MUMBAI, India, Aug. 31 -- Intellectual Property India has published a patent application (202641099791 A) filed by Sabah Afroze; Dr. Tamil Selvi; and Dr. Parisa Beham on August 18, 2026, for Process Of Ai-Enabled Portable Multi-Disease Diagnostic And Health Monitoring Device.
Inventors include Sabah Afroze; Dr. Tamil Selvi; and Dr. Parisa Beham.
The application for the patent was published on August 28, 2026, under issue no. 35/2026.
Abstract: The present invention relates to an AI-enabled portable multi-disease diagnostic and health monitoring device configured to perform rapid, non-invasive or minimally invasive health assessment using an integrated combination of physiological sensors, biochemical sensing modules, optical sensing components, signal-processing circuitry, and artificial intelligence- based analytical models. The device is designed to acquire multiple health parameters including, but not limited to, heart rate, blood oxygen saturation, body temperature, blood pressure, respiratory rate, glucose-related measurements, cardiac electrical activity, and selected biochemical or optical biomarkers. The acquired data are subjected to preprocessing, noise removal, feature extraction, normalization, and multimodal data fusion before being analyzed by one or more machine-learning or deep-learning models. The AI engine is configured to identify abnormal physiological patterns, estimate disease-related risk scores, classify potential health conditions, and provide personalized health-monitoring outputs. The device may support screening and monitoring of multiple disease conditions including cardiovascular disorders, diabetes-related abnormalities, respiratory disorders, infection-associated conditions, and other systemic health abnormalities depending upon the sensing modules incorporated. A microcontroller or embedded processor coordinates sensor acquisition, AI inference, data storage, user-interface functions, and wireless communication. The device can transmit diagnostic results and longitudinal health information to a mobile application, cloud platform, healthcare professional, or remote monitoring center. An adaptive learning mechanism may improve model performance using validated historical and newly acquired datasets while maintaining data security and privacy. The portable architecture enables point-of-care screening, home-based monitoring, rural healthcare applications, emergency assessment, preventive healthcare, and continuous or periodic health surveillance. The invention thereby provides a compact, intelligent, cost-effective, and scalable platform for preliminary multi- disease screening and personalized health monitoring
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