Personalized Cardiac Therapy using AI-Driven Heart Position State Analysis

The inventive concept discloses a next-generation cardiac sensing and therapy system that leverages AI-driven heart position state analysis to deliver personalized therapy to patients, revolutionizing the field of cardiac care.

The original patent addresses cardiac sensing and therapy delivery by medical device systems. However, it is limited to using fixed parameters and lacks real-time adaptability to changing patient heart position states. The new inventive concept solves this problem by integrating wearable sensor data, machine learning algorithms, and implantable micro-devices to provide dynamic and personalized cardiac therapy.

The system comprises a wearable device that tracks patient heart position states using non-invasive electroencephalography sensors and machine learning-based algorithms. The data is transmitted to a cloud-based platform, where it is analyzed using machine learning algorithms to identify trends and patterns. The platform provides personalized cardiac therapy recommendations to clinicians, who can adjust therapy parameters in real-time using a neural network trained to predict patient heart position states. The system can be further enhanced by incorporating a swarm of implantable micro-devices, each configured to sense cardiac electrical signals and deliver cardiac therapy in response to real-time heart position state data.

The new claims introduce the use of AI-driven heart position state analysis, wearable sensor data, and machine learning algorithms to deliver personalized cardiac therapy, which is a significant departure from the fixed parameters and limited adaptability of the original patent. The inventive concept's novelty lies in its ability to adapt to changing patient heart position states over time, providing a more effective and efficient cardiac care solution.

Alternative embodiments of the inventive concept could include using different types of wearable sensors, such as ECG or accelerometer sensors, or incorporating additional data sources, such as patient activity levels or sleep patterns. Variations could also include different machine learning algorithms or neural network architectures to improve the accuracy of heart position state predictions.

The inventive concept has significant commercial potential in the cardiac care industry, particularly in the areas of personalized medicine and remote patient monitoring. The system could be marketed to hospitals, clinics, and medical device manufacturers, with potential applications in cardiac rehabilitation, arrhythmia management, and cardiovascular disease prevention.