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Distributed Precision Stroke Care: Artificial Intelligence-Driven Stroke Management Using Multimodal Sensor Data

2025/10/22 by Aline F. Pedroso, Aline F Pedroso, Lee H. Schwamm +1
Medicine · #Acute Ischemic Stroke Management #Stroke Rehabilitation and Recovery #Cerebrovascular and Carotid Artery Diseases

paper · doi:10.1161/strokeaha.125.050447

Abstract

Delays in stroke diagnosis contribute to long-term disability. Many patients still face barriers to effective risk factor management, timely detection, and access to poststroke rehabilitation. The emergence of artificial intelligence-enabled, consumer-facing health technologies offers a transformative opportunity to address these gaps across the stroke care continuum. This review examines the evolving role of artificial intelligence-powered devices, including smartwatches, smartphones, wearable sensors, and ambient home-based technologies, in enabling precision stroke care. For stroke prevention, these tools facilitate scalable monitoring of cardiometabolic and stroke-specific risk factors. For early detection, artificial intelligence algorithms applied to multimodal sensor data can identify subtle neurological impairments and support real-time triage. In recovery, artificial intelligence-enhanced remote monitoring and virtual supervision offer scalable models for delivering personalized rehabilitation outside of specialized centers. Although most of these innovations remain in early development, they signal a paradigm shift toward accessible, individualized, and data-driven stroke prevention and management.

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