Smartwatch App Accurately Measures Social Interactions in Stroke Patients, Potentially Aiding Recovery

A smartwatch application that measures social interactions among hospitalized stroke survivors may enable new treatments to preserve or enhance 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 SocialBit app uses a machine learning algorithm to detect social interactions through sounds in the environment, and this technology was able to measure how much social interaction occurred among stroke survivors in hospital settings with 94% accuracy compared to human observers.

Researchers developed SocialBit, which is compatible with Android smartwatches and can identify social interactions in both people with and without neurological conditions. According to the American Stroke Association, the loss or change in speech and language profoundly alters the social life of stroke survivors, yet research has shown that socializing is one of the best ways to maximize recovery. Study lead author Amar Dhand noted that previous research has demonstrated that stroke survivors who are socially isolated or have a smaller circle of friends and family have worse physical outcomes at 3 and 6 months after a stroke.

The study involved 153 adults hospitalized for ischemic stroke who wore a smartwatch with the SocialBit app in their hospital rooms between 9 a.m. and 5 p.m. daily for up to 8 days. The app logged socialization time according to acoustic patterns from the participant and/or another person talking, indicating social engagement. During the same timeframe, research team members watched livestream video of participants and logged minute-by-minute social interactions for comparison.

Key findings showed that SocialBit maintained 93% accuracy in patients with aphasia, and its performance remained consistent despite TV noise, side conversations, different environments, and across various Android smartwatch models. Participants who had more severe strokes had less social interaction, with about a 1% drop in total social interaction minutes for each 1-point increase on the NIH Stroke Scale. Dhand expressed surprise at how well the app performed for people with aphasia, noting that using SocialBit to capture sounds instead of words to protect privacy ended up being helpful for people with limited language skills.

The SocialBit app may help people recover from brain injuries by supporting therapies like speech, occupational, and exercise therapy. Future research could use SocialBit to measure how many people are at risk for social isolation while in the hospital and after they leave, and explore how this isolation relates to depression and other mental health changes that can happen after a stroke. Researchers also suggest the app could help with other brain injuries and in healthy aging to maintain and improve brain health over time.

Cheryl Bushnell, chair of the American Heart Association Stroke Council and chair of the writing group for the Association's 2024 Guideline for the Primary Prevention of Stroke, commented that the research is fascinating in its capture of social interactions, noting multiple interesting ways this app could be used in future studies, including measures of quality of hospital care and social interactions at rehabilitation facilities and nursing homes. One limitation of the study was that detailed evaluations of social interactions were only tested in hospital or rehabilitation settings.

Social interaction is known to support brain health and recovery after neurological injury, so this technology could support strategies focused on strengthening social ties, which may lead to improved physical recovery and quality of life, even among stroke survivors with language difficulties. According to the American Heart Association's 2026 Heart Disease and Stroke Statistics, stroke is now the fourth leading cause of death in the United States, making innovations in recovery support particularly significant.