WEARABLE HYDROGEL SENSOR – Dr. Amil Aligayev
Project title:
Wearable Dual-Mode SERS–Colorimetric Hydrogel Sensor with AI-Driven Analysis for Early Lung Cancer Detection
Abstract:
The project develops a wearable, non-invasive sensor for detecting lung cancer biomarkers in exhaled breath. Its hydrogel patch uses metal-organic frameworks(MOFs), including ZIF-8 and functionalized MOFs, to selectively capture and concentrate volatile organic compounds such as hexanal. Their high porosity and adjustable chemical properties enhance the sensor’s sensitivity and selectivity.The captured biomarkers are analysed using two complementary methods: SERS for sensitive molecular detection and a colorimetric reaction that produces a
visible colour change. This dual-mode approach improves reliability through cross-validation.
A convolutional neural network processes SERS spectra and colorimetric images, identifies biomarker patterns, and provides rapid diagnostic classification through a smartphone or computer. The final system will combine a wearable mask or patch, MOF-based sensing materials, and AI software to support fast, affordable, and accessible early lung cancer screening.
Funding body: Science4Business – Inkubator Rozwoju S4B
Duration: 18 months
Budget: 100,000 PLN




