Published on in Vol 5 , No 8 (2017) :August

Clinical Validation of Heart Rate Apps: Mixed-Methods Evaluation Study

Clinical Validation of Heart Rate Apps: Mixed-Methods Evaluation Study

Clinical Validation of Heart Rate Apps: Mixed-Methods Evaluation Study

Journals

  1. Witt D, Kellogg R, Snyder M, Dunn J. Windows into human health through wearables data analytics. Current Opinion in Biomedical Engineering 2019;9:28 View
  2. Christle J, Hershman S, Torres Soto J, Ashley E. Mobile Health Monitoring of Cardiac Status. Annual Review of Biomedical Data Science 2020;3(1):243 View
  3. Zheng Q, Tang Q, Wang Z, Li Z. Self-powered cardiovascular electronic devices and systems. Nature Reviews Cardiology 2021;18(1):7 View
  4. Pipitprapat W, Harnchoowong S, Suchonwanit P, Sriphrapradang C. The validation of smartphone applications for heart rate measurement. Annals of Medicine 2018;50(8):721 View
  5. Lee J, Park Y, Kweon S, Kim S, Ji W, Choi C. A Cardiopulmonary Monitoring System for Patient Transport Within Hospitals Using Mobile Internet of Things Technology: Observational Validation Study. JMIR mHealth and uHealth 2018;6(11):e12048 View
  6. Dunn J, Runge R, Snyder M. Wearables and the medical revolution. Personalized Medicine 2018;15(5):429 View
  7. Ding E, Svennberg E, Wurster C, Duncker D, Manninger M, Lubitz S, Dickson E, Fitzgibbons T, Akoum N, Al-Khatib S, Attia Z, Ghanbari H, Marrouche N, Mendenhall G, Peters N, Tarakji K, Turakhia M, Wan E, McManus D. Survey of current perspectives on consumer-available digital health devices for detecting atrial fibrillation. Cardiovascular Digital Health Journal 2020;1(1):21 View
  8. Jaafar Z, Murugan A. VALIDATION OF SMARTPHONE FREE HEART RATE MONITORING APPLICATION DURING TREADMILL EXERCISE. Revista Brasileira de Medicina do Esporte 2019;25(2):112 View
  9. Ding E, Marcus G, McManus D. Emerging Technologies for Identifying Atrial Fibrillation. Circulation Research 2020;127(1):128 View
  10. Sadek I, Heng T, Seet E, Abdulrazak B. A New Approach for Detecting Sleep Apnea Using a Contactless Bed Sensor: Comparison Study. Journal of Medical Internet Research 2020;22(9):e18297 View
  11. Kang S, Joe B, Yoon Y, Cho G, Shin I, Suh J. Cardiac Auscultation Using Smartphones: Pilot Study. JMIR mHealth and uHealth 2018;6(2):e49 View
  12. Verbrugge F, Proesmans T, Vijgen J, Mullens W, Rivero-Ayerza M, Van Herendael H, Vandervoort P, Nuyens D. Atrial fibrillation screening with photo-plethysmography through a smartphone camera. EP Europace 2019;21(8):1167 View
  13. Ledwoch J, Duncker D. eHealth – Smart Devices revolutionieren die Kardiologie. Herzschrittmachertherapie + Elektrophysiologie 2020;31(4):368 View
  14. Li K, White F, Tipoe T, Liu T, Wong M, Jesuthasan A, Baranchuk A, Tse G, Yan B. The Current State of Mobile Phone Apps for Monitoring Heart Rate, Heart Rate Variability, and Atrial Fibrillation: Narrative Review. JMIR mHealth and uHealth 2019;7(2):e11606 View
  15. Ding E, Ensom E, Hafer N, Buchholz B, Picard M, Dunlap D, Rogers E, Lawton C, Koren A, Lilly C, Fitzgibbons T, McManus D. Point-of-care technologies in heart, lung, blood and sleep disorders from the Center for Advancing Point-of-Care Technologies. Current Opinion in Biomedical Engineering 2019;11:58 View
  16. Villani V, Righi M, Sabattini L, Secchi C. Wearable Devices for the Assessment of Cognitive Effort for Human–Robot Interaction. IEEE Sensors Journal 2020;20(21):13047 View
  17. Xie L, Li Z, Zhou Y, He Y, Zhu J. Computational Diagnostic Techniques for Electrocardiogram Signal Analysis. Sensors 2020;20(21):6318 View
