This Cheap Disposable Sensor Turns a Face Mask Into a Kidney Disease Detection System
Initial testing shows promising accuracy for both diagnosing the presence and absence of chronic kidney disease.
Researchers from the University of Rome Tor Vergata have developed a disposable sensor designed to sniff out signs of chronic kidney disease — by simply being inserted into a face mask.
"The implementation of this technology is expected to enhance the management of CKD patients by facilitating the timely identification of changes in disease progression," say study co-authors Sergio Bernardini and Annalisa Noce of the team's creation, which has been shown to both detect signs of chronic kidney disease and even provide data for estimation of its progression in the body.
In chronic kidney disease, the kidneys — responsible for removing waste products from the bloodstream — no longer function correctly, an issue that affects an estimated 35 million Americans and could affect millions more who are presently undiagnosed. Looking for a way to test quickly, cheaply, and non-invasively, the researchers eschewed the normal blood or urine sampling process in order to detect signs from something else: the patient's breath.
A disposable sensor, built using silver electrodes coated with a conductive polymer modified with porphyrin molecules tailored to the detection of ammonia, ethanol, propanol, and acetone, all metabolic products associated with CKD, is inserted into an off-the-shelf face mask, which the patient then wears. As the patient breaths, the electrical resistance changes — and those changes can be turned into a diagnosis, courtesy of an Espressif ESP32 microcontroller housed in a 3D-printed case and logging to a microSD Card.
Tested on 100 individuals, half of whom had an existing CKD diagnosis, the prototype sensors correctly identified those with the disease (a true positive result) 93.3 percent ± 17 percent of the time and those without (a true negative result ) 86.7 percent ± 18 percent of the time. The data can also be used, the researchers suggest, to estimate the severity of the disease, though this will require further investigation to provide diagnostically useful results.
The team's work has been published in the journal ACS Sensors under open-access terms.
Freelance journalist, technical author, hacker, tinkerer, erstwhile sysadmin. For hire: freelance@halfacree.co.uk.