Published on in Vol 4, No 1 (2016): Jan-Mar

Early Indication of Decompensated Heart Failure in Patients on Home-Telemonitoring: A Comparison of Prediction Algorithms Based on Daily Weight and Noninvasive Transthoracic Bio-impedance

Early Indication of Decompensated Heart Failure in Patients on Home-Telemonitoring: A Comparison of Prediction Algorithms Based on Daily Weight and Noninvasive Transthoracic Bio-impedance

Early Indication of Decompensated Heart Failure in Patients on Home-Telemonitoring: A Comparison of Prediction Algorithms Based on Daily Weight and Noninvasive Transthoracic Bio-impedance

Journals

  1. Daluwatte C, Yaghouby F, Scully C. A framework to characterize the performance of early warning index alarm systems for patient monitoring. MethodsX 2019;6:1660 View
  2. Cuba Gyllensten I, Crundall-Goode A, Aarts R, Goode K. Simulated case management of home telemonitoring to assess the impact of different alert algorithms on work-load and clinical decisions. BMC Medical Informatics and Decision Making 2017;17(1) View
  3. Darling C, Dovancescu S, Saczynski J, Riistama J, Sert Kuniyoshi F, Rock J, Meyer T, McManus D. Bioimpedance-Based Heart Failure Deterioration Prediction Using a Prototype Fluid Accumulation Vest-Mobile Phone Dyad: An Observational Study. JMIR Cardio 2017;1(1):e1 View
  4. Cuba-Gyllensten I, Gastelurrutia P, Bonomi A, Riistama J, Bayes-Genis A, Aarts R. A method to adapt thoracic impedance based on chest geometry and composition to assess congestion in heart failure patients. Medical Engineering & Physics 2016;38(6):538 View
  5. Larburu N, Artetxe A, Escolar V, Lozano A, Kerexeta J. Artificial Intelligence to Prevent Mobile Heart Failure Patients Decompensation in Real Time: Monitoring-Based Predictive Model. Mobile Information Systems 2018;2018:1 View
  6. Papavasileiou L, Santini L, Forleo G, Ammirati F, Santini M. Novel devices to monitor heart failure and minimize hospitalizations. Expert Review of Cardiovascular Therapy 2016;14(8):905 View
  7. Saporito S, Dovancescu S, Herold I, van den Bosch H, van Assen H, Aarts R, Korsten H, Mischi M. Comparison of cardiac magnetic resonance imaging and bio-impedance spectroscopy for the assessment of fluid displacement induced by external leg compression. Physiological Measurement 2017;38(1):15 View
  8. Pevnick J, Birkeland K, Zimmer R, Elad Y, Kedan I. Wearable technology for cardiology: An update and framework for the future. Trends in Cardiovascular Medicine 2018;28(2):144 View
  9. Singhal A, Cowie M. The Role of Wearables in Heart Failure. Current Heart Failure Reports 2020;17(4):125 View
  10. Bhatia A, Maddox T. Remote Patient Monitoring in Heart Failure: Factors for Clinical Efficacy. International Journal of Heart Failure 2021;3(1):31 View
  11. Iqbal S, Mahgoub I, Du E, Leavitt M, Asghar W. Advances in healthcare wearable devices. npj Flexible Electronics 2021;5(1) View
  12. Groenendaal W, Lee S, van Hoof C. Wearable Bioimpedance Monitoring: Viewpoint for Application in Chronic Conditions. JMIR Biomedical Engineering 2021;6(2):e22911 View
  13. Senarath S, Fernie G, Roshan Fekr A. Influential Factors in Remote Monitoring of Heart Failure Patients: A Review of the Literature and Direction for Future Research. Sensors 2021;21(11):3575 View
  14. Albuquerque de Almeida F, Corro Ramos I, Rutten-van Mölken M, Al M. Modeling Early Warning Systems: Construction and Validation of a Discrete Event Simulation Model for Heart Failure. Value in Health 2021 View