Samsung Research America's Digital Health Team has presented two AI foundation models designed to learn from wearable biosignals. The work focuses on data captured by smartwatches, including heart activity, sleep, and physical activity.
According to Artificial Intelligence News, these models are built to identify meaningful patterns in health data collected from wearable devices. The goal is to turn raw biosignal data into useful health insights for consumers.
Samsung's Connected Care Vision for Health Technology
The company discussed its Connected Care vision at the Health Forum during Galaxy Unpacked in July 2026. Samsung described a future of preventive, personalised, and connected care, supported by health technology and healthcare partnerships.
As reported by Samsung Newsroom, AI is being widely used to analyse biosignals measured by wearable devices such as smartwatches. By identifying meaningful patterns in health data, these models can support daily health monitoring.
How the AI Models Learn from Wearable Biosignals
The research team positions health foundation models as one component of new consumer health experiences. The models are designed to learn from the structure of biosignals themselves, which helps them understand the data more accurately.
According to Samsung Research, wearable photoplethysmography (PPG) has become one of the most widely available physiological signals in modern health devices. A wrist-worn optical sensor can capture pulse dynamics continuously and unobtrusively, making PPG attractive for daily health monitoring.
"This research is significant because it lays the technical groundwork for delivering health insights that are efficient, precise, and personalised." — Sharanya Desai, Head of Digital Health Algorithms at Samsung Research America
What This Means for Smartwatch Health Monitoring
The models use data from multiple biosignals to build a fuller picture of a person's health. This includes:
- Heart activity — tracking pulse and heart rhythm patterns
- Sleep — analysing sleep stages and quality
- Physical activity — understanding movement and exercise patterns
The approach combines PPG data with electrocardiography (ECG), which captures the heart's electrical activity with precise beat timing and morphology. Together, these signals provide a more complete view of cardiovascular health.
Our Take: A Step Toward Smarter Preventive Health
To put it plainly, this is a meaningful step forward for consumer health technology. Samsung is not just adding another fitness tracking feature — it is building the technical foundation for AI that can truly understand a person's health over time.
The focus on preventive and personalised care is the right direction. Instead of simply telling users how many steps they took, these models aim to detect patterns that could signal health issues before they become serious. That shift from reactive to preventive care is exactly what modern health technology needs.
The fact that Samsung is positioning these models as part of a broader Connected Care vision — working with healthcare partnerships — suggests this is a long-term strategy, not a one-off feature. For consumers, this could mean smarter, more useful health insights from the devices they already wear.
