Blood Pressure Pulse Waveform Analysis for Preeclampsia Risk Screening
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Solution Overview
Problem
Current methods for detecting preeclampsia, such as Doppler ultrasound and the Fetal Medicine Foundation's competing-risks model, are costly and require specialized training, making them inaccessible in low-resource settings, limiting their effectiveness in low- to middle-income countries.
Innovation Solution
A method and system using blood pressure pulse waveforms to predict uterine artery pulsatility index (UA-PI) by analyzing shape features and maternal factors, leveraging statistical shape modeling and machine learning to assess preeclampsia risk without the need for expensive equipment or specialized personnel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Doppler ultrasound is used to measure uterine artery pulsatility index, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent creates a simplified copy of the ultrasound measurement system using blood pressure waveforms. Instead of directly measuring uterine artery blood flow with Doppler ultrasound, the system captures peripheral blood pressure waveforms and uses machine learning models to predict UA-PI values, creating a functional equivalent that is much simpler and cheaper to implement
Solution Approach 2:
The patent replaces the mechanical/optical Doppler ultrasound system with a computational approach using blood pressure waveforms and machine learning algorithms. The physical measurement system is substituted with a data processing system that predicts the same clinical parameter through mathematical modeling
2Measurement precision
If specialized training is required for preeclampsia detection, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The system performs automated risk assessment without requiring specialized operator skills. The machine learning model automatically processes blood pressure waveform data and generates preeclampsia risk predictions, eliminating the need for trained personnel to interpret complex ultrasound images or perform sophisticated measurements
Solution Approach 2:
The patent transforms the measurement approach from requiring skilled interpretation of multiple complex parameters to a simplified system that processes readily available blood pressure waveform parameters through automated algorithms, making the procedure accessible to non-specialists
3Measurement precision
If costly equipment is used for preeclampsia screening, then measurement precision is improved, but accessibility in low-resource settings deteriorates
Solution Approach 1:
The patent replaces expensive, durable ultrasound equipment with inexpensive, disposable blood pressure monitoring devices. The system uses standard blood pressure waveform data that can be obtained from low-cost devices, making the screening method economically viable for resource-limited settings while maintaining adequate measurement precision
Data Source
AI summary
A method for assessing the risk of preeclampsia in a pregnant subject is provided. The method can comprise: obtaining at least one blood pressure pulse waveform from at least one arterial site of the subject; determining a risk of preeclampsia in the subject, based at least in part on the at least one blood pressure pulse waveform; and generating an output indicative of the determined risk.