APPARATUS AND METHOD FOR MONITORING VITAL SIGNS AND PREDICTING CRITICAL ILLNESS

Smart overview of the Invention

The invention offers a comprehensive system for monitoring vital signs using a wearable device, such as a wristband or ring, equipped with sensors and integrated with a mobile or web-based platform. This system is designed to track, store, and analyze vital signs like heart rate, body temperature, and oxygen levels. By employing artificial intelligence (AI) and machine learning models, the system can predict potential critical illnesses, recommend preventive care, and deliver personalized health insights. This approach aims to enhance remote patient management and improve healthcare outcomes.

Technical Field

This disclosure relates to continuous monitoring systems for vital signs, emphasizing secure data storage and real-time abnormal sign alerts. The system integrates data from various sources such as Electronic Medical Records (EMR), personal devices, and payer information. It offers a holistic view of a patient's health status to healthcare providers, caregivers, and family members through AI-driven analysis and personalized health recommendations.

Background

Effective patient care relies on accurate vital sign measurements to facilitate timely medical interventions. Existing devices often operate independently and lack integration, leading to fragmented data collection and delayed responses to health issues. The invention addresses the need for an integrated system that continuously monitors a range of vital signs, securely stores data, and provides real-time alerts to authorized individuals. This integrated approach aims to prevent medical emergencies by enabling early detection of abnormalities.

System Components

• Sensors: Placed in a ring or wristband to measure vital signs.
• Motherboard: Processes data from sensors and communicates with the mobile platform.
• Mobile/Web Platform: Displays vital sign data, allows threshold customization, and sends alerts.
• AI & Machine Learning: Analyzes health data for predicting illness risks and suggesting preventive care.

Methodology

The system operates by regularly reading vitals through sensors connected to a motherboard via a cable. Data is transmitted to a mobile dashboard or web platform where it is processed and displayed. Users can input custom thresholds for alerts related to vital signs. The AI module compares collected data against predefined risk thresholds to predict potential health issues and recommend actions. Additionally, the system provides a personal assistant feature to help users manage their health proactively.