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Predicting viral respiratory tract infections using wearable biosensor monitoring during 3-minute constant rate stair stepping tests

BackgroundViral Respiratory Tract Infections (VRTIs) are a major public health threat. Early detection and preventive measures are key to controlling their spread. Current machine learning approaches often depend on symptom onset, costly equipment, trained personnel, and slow results. This study aim...

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Автори: Oussama Jlassi, Amir Hadid, Emily G. McDonald, Qianggang Ding, Christopher Phillipp, Audrey Trottier, Matthew P. Cheng, Jesse Papenburg, Michael Libman, Dennis Jensen, Philippe C. Dixon
Формат: Artigo
Мова:Inglês
Опубліковано: Frontiers Media S.A. 2026-02-01
Серія:Frontiers in Sensors
Предмети:
3-min constant rate stair stepping test
early detection
heart rate variability
machine learning
physiological markers
viral respiratory tract infections
Онлайн доступ:https://www.frontiersin.org/articles/10.3389/fsens.2026.1736869/full
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