Bioinspired Adaptive Artificial Cilia With Tunable Sensitivity and Dynamic Range for Airflow Monitoring in the Central Airway
ABSTRACT Airway stents are critical for maintaining airway patency in patients with central airway obstruction. However, mucus accumulation often causes stent clogging and respiratory distress. Existing monitoring approaches, such as computed tomography, provide only intermittent assessment and involve ionizing radiation, limiting their suitability for continuous monitoring. Here, inspired by the adaptive flow‐sensing behavior of biological cilia, we report a reconfigurable airflow sensor with tunable sensitivity and dynamic sensing range. The sensor incorporates a cantilever beam whose electrical resistance changes with airflow‐induced deformation, while an external magnetic field modulates its mechanical response. This magnetic reconfiguration enhances sensitivity at low airflow velocities while extending the sensing range at higher velocities to prevent signal saturation. The sensor is validated against commercial flow sensors and integrated into a sensory ring with wireless power transfer and real‐time communication, forming a smart airway stent for continuous airflow monitoring and detection of mucus‐induced obstruction. System‐level validation in tracheal phantoms and ex vivo ovine lungs demonstrates reliable assessment of airflow and stent patency under physiologically relevant conditions. This magnetically reconfigurable sensing platform provides a versatile strategy for adaptive airflow monitoring and may enable smart airway stents for continuous assessment and personalized management of airway obstruction.
Authors
- Xiaoguang Dong (ORCID: https://orcid.org/0000-0002-9150-4014)
- D. W. Wang (ORCID: https://orcid.org/0009-0005-2597-2978)
- Caitlin T. Demarest (ORCID: https://orcid.org/0000-0001-6948-1103)
- Yuxiao Zhou (ORCID: https://orcid.org/0000-0001-5143-8967)
- Shuda Dong (ORCID: https://orcid.org/0009-0005-0175-233X)
- Yusheng Wang (ORCID: https://orcid.org/0000-0002-9743-4942)
- Ruijian Ge
- Zhongming Lyu
- Fabien Maldonado (ORCID: https://orcid.org/0000-0002-6504-2063)
- Hanwen Fan
- Nicholas Strymish
Institutions
- Vanderbilt University (US)
- Vanderbilt Health (US)
- Vanderbilt University Medical Center (US)
- Texas A&M University (US)
Publication Details
- Journal
- Advanced Materials Technologies
- Published
- 2026-10-06
- DOI
- https://doi.org/10.1002/admt.71382
- Primary Topic
- Advanced Sensor and Energy Harvesting Materials
- Type
- article
- Field-Weighted Citation Impact
- 0.00