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CN-121096659-B - Cerebral ischemia injury regulation and control analysis system

CN121096659BCN 121096659 BCN121096659 BCN 121096659BCN-121096659-B

Abstract

The invention relates to the technical field of medical health care informatics, and discloses a cerebral ischemia injury regulation and control analysis system, which comprises: using a pressure fluctuation component generated by endogenous physiological activities in the arterial pressure signal as a detection signal, and analyzing response characteristics of the intracranial pressure signal to the detection signal; when the strength of the detection signal is insufficient, the respiratory activity signal is determined as an alternative detection signal for continuous analysis, a data processing mode different from the traditional static threshold monitoring is established, and an evaluation dimension directly reflecting the intrinsic adjustment capability of the system is established by analyzing the dynamic response relation among core parameters, so that the consumption state of the functional reserve can be revealed in advance before the absolute value of the conventional physiological parameters such as intracranial pressure and the like is abnormal, and further, the time is gained for clinical intervention.

Inventors

  • CHEN XIUPING
  • XIONG JUN
  • LIU LINGLING
  • XIONG YUN

Assignees

  • 南昌大学第一附属医院

Dates

Publication Date
20260505
Application Date
20251111

Claims (9)

  1. 1. A brain ischemia injury control analysis system, comprising: A signal acquisition module configured to synchronously acquire an average arterial pressure time-series signal and an intracranial pressure time-series signal; A probe signal extraction module configured to extract pressure fluctuations in a frequency range of 0.05Hz to 0.15Hz generated by the vessel autonomous regulatory activity by performing a band-pass filtering process on the average arterial pressure time-series signal, and define the pressure fluctuations as an endogenous probe signal; The detection source determining module is configured to monitor signal energy of an endogenous detection signal, determine the endogenous detection signal as a current detection signal if the signal energy is not continuously lower than an activation threshold, and determine a respiratory cycle signal extracted from synchronously acquired respiratory activity signals as the current detection signal if the signal energy is continuously lower than the activation threshold; The response characteristic calculation module is configured to calculate the phase delay and the amplitude gain of the intracranial pressure response based on the determined current detection signal and the intracranial pressure time series signal corresponding to the current detection signal, wherein when the endogenous detection signal is the current detection signal, a short time window is set by taking the time point of each peak and each trough of the endogenous detection signal as the center, and the calculation is performed based on the intracranial pressure time series signal corresponding to the endogenous detection signal and the short time window; An evaluation index generation module is configured to generate an evaluation index representing a brain function reserve state based on the determined current detection signal and an intracranial pressure time-series signal corresponding to the current detection signal.
  2. 2. The brain ischemia injury control analysis system of claim 1, wherein the activation threshold is predetermined based on a statistical energy distribution of endogenous probe signals in the historical baseline mean arterial pressure time series signal.
  3. 3. The system of claim 1, wherein the signal acquisition module is further configured to acquire synchronized electrical brain time series signals, calculate sample entropy of the electrical brain time series signals over a short time window or over a period corresponding to a respiratory cycle signal, and generate the evaluation index by combining the synchronization metrics of the phase delay, the amplitude gain, and the sample entropy using a fixed linear combination model.
  4. 4. The brain ischemia injury control analysis system according to claim 2, wherein the evaluation index is Is generated by the following rules: , wherein, In order to evaluate the index of the present invention, For the normalized phase delay, For the normalized amplitude gain, For the normalized measure of synchronicity, 、 And (3) with And a linear weight coefficient which is preset for the prediction contribution degree of each input characteristic in the historical sample data and is 1 in sum.
  5. 5. The system of claim 1, wherein the system is further configured to obtain an airway pressure waveform synchronized with the respiratory cycle signal generated by the respiratory device after determining the respiratory cycle signal as the current detection signal and using the airway pressure waveform as a template signal, and perform a matched filtering process on the intracranial pressure time series signal using the template signal to obtain an enhanced intracranial pressure response signal, and calculate a phase delay and an amplitude gain using the enhanced intracranial pressure response signal.
  6. 6. The system for cerebral ischemia injury control analysis of claim 3, further comprising detecting whether a predetermined artifact characteristic generated by a non-physiological physical disturbance exists therein by analyzing the electroencephalogram time series signal, and suspending the operation of the evaluation index generation module during a period in which the artifact characteristic is detected.
  7. 7. The system of claim 6, further configured to classify the detected artifact characteristics into one of an impulsive artifact and a rhythmic artifact class, select an impulse response template subtraction model if the artifact class is an impulsive artifact, select an adaptive notch model if the artifact class is a rhythmic artifact, process the mean arterial pressure time series signal and the intracranial pressure time series signal with the selected models to obtain corrected signals, and calculate a response characteristic calculation module based on the corrected signals.
  8. 8. The cerebral ischemia injury regulation and control analysis system according to claim 1, further comprising calculating a current mean arterial pressure level by performing low-pass filtering processing on the mean arterial pressure time series signal, selecting a matched evaluation model parameter set from a plurality of preset evaluation model parameter sets corresponding to three arterial pressure level intervals of hypotension, normal blood pressure and hypertension respectively based on the mean arterial pressure level for use by the evaluation index generation module, wherein the plurality of preset evaluation model parameter sets are obtained by independently training and calibrating by using historical data sets corresponding to arterial pressure level intervals respectively.
  9. 9. The system of claim 1, further comprising obtaining a cerebral perfusion pressure indicator by calculating a difference between the mean arterial pressure time series signal and the intracranial pressure time series signal, and combining the assessment indicator and the cerebral perfusion pressure indicator according to a predetermined arbitration rule, wherein the arbitration rule specifies that the final regulation analysis result is determined to be in danger when the assessment indicator indicates that the brain function reserve status is good and the cerebral perfusion pressure indicator is below a survival threshold of 60 mmHg.

