An intelligent cardiovascular care monitoring system and method

Abstract

The present application relates to the technical field of medical monitoring, in particular to an intelligent cardiovascular nursing monitoring system and method, the system comprising a data acquisition module, a multi-modal monitoring module and an intelligent early warning module. The present application collects physiological data of a patient in real time through a multi-parameter monitor, including cardiac function data, blood flow data and microcirculation data, calculates cardiac function evaluation indexes, blood flow evaluation indexes and microcirculation evaluation indexes based on the three types of data respectively, and obtains a first comprehensive evaluation index by weighted summation of the three indexes, thereby performing multi-dimensional analysis on the physiological condition of the patient and improving the scientificity and accuracy of the comprehensive evaluation index. The second comprehensive evaluation index is obtained by prediction based on the historical values of the first comprehensive evaluation index, and early warning is performed based on the second comprehensive evaluation index, thereby improving the timeliness of early warning, realizing forward-looking early warning and greatly improving the safety of monitoring of critical patients.

Description

Technical Field

[0001] This invention relates to the field of medical monitoring technology, specifically to an intelligent cardiovascular nursing monitoring system and method. Background Technology

[0002] Cardiovascular diseases, especially acute myocardial infarction, cardiogenic shock, and severe myocarditis, are characterized by rapid onset, rapidly changing condition, and extremely high mortality. In the intensive care unit (ICU), continuous and accurate physiological monitoring of patients is a crucial aspect of clinical treatment. Currently, clinical practice mainly relies on bedside multi-parameter monitors to monitor patients' basic vital signs in real time, including heart rate, electrocardiogram waveform, blood pressure, and body temperature.

[0003] However, current cardiovascular monitoring models suffer from a lack of comprehensive multi-dimensional assessment capabilities due to their simplistic information processing approach. Existing monitors typically employ a "single-parameter threshold alarm" mode, where separate upper and lower limits are set for various physiological indicators such as heart rate and blood pressure. An alarm is triggered when a parameter exceeds the preset range. This approach severs the intrinsic connections between different physiological indicators, while the pathophysiological changes in critically ill patients are often the result of multiple systems and factors working together. For example, it is not uncommon for blood pressure to remain within the normal range while tissue perfusion is severely inadequate (manifested as a decreased perfusion index or increased peripheral temperature difference). Relying solely on blood pressure alarms can easily lead to missed risks. Furthermore, current alarm systems often only issue alerts when indicators have deteriorated to the threshold, by which time the patient may have already entered the decompensated stage, missing the optimal window for early intervention. In addition, single-parameter threshold alarms are prone to generating numerous false positives due to patient activity or momentary interference, leading to habitual disregard by healthcare staff and creating potential safety hazards.

[0004] Therefore, there is an urgent need for an intelligent cardiovascular nursing monitoring system and method that can integrate multi-dimensional physiological parameters, has a forward-looking early warning capability, and can effectively reduce the false positive alarm rate. Summary of the Invention

[0005] To address the problems of existing technologies, such as limited monitoring modes, lack of multi-dimensional comprehensive assessment capabilities, reliance on single parameter threshold alarms leading to missed risk assessments, and delayed early warnings causing missed opportunities for optimal intervention, this invention provides an intelligent cardiovascular nursing monitoring system and method.

[0006] In a first aspect, the present invention provides an intelligent cardiovascular nursing monitoring system, including a data acquisition module, a multimodal monitoring module, and an intelligent early warning module;

[0007] The data acquisition module is used to collect the patient's physiological data, which includes cardiac function data, blood flow data, and microcirculation data. The multimodal monitoring module includes a cardiac function monitoring unit, a blood flow monitoring unit, and a circulation monitoring unit. The cardiac function monitoring unit obtains cardiac function assessment indicators based on the cardiac function data, the blood flow monitoring unit obtains blood flow assessment indicators based on the blood flow data, and the circulation monitoring unit obtains microcirculation assessment indicators based on the microcirculation data. The multimodal monitoring module weights and sums the cardiac function assessment indicators, blood flow assessment indicators, and microcirculation assessment indicators to obtain a first comprehensive assessment indicator. The intelligent early warning module predicts a second comprehensive evaluation index based on the historical values ​​of the first comprehensive evaluation index, and issues an early warning based on the second comprehensive evaluation index.

