Advanced Cardiovascular Risk Assessment through Foot-Mounted Photoplethysmography

A next-generation system for measuring blood flow in the foot, leveraging machine learning and neural networks to predict cardiovascular disease risk and provide personalized health recommendations.

The original patent addressed the need for measuring blood flow in the foot, particularly for diabetic patients. However, it had limitations in terms of predicting cardiovascular disease risk and providing actionable insights. The new inventive concept addresses these limitations by integrating advanced analytics and machine learning capabilities to provide a more comprehensive and proactive approach to cardiovascular health monitoring.

The new inventive concept consists of a wearable device or foot-mounted sensor array that captures photoplethysmography measurements from multiple light sources and photodetectors. These measurements are then analyzed using machine learning algorithms to identify patterns indicative of cardiovascular disease risk. The system can also include a cloud-based analytics platform that receives and analyzes data from the sensor array to provide personalized health recommendations. The wearable device or sensor array can be designed to be flexible and conformable to the shape of the foot, ensuring comfort and accuracy during prolonged use.

The new claims introduce the use of machine learning and neural networks to predict cardiovascular disease risk, which is a significant departure from the original patent's focus on measuring blood flow. The integration of advanced analytics and wearable technology enables a more proactive and personalized approach to cardiovascular health monitoring, making the new inventive concept novel and non-obvious compared to the original patent.

Alternative embodiments of the inventive concept could include using different types of sensors, such as electroencephalography (EEG) or electromyography (EMG), to capture additional physiological data. The system could also be adapted for use in other parts of the body, such as the wrist or chest. Furthermore, the machine learning algorithms could be trained on larger datasets to improve their accuracy and robustness.

The new inventive concept has significant commercial potential in the healthcare and wearable technology industries. It could be marketed as a proactive tool for cardiovascular health monitoring, particularly for high-risk populations such as diabetic patients. The system could also be integrated into existing healthcare infrastructure, such as electronic health records (EHRs) and telemedicine platforms, to provide a more comprehensive and connected approach to patient care.