ReviewAdvanced healthcare materials2026
Smart Face Masks as Wearable Respiratory Sensors: A Review of Sensor Technologies, Materials, and Future Directions.
Review in Advanced healthcare materials, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Smart Face Masks as Wearable Respiratory Sensors: A Review of Sensor Technologies, Materials, and Future Directions.Advanced healthcare materials · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Smart face masks are rapidly evolving into versatile wearable devices capable of simultaneously tracking a variety of physical and biochemical signals for both personal healthcare and environmental monitoring. This review focuses on respiration monitoring and highlights recent advances in materials, device architectures, and sensor design for mask-integrated platforms. We categorize current approaches into six sensor types, humidity, gas, temperature, pressure, strain, and triboelectric, and summarize their transduction principles, material/fabrication strategies, and representative demonstrations for quantifying respiratory metrics. Finally, we discuss key challenges for real-world use, including sensor cross-sensitivity, long-term stability, and user safety, noting that everyday activities like talking or head movement can affect measurements. We also highlight future opportunities in cost-effective manufacturing, modular designs, and AI-enabled data analysis to improve accuracy and reliability in respiratory monitoring.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.