[0008] Furthermore, the cardiac function data is obtained by a multi-parameter monitor, and the cardiac function data includes the patient's real-time heart rate, ECG ST segment deviation, and number of premature atrial contractions.

[0009] Furthermore, the blood flow data is obtained from a multi-parameter monitor, and the blood flow data includes the patient's real-time systolic blood pressure, diastolic blood pressure, and mean arterial pressure.

[0010] Furthermore, the microcirculation data is obtained by a multi-parameter monitor, and the microcirculation data includes the patient's real-time peripheral tissue perfusion index and skin temperature.

[0011] Furthermore, the calculation process for the cardiac function assessment indicators includes the following steps: Arrhythmia index is calculated based on the patient's cardiac function data. Its expression is as follows:

[0012] in, Indicates the patient's basic condition value, Indicates the patient's real-time value, This indicates the number of premature atrial contractions (PACs) in the patient. This indicates the patient's real-time heart rate. and Represents the weight coefficient and ; Based on the aforementioned arrhythmia index Calculate cardiac function assessment indicators Its expression is as follows:

[0013] in, This indicates the patient's real-time heart rate; This indicates the patient's baseline heart rate; This indicates the ST segment deviation on the patient's electrocardiogram; This indicates the maximum permissible ST segment deviation on an electrocardiogram (ECG). Indicates the arrhythmia index; , and Represents the weight coefficient and ; It represents the absolute value.

[0014] Furthermore, the expression for the blood flow assessment index is as follows:

[0015] in, Indicates blood flow assessment indicators; Indicates real-time mean arterial pressure; Indicates the target mean arterial pressure; Indicates real-time systolic blood pressure; This indicates the lower limit threshold of systolic blood pressure; Indicates real-time diastolic blood pressure; This indicates the lower limit threshold of diastolic blood pressure; , and Represents the weight coefficient and ; Indicates taking the absolute value; This indicates taking the maximum value.

[0016] Furthermore, the expression for the microcirculation evaluation index is as follows:

[0017] in, Indicates microcirculation assessment indicators; Indicates the basal perfusion index; Indicates the peripheral tissue perfusion index; This indicates the difference between core temperature and peripheral skin temperature. For intubated patients, the core temperature is esophageal temperature, and for patients with indwelling urinary catheters, it is bladder temperature. Indicates the maximum clinically permissible temperature difference; and Represents the weight coefficient and .

[0018] Furthermore, based on the historical values ​​of the first comprehensive evaluation index, the expression for the second comprehensive evaluation index is obtained through prediction as follows:

[0019] in, This represents the second comprehensive evaluation indicator; This represents the first comprehensive evaluation indicator; Indicates the preceding Historical values ​​of the first comprehensive evaluation indicator within the time window; The first comprehensive evaluation index The expression is as follows:

[0020] in, This represents the first comprehensive evaluation indicator; Indicates indicators for assessing cardiac function; Indicates blood flow assessment indicators; Indicates microcirculation assessment indicators; , and This represents the weighting coefficient.

[0021] Furthermore, early warning based on the second comprehensive evaluation index includes: when the second comprehensive evaluation index... When the value is greater than or equal to the safety threshold, an early warning is issued; when the second comprehensive evaluation index... No warning will be issued if the value is below the safety threshold.

[0022] Secondly, the present invention provides an intelligent cardiovascular nursing monitoring method, comprising the following steps: S1. Real-time collection of the patient's physiological data, including cardiac function data, blood flow data, and microcirculation data.

