Andres Valdez
Pennsylvania State University, PA·Biomedical Engineering
Respiratory illnesses such as RSV (respiratory syncytial virus), influenza and COVID-19 are often caught late. By then they have already spread through crowded places like schools, airports and hospitals.
- Fields
Biomedical Engineering
Computer Science
Public Health & Epidemiology
- Topics
voice analysis
digital health
respiratory illness
- Grants
- 1 known grant, through Apr 2027
What they work on
- Assess the translation potential of a voice-based pre-screening tool for RSV, influenza and COVID-19 through I-Corps interviews and first-hand study of the healthcare industry.
- Develop machine learning algorithms that detect real-time changes from a user's own baseline voice, heart rate and temperature and relate them to clinically observed respiratory illness patterns.
- Enable secure, scalable deployment on smartphones, wearables and smart speakers using edge AI (on-device computing) and signal processing for continuous, passive monitoring.
More about the research
A voice can change subtly when a person falls ill, and phones, smartwatches and smart speakers already capture voice and body signals. The question is whether these everyday signals could flag an infection early.
Why it matters
Earlier warning of respiratory infections could let people stay home or seek care before illness worsens or spreads. This may matter most in schools, airports and hospitals. Passive screening through phones and wearables could cut unnecessary clinic visits, speed up triage and support community-wide tracking of RSV, influenza and COVID-19. This could ease the strain on health systems and lower costs.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Carol Espy-Wilson
University of Maryland, MD·Engineering
Extend a speech inversion tool, which already estimates tongue and lip movements from audio, to recover nasality and voicing by training neural networks on acoustic features.
Adam Lauring
University of Michigan, MI·Microbiology & Immunology
Test how viral shedding dynamics and coinfection with other respiratory pathogens relate to the risk of passing influenza to a household member, using data- and specimen-rich observational cohorts of human-to-human transmission.
Nirupam Roy
University of Maryland, MD·Computer Science·Early-career
Enable sensing of large-scale gestures and movements near walls, floors and tabletops using coded signal projection through passive acoustic micro-structures and an adaptive intermittent computing architecture for battery-free operation.
The school
Pennsylvania State University: 60 labs on PI Pages, $1.3B a year on research, 743 research doctorates a year.
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