A smartwatch application that measures social interactions among hospitalized stroke survivors could enable new treatments to preserve cognition, social engagement, and quality of life after a stroke, according to preliminary research to be presented at the American Stroke Association’s International Stroke Conference 2026. The study, which has not yet been peer-reviewed, introduces SocialBit, a machine learning app compatible with Android smartwatches that identifies social interactions by analyzing acoustic patterns in the environment, focusing on sounds of human speech rather than specific words to protect privacy.
The importance of this development lies in the established link between social interaction and brain health recovery after neurological injury. According to the American Stroke Association, changes in speech and language profoundly alter the social lives of stroke survivors, yet socializing is considered one of the best ways to maximize recovery. Study lead author Amar Dhand, M.D., D.Phil., of Mass General Brigham, noted that his previous research demonstrated stroke survivors who are socially isolated have worse physical outcomes months after the event. "We created a tracker of social life customized for stroke survivors," Dhand said. "Tracking human engagement is crucial, and social isolation can now be identified in real-world situations."
In the study, 153 adults hospitalized for ischemic stroke wore a smartwatch with the SocialBit app in their rooms between 9 a.m. and 5 p.m. daily for up to eight days. The app logged socialization time based on acoustic patterns indicating conversation. Researchers simultaneously observed participants via livestream video to validate the data. The findings showed SocialBit was 94% as accurate as human observers in recognizing social interactions. Notably, it maintained 93% accuracy in patients with aphasia, a language disorder common after stroke. The app's performance remained consistent despite background noise, different environments, and across various smartwatch models.
The implications are significant for stroke care and recovery strategies. Participants with more severe strokes, as measured by the NIH Stroke Scale, had less social interaction. Dhand expressed surprise at how well the app performed for people with aphasia, suggesting it could support therapies like speech, occupational, and exercise therapy. The technology could help identify patients at risk for social isolation during and after hospitalization, potentially linking isolation to depression and other post-stroke mental health changes. Future research may explore its use for other brain injuries and in healthy aging to maintain brain health.
Cheryl Bushnell, M.D., M.H.S., FAHA, chair of the American Heart Association Stroke Council, who was not involved in the study, called the research "fascinating" and noted multiple potential applications. "There are multiple interesting ways this app could be used in future studies, including measures of quality of hospital care and social interactions at rehab facilities and nursing homes," said Bushnell, who also chaired the writing group for the Association’s 2024 Guideline for the Primary Prevention of Stroke. She highlighted considerations such as whether the app distinguishes between hospital personnel and visitors, which could affect interpretation.
The study has limitations, including that evaluations were only conducted in hospital or rehabilitation settings. SocialBit is currently available only for research. According to the American Heart Association, stroke is now the fourth leading cause of death in the U.S., as noted in the 2026 Heart Disease and Stroke Statistics. This context underscores the need for innovative tools to improve outcomes. The research abstract is available in the American Stroke Association International Stroke Conference 2026 Online Program Planner.
By providing an objective measure of social engagement, SocialBit represents a technological step toward addressing a critical, non-pharmacological aspect of stroke recovery. Its ability to function accurately even for patients with communication difficulties could help tailor interventions that strengthen social ties, potentially leading to improved physical recovery and quality of life. As Dhand suggested, the app may eventually extend beyond stroke to support brain health more broadly, marking a convergence of wearable technology and neurological care.
