An intelligent multi-parameter risk early warning system for critical patients

By collecting electrocardiogram signals and invasive arterial pressure signals, a matching cost matrix is ​​constructed to assess the cardiovascular coupling status, which solves the problem of early warning lag in existing technologies and realizes accurate assessment and early warning of the cardiovascular coupling status.

CN122123669BActive Publication Date: 2026-08-25SHANGHAI FIRST PEOPLES HOSPITAL
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Patent Information

Application Number
CN202610531715.2
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2026-04-21
Publication Date
2026-08-25
Estimated Expiration
2046-04-21

AI Technical Summary

Technical Problem

Current emergency and critical care technologies rely solely on absolute blood pressure values, which cannot identify early abnormalities in cardiovascular coupling, resulting in delayed warnings and an inability to capture early warning signals before circulatory collapse.

Method used

By collecting electrocardiogram (ECG) signals and invasive arterial pressure signals, ventricular electrical amplitude, pulse pressure difference, and electromechanical delay are extracted to construct a matching cost matrix. The cardiovascular coupling status is assessed based on the optimal matching relationship. The risk warning is then output by combining pulse pressure variability, waveform difference, and response inversion ratio for graded screening.

Benefits of technology

It achieves precise alignment between cardiac electrical excitation and vascular mechanical response, reduces individual differences and signal drift, significantly improves early abnormality identification capabilities, and can capture early warning signals.

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Abstract

The present application relates to the technical field of medical monitoring, in particular to an intelligent multi-parameter risk early warning system for critical patients. The system transforms ventricular electrical amplitude sequence and pulse pressure difference sequence in a preset sliding data window to determine relative electrical amplitude sequence and relative pulse pressure sequence. The pulse pressure variability is determined based on the pulse pressure difference sequence in the window. The reference conduction time is determined according to the electrical-mechanical delay sequence in the window. The matching cost matrix is constructed according to the reference conduction time, the relative electrical amplitude sequence and the relative pulse pressure sequence, and the optimal matching relationship is solved. The excitation-response data pair set is constructed according to the optimal matching relationship, and the waveform difference index is determined. The response reverse sequence ratio is determined according to the set. The pulse pressure variability, the waveform difference index and the response reverse sequence ratio are used for hierarchical screening to determine the physiological state and output the corresponding risk warning, thereby significantly improving the early cardiovascular abnormality recognition ability.
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