[0023] S2. Based on the physiological data, calculate the cardiac function assessment index, blood flow assessment index, and microcirculation assessment index.

[0024] S3. The first comprehensive evaluation index is obtained by weighted summation of the cardiac function evaluation index, the blood flow evaluation index and the microcirculation evaluation index.

[0025] S4. Based on the first comprehensive evaluation index, a second comprehensive evaluation index is obtained through prediction.

[0026] S5. Issue an early warning based on the second comprehensive evaluation index.

[0027] Compared with the prior art, the present invention has the following beneficial effects: This invention uses a multi-parameter monitor to collect real-time physiological data from critically ill patients, including cardiac function data, blood flow data, and microcirculation data. Based on these three types of data, cardiac function assessment indicators, blood flow assessment indicators, and microcirculation assessment indicators are calculated. These three indicators are then weighted and summed to obtain a first comprehensive assessment indicator. This allows for multi-dimensional analysis of the patient's physiological condition, improving the scientific rigor and accuracy of the comprehensive assessment indicator. A second comprehensive assessment indicator is predicted based on historical values ​​of the first comprehensive assessment indicator, and early warnings are issued based on this second comprehensive assessment indicator. This improves the timeliness of early warnings, achieves proactive early warning, and significantly enhances the safety of monitoring critically ill patients. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 This is a schematic diagram of the framework of an intelligent cardiovascular nursing monitoring system according to the present invention.

[0030] Figure 2 This is a flowchart illustrating an intelligent cardiovascular nursing monitoring method according to the present invention. Detailed Implementation

[0031] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0032] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0033] This invention provides the following technical solutions: like Figure 1 The intelligent cardiovascular nursing monitoring system shown includes a data acquisition module, a multimodal monitoring module, and an intelligent early warning module; The data acquisition module is used to collect the patient's physiological data, which includes cardiac function data, blood flow data, and microcirculation data. The multimodal monitoring module includes a cardiac function monitoring unit, a blood flow monitoring unit, and a circulation monitoring unit. The cardiac function monitoring unit obtains cardiac function assessment indicators based on the cardiac function data, the blood flow monitoring unit obtains blood flow assessment indicators based on the blood flow data, and the circulation monitoring unit obtains microcirculation assessment indicators based on the microcirculation data. The multimodal monitoring module weights and sums the cardiac function assessment indicators, blood flow assessment indicators, and microcirculation assessment indicators to obtain a first comprehensive assessment indicator. The intelligent early warning module predicts a second comprehensive evaluation index based on the historical values ​​of the first comprehensive evaluation index, and issues an early warning based on the second comprehensive evaluation index.

[0034] In a preferred embodiment of this application, the cardiac function data is obtained by a multi-parameter monitor, and the cardiac function data includes the patient's real-time heart rate, electrocardiogram ST segment deviation, and number of premature atrial contractions.

[0035] In a preferred embodiment of this application, the blood flow data is obtained by a multi-parameter monitor, and the blood flow data includes the patient's real-time systolic blood pressure, diastolic blood pressure, and mean arterial pressure.

[0036] In a preferred embodiment of this application, the microcirculation data is obtained by a multi-parameter monitor, and the microcirculation data includes the patient's real-time peripheral tissue perfusion index and skin temperature.

[0037] In a preferred embodiment of this application, the calculation process of the cardiac function assessment index includes the following steps: Arrhythmia index is calculated based on the patient's cardiac function data. Its expression is as follows:

[0038] in, Indicates the patient's basic condition The value was obtained during the stable phase of the patient's condition and served as an individualized reference benchmark. Indicates the patient's real-time The value is measured based on the patient's heartbeat, i.e., the standard deviation of the normal sinus interval; This indicates the number of premature atrial contractions (PACs) in the patient; This indicates the patient's real-time heart rate; and Indicates the weighting coefficient. .

