Dr. Dennis Jensen and colleagues developed the first wearable-based system that can predict early inflammation from viral infections—like the flu—before symptoms appear. Using data from common devices such as smart rings, watches, or shirts, their AI tool detected immune responses with nearly 90% accuracy.
In the study, 55 healthy adults wore three types of sensors for almost two weeks while receiving a mild flu vaccine. The devices tracked heart rate, temperature, breathing, sleep, and activity, generating over two billion data points. This information trained AI models to recognize subtle body changes linked to inflammation—often before people felt sick or tested positive. The wearable-based models outperformed symptom reporting, even detecting early immune responses in participants who had no symptoms at all, including cases of COVID-19.
The technology could help doctors and patients act earlier to prevent complications, especially for vulnerable groups like people with COPD. The research led to the creation of a Montreal startup, Sensifai Health Inc., which aims to bring this proactive health monitoring tool to market.
Read the Publication
Development of machine learning prediction models for systemic inflammatory response following controlled exposure to a live attenuated influenza vaccine in healthy adults using multimodal wearable biosensors in Canada: a single-centre, prospective controlled trial. Hadid A, McDonald EG, Ding Q, Phillipp C, Trottier A, Dixon PC, Jlassi O, Cheng MP, Papenburg J, Libman M, Jensen D. Lancet Digit Health. 2025 Jul 2:100886.
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