By Dave DeFusco
What if a tiny ring on your finger could tell when you鈥檙e stressed, predict your heart health and alert you to dangerous changes in your body鈥攁ll in real time? That鈥檚 the bold promise behind new research presented by a Katz School team that unveiled a 鈥渄igital twin鈥 healthcare framework powered by smart rings in London at the 2025 IEEE INFOCOM Conference, a top-ranked conference on networking in the research community.
The research, conducted by Ashikur Nobel, a Ph.D. student in Mathematics at the Katz School; Dr. Honggang Wang, chair of the Katz School鈥檚 Department of Graduate Computer Science and Engineering; and Dr. Hua Fang, professor of computer and information science at the University of Massachusetts Dartmouth and the Chan Medical School, received the only 2025 IEEE INFOCOM Best Poster Award.
鈥淭his project started with a simple idea,鈥 said Nobel. 鈥淐an we take the data collected from smart rings, combine it with our physical biomarkers, such as weight, blood pressure and cholesterol, and use it to build a virtual version of a person鈥檚 health鈥攁 鈥榙igital twin鈥 that can learn, adapt and even predict what鈥檚 coming next?鈥
Originally used in industries like aviation and manufacturing, a digital twin is a virtual model of a real system that is continuously updated with live data. In the context of healthcare, it means creating a virtual model of a person鈥檚 health using real-time data from wearable sensors, like those embedded in smart rings.
Smart rings like the Oura or Samsung Galaxy Ring are small, discreet and packed with powerful sensors that can track heart rate, blood oxygen levels, sleep patterns, physical movement, and more. But Nobel wanted to go further鈥攏ot just collect data but use it to understand and predict health in real time.
Their proposed framework connects a smart ring to a nearby device, like a smartphone, via Bluetooth, avoiding the need to constantly send sensitive health data to the cloud. That local processing approach makes it faster, more secure and better for user privacy.
鈥淭he ring collects raw data鈥攜our pulse, how much you鈥檙e moving, your oxygen levels,鈥 said Nobel. 鈥淲e process that data using AI models to spot trends and make predictions. For instance, we can detect if your stress is rising or if your oxygen levels drop unexpectedly. Because it鈥檚 a digital twin, it can keep monitoring and even fill in the gaps when the ring is off.鈥
This 鈥渇illing in the gaps鈥 is made possible by advanced AI models, particularly a type known as a Transformer model which is a widely used architecture across many applications, including tools like ChatGPT. These models can learn from patterns over time and predict future outcomes, such as the likelihood of abnormal heart rhythms or poor sleep quality.
鈥淟et鈥檚 say the ring goes into power-saving mode or is temporarily taken off,鈥 said Nobel. 鈥淭he digital twin doesn鈥檛 just stop working; it keeps going, using what it鈥檚 already learned to estimate how your body is doing.鈥
That continuous prediction could be vital in early warning systems for conditions like heart attacks, breathing issues or chronic stress-related illnesses. One of the standout features of the project is how clearly it can show your health data. The team designed user-friendly visual dashboards that translate complex biological signals into simple charts and alerts. Imagine opening an app and seeing not just your heart rate, but how it鈥檚 changed over time, how it correlates with your sleep and whether stress might be affecting it.
鈥淲e wanted to make the invisible visible,鈥 said Nobel. 鈥淭he digital twin can explain what's going on inside your body in a way that makes sense, not just to doctors but to everyday users.鈥
Traditional health apps often rely on the cloud for heavy data processing, which raises concerns about privacy and speed. Nobel鈥檚 framework keeps most of the work local鈥攐n your phone or wearable device鈥攅nsuring faster results and better protection for personal information. That鈥檚 a big deal, said Dr. Wang.
鈥淲e are in an era where personalized healthcare is possible, but only if we protect users鈥 trust,鈥 he said. 鈥淭his smart ring digital twin approach is not just innovative, it鈥檚 secure, efficient and scalable. It brings together mathematics, engineering and health science to put power back in the hands of individuals.鈥
Wang noted that this research lays the foundation for a future where wearable technology doesn鈥檛 just track, but truly understands, the user. While the current prototype focuses on two main types of data鈥攑ulse signals from the ring鈥檚 light-based sensors and motion data from its accelerometer鈥攖he team hopes to expand it with additional sensors for skin temperature, hydration and even mood.
Initial results have been promising. The team tested their models using self-collected and real-world datasets and found strong predictive performance. While traditional models, like Long Short-Term Memory (LSTM) networks, were used in early stages, the research has since advanced to more powerful Transformer-based AI models. But as Nobel emphasized, this is just the beginning.
鈥淲e鈥檝e shown the digital twin works in principle. Now we need to test it in clinical settings, on diverse populations and with more complex health conditions,鈥 he said. 鈥淥ur dream is to one day have a tiny ring that quietly watches over your health and warns you before a crisis happens.鈥
