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Related Experiment Video

Updated: Jul 10, 2026

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
06:22

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections

Published on: September 19, 2025

Biodegradable Smart Face Mask for Cough Acoustic Sensing.

Mohammad Javad Bathaei1, Ata Golparvar1, Sina Hashemi Zadeh2

  • 1Department of Microelectronics, Delft University of Technology, Delft 2628 CD, The Netherlands.

ACS Sensors
|July 9, 2026
PubMed
Summary

Green Cough Sense is a new biodegradable, battery-free smart mask using a passive microphone to detect cough acoustics. This sustainable device offers a zero-waste solution for pulmonology diagnostics.

Keywords:
biodegradable devicescough acousticsgreen fabricationplanar resonatorsmart mask

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Asthma Detection Research Based on Voice Signal Processing and Machine Learning
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Last Updated: Jul 10, 2026

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04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

Area of Science:

  • Pulmonology
  • Materials Science
  • Biomedical Engineering

Background:

  • Pulmonary diagnostics often rely on subjective acoustic assessments.
  • Existing smart masks may not be environmentally sustainable.
  • There is a need for eco-friendly, passive sensing technologies for respiratory health.

Purpose of the Study:

  • To introduce Green Cough Sense, a biodegradable, battery-free smart face mask for sensing cough acoustics.
  • To develop a sustainable manufacturing process for passive acoustic sensors.
  • To validate the performance and biodegradability of the smart mask.

Main Methods:

  • Fabrication of a 3x3 array of drum-like membranes with a patch antenna using biodegradable materials (cellulose acetate, PLA, zinc).
  • Integration of a passive microphone transducing acoustic vibrations into electromagnetic reflection coefficient shifts (|S11|).
  • Measurement using a vector network analyzer and validation through in vitro and in situ human participant testing.

Main Results:

  • Demonstrated absolute sensitivity of 0.045 μm/Hz and 0.13%/Pa under monotone excitation.
  • Successfully detected mild, moderate, and severe cough events in human participants.
  • Achieved over 90% weight loss after 100 days of industrial composting, confirming biodegradability.

Conclusions:

  • Green Cough Sense is a viable, eco-friendly smart mask for acoustic cough monitoring in pulmonology.
  • The developed green manufacturing process enables sustainable production of passive acoustic sensors.
  • The device supports a zero-waste strategy for respiratory health diagnostics.