Yingcheng Liu
Yingcheng Liu has 2 papers in the ChatPPG research atlas (2022) and 27 co-authors in the atlas. Main topics: parkinsons, rf-sensing, breathing, physiological-monitoring, gait, longitudinal-monitoring.
Papers
- Artificial Intelligence-Enabled Detection and Assessment of Parkinson's Disease using Nocturnal Breathing Signals2022 · Nature Medicine 2022
This Nature Medicine study built an AI model that detects Parkinson's disease and tracks its progression from breathing signals recorded during sleep. Evaluated on 7,671 people from several US hospitals and public datasets, it detected the disease with AUC 0.90 on held-out data and 0.85 on external data, and its severity estimates matched the MDS-UPDRS rating scale (R = 0.94). Breathing can be captured without contact at home from radio waves reflected off the body.
- Published: Nature Medicine, 2022
- Cohort: 7,671 individuals
- Signals: nocturnal breathing (incl. radio-wave sensing)
- Monitoring Gait at Home with Radio Waves in Parkinson's Disease: a Marker of Severity, Progression, and Medication Response2022 · Science Translational Medicine 2022
This Science Translational Medicine study tracked gait speed at home with a radio device that senses radio waves reflected off people's bodies. Fifty people with and without Parkinson's disease were monitored for up to a year, giving more than 200,000 gait speed measurements. Home gait speed correlated strongly with MDS-UPDRS scores, tracked progression more sensitively than the rating scale and captured responses to medication.
- Published: Science Translational Medicine, 2022
- Cohort: 50 participants, up to 1 year
- Sensing: in-home radio waves (contactless)