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Page 2 of 15 Zhao et al. Soft Sci. 2026, 6, 4

With a customized electronic circuit and an application terminal, the on-mask intelligent system provides immediate
feedback for adaptive oxygen regulation. This capability is of paramount importance for improving
oxygen-management efficiency and safeguarding the lives of personnel operating under extreme conditions.

INTRODUCTION
Respiratory rhythm serves as a critical physiological barometer for homeostatic regulation to internal and
external perturbations . In extreme settings such as high altitude, deep sea, and industrial environments,
[1,2]
variations in ambient pressure, gas composition, or individual physiological constraints induce significant
fluctuations in breathing rate, ventilation volume, and rhythm, which in severe cases may affect life safety .
[3]
Real-time monitoring coupled with external oxygen supplementation is therefore essential to maintain vital
signs such as arterial oxygen saturation. Fighter pilots represent the most stringent example of this
requirement during maneuvers, generating extremely high G-forces . Oxygen delivery must precisely match
[4]
instantaneous metabolic demand to prevent gravity-induced loss of consciousness from insufficient oxygen
partial pressure or pulmonary and central nervous system toxicity arising from over-oxygenation . Thus, it
[5]
is imperative to develop a highly sensitive sensor system capable of capturing and identifying respiratory
dynamics in real-time, while issuing early warnings upon detection of abnormal patterns .
[6-8]
Wearable respiratory sensing technology has emerged as a continuous, noninvasive approach for monitoring
respiratory dynamics [9-13] . Currently, strain sensors with inherent sensitivity and form-factor constraints have
been deployed, which also necessitate tight adhesion or binding to the abdominal [14-16] , thoracic [17,18] ,
cervical , or facial skin [20,21] . During multiaxial acceleration in fighter operations, contact-based monitoring
[19]
often suffers from signal drift, classification errors, and discomfort from unstable contact [22,23] . Thus,
non-contact approaches such as humidity sensors that measure exhaled moisture are employed to monitor
respiratory rhythm [24-29] . However, slow response and recovery rates, along with signal degradation caused by
moisture accumulation, make these devices unsuitable for real-time, high-precision monitoring in extreme
environments [30,31] . In contrast, triboelectric sensors offer high sensitivity, lightweight structure, and excellent
robustness, enabling accurate capture of respiratory airflow variations under non-contact conditions [32-37] .
Inevitably, excessive sensitivity also amplifies environmental vibrations and motion artifacts . Moreover,
[38]
these respiratory monitoring paradigms mostly focus on sensor design without considering the electronic
circuit hardware support and precise algorithm development, thus making it difficult for them to truly adapt
to extreme operational settings. Therefore, the integration of tailored signal-processing algorithms with
hardware systems is required to suppress interference, extract key respiratory features, and provide real-time
feedback .
[39]
In this context, we propose a machine learning-enhanced on-mask respiratory electronic system integrated
with a proprietary algorithm and application terminal, enabling real-time, continuous, and accurate
respiratory dynamics monitoring. Specifically, low-pressure plasma treatment creates nanoscale roughness
and surface modification on the triboelectric fibers, increasing their contact area and boosting output voltage
by 420%. The optimized sensor exhibits a 96 ms response time and 2.02 V·kPa sensitivity. Moreover, the
-1
sensor maintains signal stability for 5,000 consecutive excitation cycles, and the output amplitude remains
above 95% after 90 days of exposure. Leveraging machine-learning algorithms, the system classifies
respiratory patterns with 97.2% accuracy while intelligently filtering pseudo-respiration artifacts and
providing real-time warnings.