammation and lung function decline caused by personal PM2.5 exposure: a machine learning approach in time-series data. Environmental Science and Pollution Research 2022;29(53):80436 View
  40. Arumugam A, Samara S, Shalash R, Qadah R, Farhani A, Alnajim H, Alkalih H. Does Google Fit provide valid energy expenditure measurements of functional tasks compared to those of Fibion accelerometer in healthy individuals? A cross-sectional study. Diabetes & Metabolic Syndrome: Clinical Research & Reviews 2021;15(6):102301 View
  41. Nieuwenhuijsen M, Kruize H, Gidlow C, Andrusaityte S, Antó J, Basagaña X, Cirach M, Dadvand P, Danileviciute A, Donaire-Gonzalez D, Garcia J, Jerrett M, Jones M, Julvez J, van Kempen E, van Kamp I, Maas J, Seto E, Smith G, Triguero M, Wendel-Vos W, Wright J, Zufferey J, van den Hazel P, Lawrence R, Grazuleviciene R. Positivehealtheffects of thenaturaloutdoor environment intypicalpopulations in different regions inEurope (PHENOTYPE): a study programme protocol. BMJ Open 2014;4(4):e004951 View

Books/Policy Documents

  1. Aldred R. Advances in Transportation and Health. View
  2. Aranki D, Kurillo G, Bajcsy R. Handbook of Large-Scale Distributed Computing in Smart Healthcare. View