Artificial intelligence-enabled atrial fibrillation detection using smartwatches: current status and future...

Area of Science:

• Cardiology
• Digital Health
• Artificial Intelligence

Background:

• Atrial fibrillation (AF) poses significant risks for stroke and heart failure.
• AF is often asymptomatic and intermittent, complicating diagnosis and timely intervention.
• Early detection is crucial for stroke prevention and managing cardiac complications.

Purpose of the Study:

• To review the characteristics and diagnostic performance of AI-enabled smartwatch algorithms for AF detection.
• To evaluate the clinical utility and limitations of current smartwatch technology in AF screening.
• To discuss the future role of AI-powered smartwatches in the evolving landscape of healthcare.

Main Methods:

• Review of current literature on AI-enabled smartwatch algorithms for AF detection.
• Analysis of FDA-cleared commercial smartwatches and their AF detection capabilities.
• Discussion of diagnostic performance metrics and clinical value assessments.

Main Results:

• AI-enabled smartwatches are increasingly utilized for AF detection, offering potential cost-effectiveness and ease of use.
• These devices have gained regulatory clearance, indicating growing acceptance.
• The evolving technology presents both opportunities and challenges for clinical integration.

Conclusions:

• AI-powered smartwatches represent a significant advancement in the early detection of atrial fibrillation.
• Clinicians must understand these tools to effectively integrate them into patient care strategies.
• Further research is needed to fully establish the long-term clinical impact and optimize their use in stroke prevention.