Digital cerebral infarction critical and severe early recognition system
By collecting and analyzing patients' limb movement, heart rate, blood pressure, and environmental data, multi-dimensional monitoring and graded early warning of cerebral infarction can be achieved, solving the problem of insufficient traditional detection methods and improving the accuracy and timeliness of identification.
Patent Information
- Application Number
- CN202511250450.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-03
- Publication Date
- 2025-11-21
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
Existing technologies struggle to accurately identify early symptoms before a stroke occurs, and traditional detection methods lack sufficient sensitivity, leading to missed opportunities for optimal treatment.
By collecting patients' limb movement data, heart rate data, blood pressure data, and abnormal behaviors, and combining them with environmental information (temperature, humidity), real-time monitoring and graded early warning can be achieved through multi-dimensional data fusion analysis.
It improves the accuracy of identifying early symptoms of cerebral infarction, enabling timely notification of emergency contacts to take action and avoid missing the opportunity for treatment.
Smart Images
Figure CN120982980A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of medical health monitoring, in particular to a digital cerebral infarction critical severe early identification system. BACKGROUND
[0002] Before the onset of cerebral infarction, patients often experience a short early symptom stage, which is also known as the prodromal or super-early stage of cerebral infarction. During this period, patients may exhibit a series of mild neurological abnormalities, such as uncoordinated limb movements (manifested as changes in stride length, abnormal stride frequency, etc.), slurred speech, drooling, facial muscle twitching, etc. At the same time, the patient's physiological indicators may also change significantly, such as increased or decreased heart rate, elevated or reduced blood pressure, etc. These early symptoms and signs provide important clues for the early identification and intervention of cerebral infarction.
[0003] However, in actual clinical practice, the early identification of cerebral infarction faces many challenges. On the one hand, early symptoms are often mild and nonspecific, easily overlooked by patients and family members, or confused with other common diseases; on the other hand, traditional medical detection methods are not sensitive enough to the early pathological changes of cerebral infarction, making it difficult to make accurate diagnoses at the initial stage of symptoms. In addition, even in a hospital environment, from the patient's visit to the completion of relevant examinations (such as head CT, magnetic resonance imaging, etc.) and diagnosis, it takes a certain amount of time, which may miss the best treatment opportunity. SUMMARY
[0004] In view of the above, the present application proposes a digital cerebral infarction critical severe early identification system to solve at least one of the problems in the background art.
[0005] The present application provides a digital cerebral infarction critical severe early identification system, comprising: an acquisition module configured to obtain limb movement data, heart rate data and blood pressure data of a target patient; an identification module configured to obtain whether the target patient has abnormal behavior; a warning module configured to warn according to the limb movement data, heart rate data, blood pressure data and abnormal behavior of the target patient.
[0006] In some embodiments, the limb movement data includes stride length data and stride frequency data.
[0007] In some embodiments, the acquisition module is further configured to obtain environmental information of the target patient, the environmental information including temperature information and humidity information.
[0008] In some embodiments, the identification module obtains whether the target patient has abnormal behavior, comprising: When the target patient is at the target residence, abnormal behaviors of the target patient are monitored, including drooling.
[0009] In some embodiments, when the warning module issues a warning based on the target patient's limb movement data, heart rate data, blood pressure data, and abnormal behavior, it includes: When the target patient is at the target residence, and the identification module detects abnormal behavior in the target patient, the early warning module sends a first early warning signal to the target patient's emergency contact and determines whether the target patient's heart rate and blood pressure data are within the safe threshold range. Otherwise, the first warning signal will not be sent to the emergency contact of the target patient.
[0010] In some embodiments, when the warning module sends a first warning signal to the emergency contact of the target patient and determines whether the target patient's heart rate and blood pressure data are within a safe threshold range, it includes: When at least one of the target patient's heart rate and blood pressure data is greater than or less than the safety threshold range, the early warning module sends a second early warning signal to the target patient's emergency contact. Otherwise, a second warning signal will not be issued to the emergency contact of the target patient.
