AI-Driven Real-Time Monitoring of Cardiovascular Conditions With Wearable Devices: Scoping Review
Robust, interdisciplinary research is needed to harness the full potential of AI-driven, real-time cardiovascular health management using wearable devices. This includes the development and validation of scalable solutions for continuous community-based deployment. Furthermore, real-world challenges such as participant compliance, hardware and connectivity constraints, and AI model optimization for real-time continuous monitoring must be carefully addressed.
Authors
- Milad Lankarany (ORCID: https://orcid.org/0000-0001-6571-2867)
- Cynthia Chui (ORCID: https://orcid.org/0009-0000-0216-148X)
- Shehroz S. Khan (ORCID: https://orcid.org/0000-0002-1195-4999)
- Ali Abedi (ORCID: https://orcid.org/0000-0002-7393-1362)
- Anshul Verma (ORCID: https://orcid.org/0000-0003-0843-8405)
- Jathushan Kaetheeswaran (ORCID: https://orcid.org/0009-0009-8792-9050)
- Dherya Jain (ORCID: https://orcid.org/0009-0006-0240-9709)
Institutions
- University Health Network (CA)
- University of Toronto (CA)
- Toronto Rehabilitation Institute (CA)
- American University of the Middle East (KW)
- Ontario Brain Institute (CA)
Publication Details
- Journal
- JMIR mhealth and uhealth
- Published
- 2025-09-12
- DOI
- https://doi.org/10.2196/73846
- Citations
- 3
- Primary Topic
- Cardiovascular Health and Risk Factors
- Type
- article
- Field-Weighted Citation Impact
- 4.16