MUMBAI, India, Sept. 14 -- Intellectual Property India has published a patent application (202641106654 A) filed by Ayain John; Dayananda Sagar Academy Of Technology And Management; Abhishree M; Gahana M N; and Ningamma Gogi on September 04, 2026, for Ai And Quantum Machine Learning-Based Health Risk Prediction Using Wearable Sensor Data.
Inventors include Ayain John; Dayananda Sagar Academy Of Technology And Management; Abhishree M; Gahana M N; and Ningamma Gogi.
The application for the patent was published on September 11, 2026, under issue no. 37/2026.
Abstract: The invention relates to an intelligent health-risk prediction system that integrates wearable sensor data, clinical parameters, Internet of Things (IoT) communication, data preprocessing, feature extraction, Artificial Intelligence (AI), and Quantum Machine Learning (QML). The system collects physiological and activity-related information from wearable sources including smartwatches, fitness trackers, heart-rate sensors and IoT sensors. The collected information may include heart rate, step count, sleep duration, activity level and calories burned. Clinical parameters including blood pressure, cholesterol, body mass index (BMI) and age are also incorporated. An ESP32 or Arduino based IoT gateway can collect and transmit the sensor information through Wi-Fi or Bluetooth to a computing unit. The data is cleaned, missing values are handled and the data is normalized before relevant features are extracted. The processed features are supplied to an AI and Quantum Machine Learning prediction module for health-risk classification. The resulting health-risk prediction is used to generate a preventive recommendation for the user. The invention provides an integrated framework for combining heterogeneous wearable and clinical information for health-risk prediction and preventive monitoring.
Disclaimer: Curated by HT Syndication.