  18. Mühlen J, Stang J, Lykke Skovgaard E, Judice P, Molina-Garcia P, Johnston W, Sardinha L, Ortega F, Caulfield B, Bloch W, Cheng S, Ekelund U, Brønd J, Grøntved A, Schumann M. Recommendations for determining the validity of consumer wearable heart rate devices: expert statement and checklist of the INTERLIVE Network. British Journal of Sports Medicine 2021;55(14):767 View
  19. Béres S, Holczer L, Hejjel L. On the Minimal Adequate Sampling Frequency of the Photoplethysmogram for Pulse Rate Monitoring and Heart Rate Variability Analysis in Mobile and Wearable Technology. Measurement Science Review 2019;19(5):232 View
  20. Krzowski B, Skoczylas K, Osak G, Żurawska N, Peller M, Kołtowski Ł, Zych A, Główczyńska R, Lodziński P, Grabowski M, Opolski G, Balsam P. Kardia Mobile and ISTEL HR applicability in clinical practice: a comparison of Kardia Mobile, ISTEL HR, and standard 12-lead electrocardiogram records in 98 consecutive patients of a tertiary cardiovascular care centre. European Heart Journal - Digital Health 2021;2(3):467 View
  21. van der Velden R, Verhaert D, Hermans A, Duncker D, Manninger M, Betz K, Gawalko M, Desteghe L, Pisters R, Hemels M, Pison L, Sohaib A, Sultan A, Steven D, Wijtvliet P, Gupta D, Svennberg E, Luermans J, Chaldoupi M, Vernooy K, den Uijl D, Lodzinski P, Jansen W, Eckstein J, Bollmann A, Vandervoort P, Crijns H, Tieleman R, Heidbuchel H, Pluymaekers N, Hendriks J, Linz D. The photoplethysmography dictionary: practical guidance on signal interpretation and clinical scenarios from TeleCheck-AF. European Heart Journal - Digital Health 2021;2(3):363 View
  22. Betz K, van der Velden R, Gawalko M, Hermans A, Pluymaekers N, Hillmann H, Hendriks J, Duncker D, Linz D. Interpretation der Photoplethysmographie: Schritt für Schritt. Herzschrittmachertherapie + Elektrophysiologie 2021;32(3):406 View
  23. Książczyk M, Dębska-Kozłowska A, Warchoł I, Lubiński A. Enhancing Healthcare Access–Smartphone Apps in Arrhythmia Screening: Viewpoint. JMIR mHealth and uHealth 2021;9(8):e23425 View
  24. Yen C, Chang S, Jia-Xian L, Huang Y. A Deep Learning-Based Continuous Blood Pressure Measurement by Dual Photoplethysmography Signals. Computers, Materials & Continua 2022;70(2):2937 View
  25. Garikapati K, Turnbull S, Bennett R, Campbell T, Kanawati J, Wong M, Thomas S, Chow C, Kumar S. The Role of Contemporary Wearable and Handheld Devices in the Diagnosis and Management of Cardiac Arrhythmias. Heart, Lung and Circulation 2022;31(11):1432 View
  26. Knight S, Lipoth J, Namvari M, Gu C, Hedayati Ch. M, Syed-Abdul S, Spiteri R. The Accuracy of Wearable Photoplethysmography Sensors for Telehealth Monitoring: A Scoping Review. Telemedicine and e-Health 2022 View
  27. Cermakova E, Piskovska A, Trhonova V, Schilliger L, Knotek Z. Comparison of three ECG machines for electrocardiography in green iguanas (Iguana iguana). Veterinární medicína 2021;66(2):66 View
  28. Sim D, Brothers M, Slocik J, Islam A, Maruyama B, Grigsby C, Naik R, Kim S. Biomarkers and Detection Platforms for Human Health and Performance Monitoring: A Review. Advanced Science 2022;9(7):2104426 View
  29. Lujan M, Perez-Pozuelo I, Grandner M. Past, Present, and Future of Multisensory Wearable Technology to Monitor Sleep and Circadian Rhythms. Frontiers in Digital Health 2021;3 View
  30. Wong M, Hei H, Lim S, Ng E. Applied machine learning for blood pressure estimation using a small, real-world electrocardiogram and photoplethysmogram dataset. Mathematical Biosciences and Engineering 2022;20(1):975 View

Books/Policy Documents

  1. Schmitz-Grosz K. Digitalization in Healthcare. View