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Citing this Article

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Published on 15.02.19 in Vol 7, No 2 (2019): February

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

Works citing "The Current State of Mobile Phone Apps for Monitoring Heart Rate, Heart Rate Variability, and Atrial Fibrillation: Narrative Review"

According to Crossref, the following articles are citing this article (DOI 10.2196/11606):

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

  1. Ahmed N, Zhu Y. Early Detection of Atrial Fibrillation Based on ECG Signals. Bioengineering 2020;7(1):16
    CrossRef
  2. Chen Y, Lu W, Pagaduan JC, Kuo C. A Novel Smartphone App for the Measurement of Ultra–Short-Term and Short-Term Heart Rate Variability: Validity and Reliability Study. JMIR mHealth and uHealth 2020;8(7):e18761
    CrossRef
  3. Koepp J, Baron MV, Hernandes Martins PR, Brandenburg C, Kira ATF, Trindade VD, Ley Dominguez LM, Carneiro M, Frozza R, Possuelo LG, De Mello Pinto MV, Mahlmann Kipper L, Pinheiro da Costa BE. The Quality of Mobile Apps Used for the Identification of Pressure Ulcers in Adults: Systematic Survey and Review of Apps in App Stores. JMIR mHealth and uHealth 2020;8(6):e14266
    CrossRef
  4. Vandekerckhove P, Vandekerckhove Y, Tavernier R, De Jaegher K, de Mul M. Leveraging User Experience to Improve Video Consultations in a Cardiology Practice During the COVID-19 Pandemic: Initial Insights. Journal of Medical Internet Research 2020;22(6):e19771
    CrossRef
  5. Liu I, Ni S, Peng K. Enhancing the Robustness of Smartphone Photoplethysmography: A Signal Quality Index Approach. Sensors 2020;20(7):1923
    CrossRef
  6. Liu I, Ni S, Peng K. Happiness at Your Fingertips: Assessing Mental Health with Smartphone Photoplethysmogram-Based Heart Rate Variability Analysis. Telemedicine and e-Health 2020;
    CrossRef
  7. Sadek I, Heng 2nd TTS, Ping 3rd ESC, Abdulrazak 4th B. A new approach for detecting sleep apnea using a contactless bed sensor: a comparison study (Preprint). Journal of Medical Internet Research 2020;
    CrossRef
  8. Ding EY, Marcus GM, McManus DD. Emerging Technologies for Identifying Atrial Fibrillation. Circulation Research 2020;127(1):128
    CrossRef
  9. MacKinnon GE, Brittain EL. Mobile Health Technologies in Cardiopulmonary Disease. Chest 2020;157(3):654
    CrossRef
  10. Guan J, Wang A, Song W, Obore N, He P, Fan S, Zhi H, Wang L. Screening for arrhythmia with the new portable single-lead electrocardiographic device (SnapECG): an application study in community-based elderly population in Nanjing, China. Aging Clinical and Experimental Research 2020;
    CrossRef
  11. Marinucci D, Sbrollini A, Marcantoni I, Morettini M, Swenne CA, Burattini L. Artificial Neural Network for Atrial Fibrillation Identification in Portable Devices. Sensors 2020;20(12):3570
    CrossRef
  12. Turchioe MR, Jimenez V, Isaac S, Alshalabi M, Slotwiner D, Creber RM. Review of mobile applications for the detection and management of atrial fibrillation. Heart Rhythm O2 2020;1(1):35
    CrossRef
  13. Vavrinsky E, Subjak J, Donoval M, Wagner A, Zavodnik T, Svobodova H. Application of Modern Multi-Sensor Holter in Diagnosis and Treatment. Sensors 2020;20(9):2663
    CrossRef
  14. Frisch DR. Diagnosing atrial fibrillation by mobile technology: physician decision or device provision?. Heart 2020;106(9):629
    CrossRef
  15. Ringwald M, Crich A, Beysard N. Smart watch recording of ventricular tachycardia: Case study. The American Journal of Emergency Medicine 2020;38(4):849.e3
    CrossRef
  16. Saarikko J, Niela-Vilen H, Ekholm E, Hamari L, Azimi I, Liljeberg P, Rahmani AM, Löyttyniemi E, Axelin A. Continuous 7-Month Internet of Things–Based Monitoring of Health Parameters of Pregnant and Postpartum Women: Prospective Observational Feasibility Study. JMIR Formative Research 2020;4(7):e12417
    CrossRef
  17. Baldassarre A, Mucci N, Padovan M, Pellitteri A, Viscera S, Lecca LI, Galea RP, Arcangeli G. The Role of Electrocardiography in Occupational Medicine, from Einthoven’s Invention to the Digital Era of Wearable Devices. International Journal of Environmental Research and Public Health 2020;17(14):4975
    CrossRef
  18. Kizakevich PN, Eckhoff RP, Lewis GF, Davila MI, Hourani LL, Watkins R, Weimer B, Wills T, Morgan JK, Morgan T, Meleth S, Lewis A, Krzyzanowski MC, Ramirez D, Boyce M, Litavecz SD, Lane ME, Strange LB. Biofeedback-Assisted Resilience Training for Traumatic and Operational Stress: Preliminary Analysis of a Self-Delivered Digital Health Methodology. JMIR mHealth and uHealth 2019;7(9):e12590
    CrossRef
  19. Tabei F, Zaman R, Foysal KH, Kumar R, Kim Y, Chong JW, Mumtaz W. A novel diversity method for smartphone camera-based heart rhythm signals in the presence of motion and noise artifacts. PLOS ONE 2019;14(6):e0218248
    CrossRef
  20. Patel UK, Anwar A, Saleem S, Malik P, Rasul B, Patel K, Yao R, Seshadri A, Yousufuddin M, Arumaithurai K. Artificial intelligence as an emerging technology in the current care of neurological disorders. Journal of Neurology 2019;
    CrossRef
  21. Martymianova LO, Tykhonova TM, Bychkova OY, Lysenko NV, Barabash NY. GENERAL CARDIOVASCULAR RISK AND FUNCTIONAL INDICATORS OF THE PERMANENT ATRIAL FIBRILLATION. Wiadomości Lekarskie 2019;72(12)
    CrossRef
  22. Diederichsen SZ, Haugan KJ, Brandes A, Lanng MB, Graff C, Krieger D, Kronborg C, Holst AG, Køber L, Højberg S, Svendsen JH. Natural History of Subclinical Atrial Fibrillation Detected by Implanted Loop Recorders. Journal of the American College of Cardiology 2019;74(22):2771
    CrossRef