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FAQ: SocialBit Smartwatch App for Detecting Social Interactions After Stroke
TL;DR
The SocialBit smartwatch app gives healthcare providers a competitive edge by accurately tracking stroke patients' social interactions to optimize recovery strategies and improve outcomes.
SocialBit uses machine learning algorithms on Android smartwatches to detect acoustic patterns of human speech, achieving 93-94% accuracy in measuring social interactions even with background noise.
This technology helps reduce social isolation among stroke survivors, potentially improving their recovery, quality of life, and mental health through enhanced social engagement monitoring.
A smartwatch app can now detect social interactions through sound patterns, working even for stroke patients with language difficulties while protecting privacy.
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SocialBit is a machine learning app compatible with Android smartwatches that identifies social interactions by detecting acoustic patterns from people talking, specifically designed to track social engagement among stroke survivors.
Research shows that socializing is one of the best ways to maximize recovery after stroke, and stroke survivors who are socially isolated or have smaller social circles have worse physical outcomes at 3 and 6 months post-stroke.
The app uses a machine learning algorithm to detect social interactions through sounds in the environment, logging socialization time based on acoustic patterns from the participant and/or another person talking.
The study was led by Amar Dhand, M.D., D.Phil., an associate professor of neurology at Mass General Brigham, and involved 153 adults hospitalized for ischemic stroke who wore smartwatches with the SocialBit app.
The preliminary study will be presented at the American Stroke Association's International Stroke Conference 2026 in New Orleans, Feb. 4-6, 2026, with findings embargoed until January 29, 2026.
Unlike other devices focused on people without disabilities, SocialBit is specifically customized for stroke survivors, including those with communication difficulties like dysarthria (speech changes) and aphasia (language impairment).
SocialBit could enable new treatments to preserve or enhance cognition, social engagement, and quality of life after stroke by identifying social isolation in real-world situations and notifying patients, family, caregivers, and healthcare professionals.
No, SocialBit is currently only available for use in research projects and not publicly available.
The study is a research abstract presented at a scientific meeting, not yet peer-reviewed, and findings are considered preliminary until published as full manuscripts in a peer-reviewed scientific journal.
The American Stroke Association provides information about stroke effects including communication and aphasia at their website: https://www.stroke.org/en/about-stroke/effects-of-stroke/communication-and-aphasia/stroke-and-aphasia/socializing-with-aphasia.
Curated from NewMediaWire