Description

Cerebral ischemia injury regulation and control analysis system Technical Field The invention relates to a cerebral ischemia injury regulation and control analysis system, and belongs to the technical field of medical care informatics. Background Currently, in nerve intensive care, a common technical strategy is to continuously monitor core physiological parameters of a patient, such as intracranial pressure and mean arterial pressure, by using sensors, and compare the monitored values with preset safety thresholds, and the application of healthcare informatics in this field is mainly implemented by integrating these independent data streams into a unified monitoring platform for clinical observation and decision. However, when this monitoring strategy is applied to evaluate the actual functional reserves of the brain of a patient in the apparent steady state of physiological parameters, the limitation of information acquisition of the brain will affect the subsequent clinical judgment, and in the intensive care process, each physiological parameter of a patient may be in a normal range, but the steady data of this surface may correspond to two distinct functional states of the brain with perfect or imminent failure in autonomous regulation function, and the existing monitoring strategy can only reflect what state the system is currently, but lacks the technical dimension of how much disturbance the evaluation system can bear, so that the initiation of clinical intervention measures often needs to wait for the absolute value of a certain parameter to be triggered after abnormality occurs. To deal with this problem, the direct improvement idea is to increase the accuracy of signal processing or introduce a more complex statistical model, but such methods usually aim at smoothing the signal to filter out fluctuations and obtain a more stable mean value, and this processing method instead discards the information about the system dynamic response capability contained in the inherent variability of the signal, and specifically, the data processing method in the prior art mainly has the following limitations that 1, its analysis model is usually based on a linear system assumption and fails to fully consider the nonlinear function reserve characteristics of the brain, 2, its processing process usually filters the inherent variability of the physiological signal as noise, thus losing the early information contained in the signal complexity or information entropy and being capable of indicating the change of the system function state, and 3, its analysis logic focuses on the independent values of each signal, fails to generate the evaluation information about the overall robustness of the system from the dynamic coupling relation of a plurality of signals, and the combined effect of these limitations results in that the existing data analysis method cannot provide effective information support due to the inherent limitation of its processing logic under the clinical requirements that require the accurate evaluation of the function reserve to support. Therefore, how to use the existing conventional multi-modal continuous monitoring data to create a data analysis system, the system can surpass the traditional static threshold comparison, and by processing and using the ignored dynamic response characteristics and the inherent variability information in the signals, an assessment index for quantifying the brain function reserves and the system vulnerability is constructed, which becomes the technical problem to be solved by the invention. Disclosure of Invention The invention provides a cerebral ischemia injury regulation and control analysis system, which mainly aims to solve the problem that the data processing mode in the prior art can only carry out static threshold comparison and cannot acquire information about brain dynamic function reserve and system vulnerability assessment from conventional monitoring data. In order to achieve the above object, the present invention provides a cerebral ischemia injury control analysis system, comprising: A signal acquisition module configured to synchronously acquire an average arterial pressure time-series signal and an intracranial pressure time-series signal; A probe signal extraction module configured to extract pressure fluctuations in a frequency range of 0.05Hz to 0.15Hz generated by the vessel autonomous regulatory activity by performing a band-pass filtering process on the average arterial pressure time-series signal, and define the pressure fluctuations as an endogenous probe signal; The detection source determining module is configured to monitor signal energy of an endogenous detection signal, determine the endogenous detection signal as a current detection signal if the signal energy is not continuously lower than an activation threshold, and determine a respiratory cycle signal extracted from synchronously acquired respiratory activity signals as the current d