Non-Invasive Remote Monitoring in Heart Failure: Towards Wearable Devices and Artificial Intelligence Solutions
Monitoring with non-wearable and wearable devices reduces hospitalizations by detecting early signs of deterioration and enhancing self-care behaviour. While the initial investment can be high, the long-term cost-effectiveness is supported by reduced hospitalisations. AI is increasingly integrated into monitoring systems, enhancing predictive accuracy and personalized care. Remote monitoring reduces mortality and hospitalisations in patients with HF, with benefits in cost-effectiveness, and the potential to optimize care delivery by integrating AI. Future research should focus on identifying monitoring strategies for specific HF populations, such as patients with advanced HF.
Authors
- Cristina B. Pizarro (ORCID: https://orcid.org/0009-0006-0279-8871)
- Pim van der Harst (ORCID: https://orcid.org/0000-0002-2713-686X)
- René van Es (ORCID: https://orcid.org/0000-0001-9950-4388)
- Mark J. Schuuring (ORCID: https://orcid.org/0000-0002-2843-1852)
- Marish I.F.J. Oerlemans (ORCID: https://orcid.org/0000-0003-3166-518X)
- Bas B.S. Schots (ORCID: https://orcid.org/0009-0009-0291-7940)
Institutions
- Heidelberg University (DE)
- Medisch Spectrum Twente (NL)
- University Hospital Heidelberg (DE)
- University Medical Center Utrecht (NL)
- Systems Analytics (United States) (US)
- ERN GUARD-Heart (NL)
- University of Twente (NL)
Publication Details
- Journal
- Current Heart Failure Reports
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1007/s11897-025-00725-w
- Citations
- 2
- Primary Topic
- Heart Failure Treatment and Management
- Type
- article
- Field-Weighted Citation Impact
- 2.78