Shock Probability Determination System Using Fuzzy Logic
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for differentiating between types of shock in patients are time-consuming and often lead to delayed or incorrect diagnoses due to the complexity of hemodynamic parameters and limited medical resources, particularly in emergency situations.
Innovation Solution
A system utilizing a hardware processor and executable software modules that determine the probability of shock types based on a combination of physiological and demographic parameters, employing fuzzy logic or neural networks to compare current values against normalized ranges, providing continuous monitoring and trend analysis for rapid differential diagnosis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive hemodynamic parameter measurement and clinical assessment are performed to differentiate shock types, then diagnostic accuracy is improved, but diagnosis time is significantly increased
Solution Approach 1:
The patent segments the comprehensive shock differentiation process into multiple independent probability calculations for different shock types (cardiogenic, hypovolemic, septic, anaphylactic). Each shock type is evaluated separately using specific hemodynamic parameter combinations, allowing parallel processing and faster overall diagnosis while maintaining comprehensive assessment accuracy.
Solution Approach 2:
The patent transforms the traditional qualitative clinical assessment into quantitative probability calculations. By converting hemodynamic parameters (cardiac output, stroke volume, systemic vascular resistance, etc.) into numerical probability scores for each shock type, the system enables rapid computational comparison and automated differentiation, significantly reducing diagnosis time while preserving accuracy.
2Reliability
If multiple hemodynamic parameters are monitored and analyzed to determine shock type, then diagnostic reliability is improved, but system complexity is increased
Solution Approach 1:
The patent divides the complex diagnostic system into modular probability calculation units, each dedicated to assessing a specific shock type. Each module independently processes relevant hemodynamic parameters and generates a probability score, making the overall complex system manageable through functional segmentation and parallel operation.
Solution Approach 2:
The patent creates a universal diagnostic framework that handles multiple shock types (cardiogenic, hypovolemic, septic, anaphylactic) using a common probabilistic approach. The same computational architecture and parameter processing methods are applied across all shock type assessments, reducing system complexity through methodological universality despite the diversity of shock conditions.
3Measurement precision
If traditional clinical assessment methods are used for shock differentiation, then diagnostic thoroughness is improved, but productivity is reduced
Solution Approach 1:
The patent replaces the manual mechanical process of clinical assessment with an automated computational system. Hemodynamic parameters are automatically collected, processed, and analyzed by computer algorithms that calculate shock type probabilities, eliminating the time-consuming manual evaluation process while maintaining or improving diagnostic thoroughness through consistent application of assessment criteria.
Solution Approach 2:
The patent enables continuous monitoring and real-time probability calculation for multiple shock types simultaneously. Rather than performing sequential assessments, the system continuously processes hemodynamic data and updates shock type probabilities in real-time, maximizing diagnostic productivity without sacrificing thoroughness through uninterrupted evaluation.
Data Source
AI summary
A shock probability determination system and method provides an output of probabilities for different types of shock based on input of selected patient demographic parameters and current clinical parameter values as well as normal ranges for each clinical parameter based on patient demographic data. The probability of different types of shock is determined based on comparison of current clinical parameter values of selected patient hemodynamic parameters to a normal range for each hemodynamic parameter. In one aspect, probabilities of cardiogenic shock, hypovolemic shock, septic shock, and anaphylactic shock are determined. In another aspect, a fluid status indicator is determined based on real-time probability of hypovolemic shock.