Smart mask tracks respiratory sounds for disease identification


Wednesday, 01 February, 2023


Smart mask tracks respiratory sounds for disease identification

Wearing face masks has been recognised as one of the most effective ways to prevent the spread of COVID-19 and other respiratory diseases, but the potential for smart masks to monitor human physiological signals is also being explored. A research team led by the City University of Hong Kong recently invented a mask, integrating an ultrathin soundwave sensor, which is capable of detecting the respiratory sounds of breathing, coughing and speaking.

Using machine-learning algorithms and a high-sensitivity soundwave sensor operable across a wide bandwidth, the smart mask has opened new avenues for the identification of respiratory diseases. The ultra-lightweight, wearable technology has been described in the journal Advanced Science.

“Many countries now believe that COVID-19 will soon become endemic,” said team member Professor Li Wenjung. “However, we must set aside optimism and be realistic about the likely levels of illness, disability and death associated with this disease in the coming years. It is important to remember that endemicity does not correspond to harmlessness.” Thus, he suggested that people should continue to be cautious about COVID-19 and use available and proven measures, including masks, to control the spread of the virus.

The smart mask developed by Li and his colleagues has a sponge-like structure as thin as 400 μm, fabricated with carbon nanotube and polydimethylsiloxane (CNT/PDMS) materials, using a novel modified sacrificial-release technique. The team’s ultrathin, lightweight sensor can be practically integrated and work effectively with both rigid masks and deformable non-woven fabric masks.

The flexible sensor can be used to detect human respiratory activity by integrating it with commercial masks. Image credit: City University of Hong Kong.

“This smart mask utilises our self-developed, high-sensitivity, wide-bandwidth flexible sensor that can detect and record daily human respiratory activity, such as breathing, coughing and speaking, for cloud data storage,” Li said.

The team recruited 31 people in order to collect their respiratory activity while they wore the smart mask, and the findings showed that the acoustic wave sensor was highly sensitive in measuring both static and dynamic pressure. Besides performing well in the static pressure range of 27.9 Pa to 2.5 kPa, the sensor also responded to high-frequency dynamic pressure generated by the human voice, ie, sound harmonic acoustic energy up to 4000 Hz. In addition, the sensor can sense air movement, including directional flow and vibration.

Illustration of the overall concept of the smart mask, which integrates an ultrathin nanocomposite soundwave sensor to detect various respiratory sounds of breathing, coughing and speaking. Image credit: City University of Hong Kong.

These findings suggest that the sensor could be used to detect human respiratory activity by integrating it with a commercial polycarbonate mask. It also demonstrated that the smart mask could detect and differentiate three common respiratory functions: breathing, coughing and speaking.

“Advanced artificial intelligence technology enables the integrated mask to recognise different coughing and breathing patterns automatically, indicating its potential use to diagnose respiratory-related diseases in the future,” said team member Professor Wang Jianping.

“Presently, researchers use commercial sensors to detect temperature changes and airflow to count the number of coughs, but they cannot capture important physiological information contained in the human voice, coughing and breathing. Our smart mask is sensitive to both subtle air pressure and high-frequency vibrations and can detect three phrases of coughing,” Li added. The speech-detection ability of the smart mask can also help resolve the sound attenuation problem caused by wearing masks.

The team aims to eventually develop real-time diagnostics algorithms for applications such as pneumoconiosis symptom assessment. Team member Dr Yu Xinge concluded, “As a potentially low-cost, daily smart wearable device, this new IoT smart mask will help personal and public health management of respiratory disease screening and diagnosis, especially in cities with a dense population.”

Top image caption: The smart mask is expected to help improve personal and public health. Image credit: City University of Hong Kong.

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