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Citing this Article

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Published on 12.08.13 in Vol 2, No 2 (2013): Jul-Dec

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

Works citing "Live Long and Prosper: Potentials of Low-Cost Consumer Devices for the Prevention of Cardiovascular Diseases"

Jochen Meyer, Andreas Hein

Med 2 0 2013 (Aug 12); 2(2):e7 

According to Crossref, the following articles are citing this article (DOI 10.2196/med20.2667):

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

  1. Meng Y, Speier W, Shufelt C, Joung S, E Van Eyk J, Bairey Merz CN, Lopez M, Spiegel B, Arnold CW. A Machine Learning Approach to Classifying Self-Reported Health Status in a Cohort of Patients With Heart Disease Using Activity Tracker Data. IEEE Journal of Biomedical and Health Informatics 2020;24(3):878
    CrossRef
  2. Speier W, Dzubur E, Zide M, Shufelt C, Joung S, Van Eyk JE, Bairey Merz CN, Lopez M, Spiegel B, Arnold C. Evaluating utility and compliance in a patient-based eHealth study using continuous-time heart rate and activity trackers. Journal of the American Medical Informatics Association 2018;25(10):1386
    CrossRef
  3. Hawkins J, Charles JM, Edwards M, Hallingberg B, McConnon L, Edwards RT, Jago R, Kelson M, Morgan K, Murphy S, Oliver EJ, Simpson SA, Moore G. Acceptability and Feasibility of Implementing Accelorometry-Based Activity Monitors and a Linked Web Portal in an Exercise Referral Scheme: Feasibility Randomized Controlled Trial. Journal of Medical Internet Research 2019;21(3):e12374
    CrossRef
  4. Sawani S, Siddiqui AR, Azam SI, Humayun K, Ahmed A, Habib A, Naz S, Tufail M, Iqbal R. Lifestyle changes and glycemic control in type 1 diabetes mellitus: a trial protocol with factorial design approach. Trials 2020;21(1)
    CrossRef
  5. Austin C, Hokanson J, McGinnis P, Patrick S. The Relationship between Running Power and Running Economy in Well-Trained Distance Runners. Sports 2018;6(4):142
    CrossRef
  6. Mercer K, Giangregorio L, Schneider E, Chilana P, Li M, Grindrod K. Acceptance of Commercially Available Wearable Activity Trackers Among Adults Aged Over 50 and With Chronic Illness: A Mixed-Methods Evaluation. JMIR mHealth and uHealth 2016;4(1):e7
    CrossRef
  7. Apovian CM, Garvey WT, Ryan DH. Challenging obesity: Patient, provider, and expert perspectives on the roles of available and emerging nonsurgical therapies. Obesity 2015;23(S2)
    CrossRef
  8. Meyer J, Boll S. Digital Health Devices for Everyone!. IEEE Pervasive Computing 2014;13(2):10
    CrossRef
  9. WOODMAN JA, CROUTER SE, BASSETT DR, FITZHUGH EC, BOYER WR. Accuracy of Consumer Monitors for Estimating Energy Expenditure and Activity Type. Medicine & Science in Sports & Exercise 2017;49(2):371
    CrossRef
  10. Zelenović J, Zelenović V. Managing Consumers and Employees through Digital Services. Sustainability 2022;14(14):8824
    CrossRef
  11. Rao K, Speier W, Meng Y, Wang J, Ramesh N, Xie F, Su Y, Nowell WB, Curtis JR, Arnold C. Machine Learning Approaches to Classify Self-Reported Rheumatoid Arthritis Health Scores Using Activity Tracker Data: Longitudinal Observational Study. JMIR Formative Research 2023;7:e43107
    CrossRef
  12. Wróbel-Lachowska M, Dominiak J, Woźniak MP, Bartłomiejczyk N, Diethei D, Wysokińska A, Niess J, Grudzień K, Woźniak PW, Romanowski A. ‘That’s when I put it on’: stakeholder perspectives in large-scale remote health monitoring for older adults. Personal and Ubiquitous Computing 2023;27(6):2193
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/med20.2667):

  1. Cosoli G, Scalise L. Sensors. 2019. Chapter 47:377
    CrossRef
  2. Meyer J, Fortmann J, Wasmann M, Heuten W. MultiMedia Modeling. 2015. Chapter 39:323
    CrossRef
  3. Hellmers S, Fudickar S, Büse C, Dasenbrock L, Heinks A, Bauer JM, Hein A. Ambient Assisted Living. 2017. Chapter 6:85
    CrossRef
  4. . Prescription des Activités Physiques. 2016. :195
    CrossRef