[0039] Arrhythmia Index In the formula, the first term This reflects the degree of decrease in real-time heart rate variability relative to baseline levels. A decrease suggests impaired autonomic nervous system function and an increased risk of arrhythmias. (Second item) This reflects the frequency of premature atrial contractions (PACs) and is calculated by weighting and summing the relative heart rate normalization results in a comprehensive arrhythmia index. Its value range is normalized to The higher the value, the more severe the arrhythmia, providing a quantitative basis for subsequent comprehensive assessment.

[0040] Based on the aforementioned arrhythmia index Calculate cardiac function assessment indicators Its expression is as follows:

[0041] in, This indicates the patient's real-time heart rate; This represents the patient's baseline heart rate, taken from the average value during a stable phase of the disease, and is used to measure the degree of deviation of the heart rate from the baseline. This indicates the ST segment deviation on the patient's electrocardiogram; This indicates the maximum permissible ST segment deviation on an electrocardiogram (ECG). Indicates the arrhythmia index; , and Represents the weight coefficient and .

[0042] Cardiac function assessment indicators In the formula, the first term measures the abnormal increase or decrease in real-time heart rate relative to baseline heart rate; both excessively fast and slow heart rates lead to an increased value. The second term quantifies the severity of ST segment deviation. The third term introduces an arrhythmia index. The weighted sum of these three terms yields the cardiac function index. The range of values ​​is normalized to The higher the value, the worse the cardiac function, thus providing a quantitative basis for subsequent multi-dimensional comprehensive assessment.

[0043] When the heart rate increases, myocardial oxygen consumption increases and diastolic filling time is shortened, which may induce or aggravate myocardial ischemia. Therefore, ST segment deviation that occurs when the heart rate is significantly elevated often indicates that the heart is overloaded and supply and demand are imbalanced, and the occurrence of acute coronary events should be highly suspected. Conversely, a slow heart rate may also induce ischemia due to reduced coronary perfusion. ST segment deviation when the heart rate is slow is equally important. Any abnormal ST segment deviation is a warning signal of myocardial ischemia in patients.

[0044] In a preferred embodiment of this application, the expression for the blood flow assessment index is as follows:

[0045] in, Indicates blood flow assessment indicators; Indicates real-time mean arterial pressure; Indicates the target mean arterial pressure; Indicates real-time systolic blood pressure; This indicates the lower limit threshold of systolic blood pressure; Indicates real-time diastolic blood pressure; This indicates the lower limit threshold of diastolic blood pressure; , and Represents the weight coefficient and ; Indicates taking the absolute value; This indicates taking the maximum value.

[0046] Blood flow assessment indicators In the formula This reflects the absolute deviation of mean arterial pressure from the target value. Mean arterial pressure is the main driving force of organ perfusion; both excessively low and excessively high mean arterial pressure can lead to organ dysfunction. Simultaneously, excessively low systolic pressure often indicates insufficient cardiac output or decreased peripheral vascular resistance, serving as an important early warning indicator of shock. Excessively low diastolic pressure can directly lead to insufficient myocardial blood supply, inducing or aggravating myocardial ischemia. Through weighted summation... The function will evaluate blood flow indicators The range of values ​​is normalized to A higher value indicates a more unstable hemodynamic state, providing a quantitative basis for subsequent multi-dimensional comprehensive assessment.

[0047] In a preferred embodiment of this application, the expression for the microcirculation evaluation index is as follows:

[0048] in, Indicates microcirculation assessment indicators; Indicates the basal perfusion index; Indicates the peripheral tissue perfusion index; This indicates the difference between core temperature and peripheral skin temperature. For intubated patients, the core temperature is esophageal temperature, and for patients with indwelling urinary catheters, it is bladder temperature. Indicates the maximum clinically permissible temperature difference; and Represents the weight coefficient and .

