Next-Generation Volume Responsiveness Prediction System
Legal Citation
Summary of the Inventive Concept
A novel system leveraging neural networks to predict a patient's volume responsiveness, enabling personalized fluid management and optimized patient care.
Background and Problem Solved
The original patent disclosed a method for determining a parameter representative of a patient's volume responsiveness. However, this approach relied on oscillometric non-invasive pulse measurements, which may not provide accurate results in certain patient populations. The new inventive concept addresses these limitations by utilizing machine learning algorithms to analyze pulse signals and provide more accurate predictions.
Detailed Description of the Inventive Concept
The next-generation volume responsiveness prediction system comprises a neural network trained on a dataset of pulse signals and corresponding volume responsiveness indicators. This neural network can receive new pulse signals and output predicted volume responsiveness indicators, enabling healthcare providers to adjust fluid administration protocols accordingly. The system can be integrated into wearable devices, cloud-based platforms, or hospital systems, providing real-time monitoring and personalized care. The neural network can be fine-tuned for specific patient populations, ensuring accurate predictions and optimal fluid management.
Novelty and Inventive Step
The new inventive concept introduces the use of neural networks to predict volume responsiveness, which is a significant departure from the original patent's method. This approach provides a more accurate and personalized prediction, enabling healthcare providers to make informed decisions about fluid administration.
Alternative Embodiments and Variations
Alternative embodiments of the inventive concept include the use of different machine learning algorithms, such as decision trees or support vector machines, to analyze pulse signals. Additionally, the system could be integrated with other medical devices, such as blood pressure monitors or cardiac output monitors, to provide a more comprehensive picture of a patient's hemodynamic status.
Potential Commercial Applications and Market
The next-generation volume responsiveness prediction system has significant commercial potential in the healthcare industry, particularly in critical care and anesthesia. The system could be marketed as a standalone device or integrated into existing hospital systems, providing a competitive advantage for healthcare providers and improving patient outcomes.
Section 103 Obviousness Analysis (PHOSITA)
Field of Art
Medical signal processing, physiological monitoring, and machine learning applied to patient hemodynamic assessment, with expertise in signal analysis, neural network design, and clinical parameter prediction
Person of Ordinary Skill (PHOSITA) Profile
A biomedical engineer or clinical data scientist with advanced training in signal processing, machine learning techniques, and medical device development, possessing knowledge of neural networks, pulse signal analysis, and predictive medical technologies
Obviousness Rationale
A PHOSITA would recognize that applying neural network techniques to the source patent's pulse signal analysis represents a predictable extension of existing medical signal processing methods. The fundamental approach of analyzing patient pulse signals for volume responsiveness remains consistent, with the neural network serving as an advanced computational technique for pattern recognition and prediction. The core technical problem of extracting meaningful volume responsiveness indicators is directly addressed through an alternative computational approach that offers enhanced predictive capabilities.
Obvious Combinations & Variations
Original Patent Information
| Patent Number | US 11,857,302 |
|---|---|
| Title | Method, logic unit and system for determining a parameter representative for the patient's volume responsiveness |
| Assignee(s) | PHILIPS MEDIZIN SYSTEME BÖBLINGEN GMBH |