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The Analytical Scientist / Issues / 2025 / June / Facemask Sensor for Kidney Disease Diagnosis
Sensors News and Research

Facemask Sensor for Kidney Disease Diagnosis

Breath signatures analyzed using machine learning show promise in identifying renal dysfunction

06/20/2025 2 min read

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0625-101-AI-News-Facemask-Sensor-for-Kidney-Disease-Diagnosis_Teaser.png

A recent study in ACS Sensors reports that a new type of facemask can help identify chronic kidney disease (CKD) by analyzing compounds in a person’s breath. The facemask contains a set of small chemical sensors that respond to gases linked with kidney function.

The sensors, built into the inner layer of a filtering face piece mask, use a conductive polymer material combined with porphyrins – molecules sensitive to different breath chemicals. These sensors are especially responsive to ammonia and certain alcohols, which tend to change in concentration in people with kidney problems.

Researchers tested the device on 101 people, including 53 with CKD and 48 healthy individuals. Each person wore the mask and completed two short breathing exercises. The sensors recorded breath signals, which were analyzed using a method that captures patterns related to breathing rate and gas concentration.

Paired with a machine learning approach called linear discriminant analysis, the mask correctly identified CKD patients with 93 percent accuracy for positives and 87 percent for negatives. Additional analysis suggested that the sensors could also detect differences between early and late stages of kidney disease, although this part of the study was less conclusive.

The results show that breath analysis using facemasks could offer a low-cost, noninvasive way to help screen for or monitor CKD. Unlike standard diagnostic methods such as blood or urine tests, this system only requires a short breath sample and no laboratory processing.

“The implementation of this technology is expected to enhance the management of CKD patients by facilitating the timely identification of changes in disease progression,” said Sergio Bernardini and Annalisa Noce, coauthors of the study in the press release.

Although further refinement and larger trials are needed, the findings support the potential use of wearable sensor arrays in disease detection and monitoring. This could have particular utility in CKD, where early identification and tracking of disease progression are critical yet often limited by invasive or resource-intensive diagnostics.

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