AI-driven Volatile Organic Compound (VOC) gas sensors represent a non-invasive, cost-effective breakthrough for early lung cancer diagnosis — analyzing breath biomarkers with clinical-grade accuracy.
At SenseMind, we're at the prototype stage of developing advanced AI-driven VOC gas sensor technology for early lung cancer detection. Our interdisciplinary team is pioneering non-invasive breath analysis solutions that will transform healthcare diagnostics.
To save lives through early lung cancer detection using AI-driven VOC gas sensor technology that analyzes exhaled breath.
Expert biomedical engineers, nanotechnologists, and AI specialists pioneering breath-based diagnostics.
Developing cutting-edge electronic nose prototypes that push the boundaries of VOC gas sensing.
Constantly evolving our sensor technology to meet the changing needs of modern healthcare.
We are developing next-generation VOC gas sensors designed to detect volatile organic compounds in exhaled breath with exceptional sensitivity. Our prototype systems integrate AI algorithms with advanced nanomaterial-based gas sensors to enable earlier, more accurate, and completely non-invasive lung cancer diagnoses.
From gas sensor fabrication to AI-powered breath analysis, our integrated platform delivers complete VOC detection capabilities for early lung cancer diagnosis.
High-sensitivity detection of volatile organic compounds in exhaled breath linked to lung cancer, including ethylbenzene, toluene, and hexanal.
Proprietary nanomaterial-based gas sensors fabricated with precision for optimal VOC capture and signal transduction.
Detect lung cancer at its earliest stages when treatment is most effective, using non-invasive breath analysis.
Streamlined breath collection and analysis protocols designed for clinical and point-of-care settings.
Advanced machine learning algorithms analyze sensor response patterns to classify VOC profiles and generate diagnostic reports.
Seamless integration with laboratory information systems and electronic health records for efficient clinical workflows.
Our proprietary electronic nose platform leverages nanomaterial-based gas sensors and AI pattern recognition for unprecedented detection of volatile organic compounds in exhaled breath.
Array of cross-selective gas sensors that collectively fingerprint VOC profiles in exhaled breath.
Metal oxide and conducting polymer nanocomposites engineered for selective VOC adsorption.
Resistive, capacitive, and acoustic wave detection methods convert molecular binding into measurable signals.
Deep learning models classify multi-sensor response patterns to distinguish cancer-linked VOC signatures.
Ultra-trace detection of VOC biomarkers at clinically relevant concentrations.
Single exhalation sampling with results delivered in under 10 minutes.
A patient exhales into a single-use mouthpiece connected to the VOC sensor chamber. No blood draw or invasive procedure is required.
Exhaled volatile organic compounds adsorb onto functionalized nanomaterial sensing layers, triggering measurable changes in electrical resistance.
The multi-sensor array captures response patterns across all channels, digitizing the analog signals for analysis.
Machine learning algorithms analyze the sensor response pattern, comparing it against trained VOC profiles to generate a diagnostic report.
A group of interdisciplinary researchers specializing in nanotechnology, gas sensor fabrication, AI pattern recognition, and biomedical science — dedicated to transforming lung cancer detection through VOC breath analysis.
Interested in our VOC gas sensor technology or breath analysis research? Reach out to discuss collaboration opportunities.