Maternal PPH Monitoring Using Multimodal Risk Prediction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current systems fail to comprehensively evaluate multiple risk factors for postpartum hemorrhage (PPH) in maternal patients, leading to delayed diagnosis and ineffective prevention strategies.
Innovation Solution
A patient monitoring system that integrates ultrasound, electromyography (EMG), cardiac measurements, and uterine health indicators, utilizing a machine learning model to predict PPH probability and severity, and generate a risk index, with the capability to alert caregivers and adjust monitoring frequency based on risk assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple monitoring parameters (ultrasound, EMG, cardiac measurements) are integrated to improve PPH prediction accuracy, then the measurement precision and reliability of PPH risk assessment is improved, but the device complexity increases
Solution Approach 1:
The patent combines multiple monitoring systems (ultrasound imaging, EMG sensors, cardiac monitoring) into a single integrated patient monitoring system. The processor receives and processes data from all these different sources simultaneously, merging their functions to comprehensively assess PPH risk through multiple physiological parameters including uterine activity, fetal status, and maternal cardiac function.
Solution Approach 2:
The monitoring system is designed to perform multiple functions: ultrasound imaging for uterine assessment, EMG for uterine muscle activity detection, cardiac monitoring for maternal vital signs, and risk index calculation. This multi-functional approach allows a single system to address various aspects of PPH risk assessment without requiring separate dedicated devices for each parameter.
2Reliability
If continuous monitoring is implemented to improve early detection capability, then the reliability of PPH prediction is improved, but the energy consumption and device complexity increase
Solution Approach 1:
The system performs monitoring and risk assessment at periodic intervals rather than continuously. The processor calculates the PPH risk index based on received data and compares it to thresholds at discrete time points, generating alerts when risk levels exceed predetermined criteria. This periodic assessment approach maintains detection reliability while reducing energy consumption compared to continuous real-time monitoring.
3Measurement precision
If a comprehensive risk index system is implemented to improve patient stratification, then the measurement precision of risk assessment is improved, but the device complexity and data processing requirements increase
Solution Approach 1:
The patent replaces complex manual assessment methods with automated electronic processing. The processor automatically receives monitoring data, calculates the PPH risk index by integrating multiple parameters, and compares results to predetermined thresholds. This substitution of automated computational processing for manual clinical assessment improves precision while managing complexity through algorithmic standardization.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Proactively identifies high-risk patients for PPH, enabling early intervention and prevention through continuous monitoring and uterine muscle stimulation, thereby reducing maternal mortality.
Implementation Method 1
a transducer array configured to be positioned on a maternal abdomen and sized to image an entire uterus without being repositioned or otherwise moved. The plurality of transducer elements are spread across a transducer area
Implementation Method 2
electromyography (EMG) data obtained during the measurement period from abdominal electrodes on the patient
Data Source
AI summary
A method and system for monitoring a patient for postpartum hemorrhage (PPH) is configured to receive PPH factor information for the patient, wherein the PPH factor information includes at least two of the following: ultrasound data generated based on one or more abdominal ultrasound images of the patient obtained in a measurement period, electromyography (EMG) data obtained during the measurement period from abdominal electrodes on the patient, cardiac measurement data obtained from the patient during the measurement period, and a uterine health indicator for the patient. The system and method are configured to process the PPH factor information to determine a PPH probability index indicating a probability that the patient will develop PPH and a PPH severity index predicting a severity of PPH, and generate a PPH risk index for the measurement period based on the PPH probability index and the PPH severity index.