[0049] Microcirculation assessment indicators In the formula, the first term This reflects the degree of decrease in the real-time perfusion index relative to the baseline level. A decreased perfusion index indicates reduced local tissue blood flow and is an early and sensitive indicator of microcirculatory disturbances; the second item... This reflects the ratio of the central to peripheral temperature difference relative to the clinically permissible maximum. An increased temperature difference is a typical manifestation of compensatory peripheral vasoconstriction under stress, prioritizing blood supply to vital organs. However, an excessively large temperature difference often indicates tissue hypoperfusion and microcirculatory failure. The resulting microcirculatory assessment index is obtained through weighted summation. The range of values ​​is normalized to The larger the value, the more severe the microcirculation disorder, providing a quantitative basis for subsequent multi-dimensional comprehensive assessment.

[0050] In a preferred embodiment of this application, the expression for the second comprehensive evaluation index, which is predicted based on the historical values ​​of the first comprehensive evaluation index, is as follows:

[0051] in, This represents the second comprehensive evaluation indicator; This represents the first comprehensive evaluation indicator; Indicates the preceding The historical values ​​of the first comprehensive evaluation indicator are used within a time window of 5 seconds, with evaluations performed every 5 seconds; the second comprehensive evaluation indicator... When the trend is upward, the predicted value will further amplify the upward trend, indicating that the condition may deteriorate rapidly; when the second comprehensive assessment indicator... When the trend is downward, the predicted value will decrease accordingly, indicating that the condition is stabilizing or improving.

[0052] The first comprehensive evaluation index The expression is as follows:

[0053] in, This represents the first comprehensive evaluation indicator; Indicates indicators for assessing cardiac function; Indicates blood flow assessment indicators; Indicates microcirculation assessment indicators; , and This represents the weighting coefficient.

[0054] As a preferred embodiment of this application, early warning based on the second comprehensive evaluation index includes: when the second comprehensive evaluation index... When the value is greater than or equal to the safety threshold, an early warning is issued; when the second comprehensive evaluation index... No warning will be issued if the value is below the safety threshold.

[0055] like Figure 2 The present invention illustrates an intelligent cardiovascular nursing monitoring method, comprising the following steps: S1. Real-time collection of the patient's physiological data, including cardiac function data, blood flow data, and microcirculation data.

[0056] S2. Calculate cardiac function assessment indicators based on the physiological data. Blood flow assessment indicators and microcirculation assessment indicators .

[0057] S3, The cardiac function assessment indicators The blood flow assessment indicators and the microcirculation assessment indicators The weighted summation yields the first comprehensive evaluation index. .

[0058] S4. Based on the first comprehensive evaluation index The second comprehensive evaluation index is obtained through prediction. .

[0059] S5. Based on the second comprehensive evaluation index Issue an early warning.

[0060] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent cardiovascular nursing monitoring system, characterized in that, It includes a data acquisition module, a multimodal monitoring module, and an intelligent early warning module; The data acquisition module is used to collect the patient's physiological data, which includes cardiac function data, blood flow data, and microcirculation data. The multimodal monitoring module includes a cardiac function monitoring unit, a blood flow monitoring unit, and a circulation monitoring unit. The cardiac function monitoring unit obtains cardiac function assessment indicators based on the cardiac function data. The blood flow monitoring unit obtains blood flow assessment indicators based on the blood flow data. The circulation monitoring unit obtains microcirculation assessment indicators based on the microcirculation data. The multimodal monitoring module weights and sums the cardiac function assessment indicators, blood flow assessment indicators, and microcirculation assessment indicators to obtain a first comprehensive assessment indicator. The intelligent early warning module predicts a second comprehensive evaluation index based on the historical values ​​of the first comprehensive evaluation index, and issues an early warning based on the second comprehensive evaluation index.

2. The intelligent cardiovascular nursing monitoring system according to claim 1, characterized in that, The cardiac function data was obtained by a multi-parameter monitor, and the cardiac function data included the patient's real-time heart rate, ST segment deviation on electrocardiogram, and number of premature atrial contractions.

3. The intelligent cardiovascular nursing monitoring system according to claim 1, characterized in that, The blood flow data was obtained from a multi-parameter monitor and included the patient's real-time systolic blood pressure, diastolic blood pressure, and mean arterial pressure.

