SynthesisMedicine2026
AI-integrated smartwatch monitoring for early detection of stroke and hemorrhage: A systematic review.
Synthesis in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
6 authors.
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Abstract
backgroundEarly detection of cerebrovascular events (subarachnoid hemorrhage [SAH], ischemic stroke, intracranial hemorrhage [ICH]) is critical for timely intervention. Emerging smartwatches with multiple sensors and artificial intelligence (AI) algorithms offer potential for real-time detection of acute neurological events. We performed a systematic review (2010-2025) per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines to identify published studies on AI-enabled smartwatches for detecting SAH, ischemic stroke, and ICH.
methodsWe searched multiple databases from January 2010 through May 2025 using combinations of smartwatch OR wearable, stroke OR SAH OR ICH, and AI OR machine learning OR deep learning. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool for diagnostic accuracy studies.
resultsThe search yielded 3 eligible studies on ischemic stroke detection by wearable accelerometers with AI. The stroke studies (n = 3) used bilateral wrist/arm accelerometers to detect unilateral motor deficits. Deep learning models achieved high diagnostic accuracy (area under the receiver operating characteristic curve 0.95-0.99) for detecting acute stroke symptoms. One study reported a median detection time of 15 to 29 minutes after stroke onset, depending on the false alarm threshold. A feasibility trial (STROKE ALARM) using accelerometer bands and a smartphone app triggered frequent false alarms without observed strokes.
conclusionWearable technology with AI shows promise for ischemic stroke symptom detection, but there is a critical gap in SAH and ICH detection. Challenges include sensor accuracy, false alarms, and algorithm generalizability. We propose a conceptual multisensory model integrating heart rate (electrocardiogram/photoplethysmography), blood pressure surrogates, and motion data into an AI pipeline for future smartwatch systems, which can lead to the detection of stroke/SAH, might show promise in other brain pathologies.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.