A Beetle-Inspired Condensation Interface for Efficient Exhaled Breath Condensate Collection in an Externally...

Area of Science:

• Biomimetic engineering
• Respiratory diagnostics
• Noninvasive sensing technologies

Background:

• Exhaled breath condensate (EBC) and gases are valuable noninvasive biomarkers for respiratory health.
• Current mask-based systems face challenges in efficient condensate collection and multichannel data acquisition.
• A need exists for integrated, practical devices for real-time respiratory monitoring.

Purpose of the Study:

• To develop a mask-based prototype for efficient EBC harvesting and simultaneous multichannel respiratory biomarker readout.
• To utilize a biomimetic condensation interface inspired by beetle structures for enhanced EBC collection.
• To integrate gas-phase (CO2, acetone) and ionic (pH) biomarker detection with temporal data fusion.

Main Methods:

• Designed a mask with a heterogeneous-wettability condensation interface featuring hydrophilic nucleation sites and a superhydrophobic background.
• Integrated an external module for real-time, time-aligned measurement of CO2, acetone, and EBC pH.
• Evaluated the device's performance in terms of EBC collection rate, environmental robustness, and stability.
• Conducted a pilot human study to assess temporal biomarker differences across various physiological states.

Main Results:

• The biomimetic surface demonstrated significantly higher EBC collection rates compared to control surfaces across various conditions.
• The integrated three-channel system showed good repeatability, environmental robustness, and long-term stability.
• Pilot human monitoring revealed state-associated temporal differences in respiratory biomarkers.

Conclusions:

• The developed mask-based prototype successfully integrates efficient biomimetic EBC collection with multichannel respiratory readout.
• This proof-of-concept demonstrates a promising approach for noninvasive respiratory assessment through temporal data fusion.
• Further validation is needed for clinical application, but the system shows potential for future diagnostic tools.