Intelligent Physiological Sensor System with Predictive Maintenance and Adaptive Measurement

A next-generation physiological sensor system that integrates machine learning, predictive maintenance, and adaptive measurement capabilities to provide more accurate, personalized, and reliable vital sign monitoring.

The original patent disclosed a system for monitoring the life of a physiological sensor, but it had limitations in terms of predicting sensor failure, optimizing sensor performance, and adapting to individual user physiology. The new inventive concept addresses these limitations by incorporating advanced technologies to ensure seamless and accurate vital sign monitoring.

The system comprises a machine learning module that analyzes usage patterns, environmental factors, and sensor performance data to predict the sensor's remaining lifespan. A notification module alerts the user when the sensor approaches end-of-life, enabling proactive replacement. The system also features a wearable device with a physiological sensor that incorporates a power harvesting module, capturing and converting ambient energy into electrical power. The sensor's firmware is periodically updated to optimize its performance and reduce wear and tear. Furthermore, the system includes a cloud-based platform for monitoring and analyzing physiological sensor data, identifying trends and anomalies, and providing personalized interventions based on the user's health profile. The physiological sensor itself is equipped with a built-in artificial intelligence module that adapts to the user's unique physiology, adjusting measurement parameters for more accurate and personalized readings.

The new inventive concept introduces a paradigm shift in physiological sensor technology by integrating machine learning, predictive maintenance, and adaptive measurement capabilities. The inventive step lies in the combination of these advanced technologies to provide a more reliable, accurate, and personalized vital sign monitoring system.

Alternative embodiments of the inventive concept could include variations in the machine learning algorithms, different types of power harvesting modules, and diverse cloud-based platform architectures. Additionally, the system could be adapted for use in various medical applications, such as critical care, surgical, or pediatric monitoring.

The intelligent physiological sensor system has significant commercial potential in the healthcare industry, particularly in the areas of remote patient monitoring, telemedicine, and personalized medicine. The system's predictive maintenance and adaptive measurement capabilities could reduce healthcare costs, improve patient outcomes, and enhance the overall quality of care.