A groundbreaking smartwatch app designed to monitor the social interactions of stroke survivors could pave the way for innovative treatments aimed at preserving and enhancing cognitive function, social engagement, and quality of life post-stroke. This development is set to be unveiled at the American Stroke Association’s International Stroke Conference 2026 in New Orleans, a premier event dedicated to advancing stroke and brain health science.
The app, known as SocialBit, was developed by researchers to be compatible with Android smartwatches. It utilizes machine learning to identify social interactions in individuals with and without neurological conditions. Unlike other devices that primarily focus on people without disabilities, SocialBit is tailored for stroke survivors and is currently available solely for research purposes.
Revolutionizing Stroke Recovery
According to the American Stroke Association, stroke survivors often experience significant changes in speech and language, which can drastically alter their social lives. Socializing, however, is recognized as one of the most effective ways to maximize recovery after a stroke.
Dr. Amar Dhand, the study’s lead author and an associate professor of neurology at Mass General Brigham in Boston, emphasized the importance of tracking social interactions. “My 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,” he stated. “Tracking human engagement is crucial, and social isolation can now be identified in real-world situations.”
“This may be addressed by notifying the patient, family members, caregivers, and health care professionals of social isolation.” – Amar Dhand, M.D., D.Phil.
Study Insights and Findings
The study involved 153 adults who were hospitalized for an ischemic stroke. Participants wore a smartwatch equipped with the SocialBit app during their hospital stay, logging socialization time based on acoustic patterns. The app’s accuracy was compared to human observers who monitored social interactions via livestream video.
Compared with human observers, SocialBit was 94% as accurate in recognizing social interactions. In patients with aphasia, SocialBit maintained an accuracy of 93%.
SocialBit’s performance remained consistent despite various environmental factors, such as TV noise and different settings, and across multiple Android smartwatch models. The study also found that participants with more severe strokes engaged in less social interaction, with a 1% decrease in social interaction minutes for each 1-point increase on the NIH Stroke Scale.
Potential for Broader Applications
The app’s ability to capture sounds instead of words to protect privacy proved advantageous for individuals with limited language skills. “I was surprised by how well the app performed for people with aphasia,” Dhand noted. The app’s potential extends beyond stroke recovery, as it could support therapies such as speech, occupational, and exercise therapy.
Future research could leverage SocialBit to assess the risk of social isolation among hospitalized patients and explore its connections to depression and mental health changes post-stroke. “We can also test if this app can help with other brain injuries and in healthy aging to keep and improve brain health over time,” Dhand added.
Implications for Healthcare
While the study’s evaluations were limited to hospital and rehabilitation settings, the app’s potential applications are vast. Dr. Cheryl Bushnell, chair of the American Heart Association Stroke Council, highlighted the app’s ability to capture social interactions and its implications for hospital care quality.
“This research is fascinating in its capture of social interactions, which I presume can distinguish between conversations from case managers, nurses, therapists, and the care team from non-hospital personnel.” – Cheryl Bushnell, M.D., M.H.S., FAHA
Bushnell, who was not involved in the study, suggested that the app could be used to measure the quality of care in hospitals and rehabilitation facilities. The app’s ability to distinguish between hospital and non-hospital personnel could also highlight the role of family and friends in a patient’s social interactions.
As the healthcare industry continues to explore innovative solutions for patient care, the SocialBit app represents a promising tool for enhancing the recovery and quality of life for stroke survivors. Further research and development could expand its use to other areas of brain health and aging.