4. The intelligent cardiovascular nursing monitoring system according to claim 1, characterized in that, The microcirculation data was obtained by a multi-parameter monitor, and the microcirculation data included the patient's real-time peripheral tissue perfusion index and skin temperature.

5. The intelligent cardiovascular nursing monitoring system according to claim 1, characterized in that, The calculation process for the cardiac function assessment indicators includes the following steps: Arrhythmia index is calculated based on the patient's cardiac function data. Its expression is as follows: in, Indicates the patient's basic condition value, Indicates the patient's real-time value, This indicates the number of premature atrial contractions (PACs) in the patient. This indicates the patient's real-time heart rate. and Represents the weight coefficient and ; Based on the aforementioned arrhythmia index Calculate cardiac function assessment indicators Its expression is as follows: in, This indicates the patient's real-time heart rate; This indicates the patient's baseline heart rate; This indicates the ST segment deviation on the patient's electrocardiogram; This indicates the maximum permissible ST segment deviation on an electrocardiogram (ECG). Indicates the arrhythmia index; , and Represents the weight coefficient and ; It represents the absolute value.

6. The intelligent cardiovascular nursing monitoring system according to claim 1, characterized in that, The expression for the blood flow assessment index is as follows: in, Indicates blood flow assessment indicators; Indicates real-time mean arterial pressure; Indicates the target mean arterial pressure; Indicates real-time systolic blood pressure; This indicates the lower limit threshold of systolic blood pressure; Indicates real-time diastolic blood pressure; This indicates the lower limit threshold of diastolic blood pressure; , and Represents the weight coefficient and ; Indicates taking the absolute value; This indicates taking the maximum value.

7. The intelligent cardiovascular nursing monitoring system according to claim 1, characterized in that, The expression for the microcirculation assessment index is as follows: in, Indicates microcirculation assessment indicators; Indicates the basal perfusion index; Indicates the peripheral tissue perfusion index; This indicates the difference between core temperature and peripheral skin temperature. For intubated patients, the core temperature is esophageal temperature, and for patients with indwelling urinary catheters, it is bladder temperature. Indicates the maximum clinically permissible temperature difference; and Represents the weight coefficient and .

8. The intelligent cardiovascular nursing monitoring system according to claim 1, characterized in that, The expression for the second comprehensive evaluation index, predicted based on the historical values ​​of the first comprehensive evaluation index, is as follows: in, This represents the second comprehensive evaluation indicator; This represents the first comprehensive evaluation indicator; Indicates the preceding Historical values ​​of the first comprehensive evaluation indicator within the time window; The first comprehensive evaluation index The expression is as follows: in, This represents the first comprehensive evaluation indicator; Indicates indicators for assessing cardiac function; Indicates blood flow assessment indicators; Indicates microcirculation assessment indicators; , and This represents the weighting coefficient.

9. The intelligent cardiovascular nursing monitoring system according to claim 8, characterized in that, Early warning based on the second comprehensive evaluation index includes: when the second comprehensive evaluation index... When the value is greater than or equal to the safety threshold, an early warning is issued; when the second comprehensive evaluation index... No warning will be issued if the value is below the safety threshold.

10. An intelligent cardiovascular nursing monitoring method, implemented based on the system described in any one of claims 1-9, characterized in that, Includes the following steps: The patient's physiological data is collected in real time, including cardiac function data, blood flow data, and microcirculation data; Based on the physiological data, cardiac function assessment indicators, blood flow assessment indicators, and microcirculation assessment indicators were calculated. The first comprehensive evaluation index is obtained by weighted summation of the cardiac function evaluation index, the blood flow evaluation index, and the microcirculation evaluation index; The second comprehensive evaluation index is obtained by predicting based on the first comprehensive evaluation index. Early warnings will be issued based on the second comprehensive evaluation indicator.

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