[0011] In some embodiments, when the target patient is not at the target residence, and at least one of the target patient's stride data and cadence data is less than the limb safety threshold range, the target patient's heart rate data, blood pressure data, and environmental information are determined. Otherwise, the heart rate data, blood pressure data, and environmental information of the target patient will not be assessed.
[0012] In some embodiments, when at least one of the target patient's stride length data and cadence data is less than a limb safety threshold range, the determination of the target patient's heart rate data, blood pressure data, and environmental information includes: When at least one of the target patient's stride length data and cadence data is less than the limb safety threshold range, and at least one of the target patient's heart rate data and blood pressure data is greater than or less than the safety threshold range, the environmental information of the target patient is determined. Otherwise, the environmental information of the target patient will not be determined.
[0013] In some embodiments, when at least one of the target patient's stride length data and cadence data is less than a limb safety threshold range, and at least one of the target patient's heart rate data and blood pressure data is greater than or less than the safety threshold range, determining the environmental information of the target patient includes: When the temperature information in the environment where the target patient is located is greater than the temperature threshold range, and the humidity information in the environment where the target patient is located is less than or equal to the humidity threshold range, the early warning module sends a third early warning signal to the emergency contact of the target patient. When the temperature information in the environment where the target patient is located is less than or equal to the temperature threshold range, and the humidity information in the environment where the target patient is located is greater than the humidity threshold range, the early warning module sends a fourth early warning signal to the emergency contact of the target patient.
[0014] In some embodiments, when at least one of the target patient's stride length data and cadence data is less than a limb safety threshold range, and at least one of the target patient's heart rate data and blood pressure data is greater than or less than the safety threshold range, the determination of the target patient's environmental information further includes: When the temperature information in the environment where the target patient is located is greater than the temperature threshold range, and the humidity information in the environment where the target patient is located is greater than the humidity threshold range, the early warning module sends a fifth early warning signal to the emergency contact of the target patient. When the temperature information in the environment where the target patient is located is less than or equal to the temperature threshold range, and the humidity information in the environment where the target patient is located is less than or equal to the humidity threshold range, the warning module sends a sixth warning signal to the emergency contact of the target patient.
[0015] Compared with existing technologies, the advantages of this invention are as follows: by collecting multiple information such as the patient's limb movement data (e.g., stride length, cadence), heart rate data, blood pressure data, and abnormal behaviors (e.g., drooling), and combining this with environmental information (temperature, humidity), it can more comprehensively and accurately capture early signs of stroke. This multi-dimensional data fusion analysis greatly improves the accuracy of identifying early symptoms of stroke and avoids misjudgment or missed diagnosis that may occur with a single data source. Compared with traditional methods that rely solely on a single symptom or simple examination, this invention can detect potential risks at an earlier stage, buying valuable time for subsequent intervention. Utilizing advanced sensor and data transmission technologies, the system can acquire various patient data in real time, enabling continuous dynamic monitoring of the patient's health status. Whether the patient is in their daily activities or in different environments, the system can promptly grasp changes in their physical indicators, ensuring that no critical information is missed. Multi-level warning signals are set according to different data combinations and degrees of abnormality. For example, when a patient exhibits abnormal behavior at home, a first warning signal is sent to the emergency contact. Further analysis of heart rate and blood pressure data is then conducted to determine if the patient is within safe threshold ranges; if so, a second warning signal is issued. When the patient is not at home and abnormal limb movement data is detected, environmental information is also considered to determine the appropriate warning signal. This tiered warning mechanism can promptly and accurately notify relevant personnel based on the severity and progression of the illness, enabling them to take appropriate measures and improving the effectiveness and timeliness of the response.
[0016] The above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure.
[0017] Other features and aspects of this disclosure will become clearer from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description
[0018] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific 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 from these drawings without creative effort.
[0019] Figure 1 Functional block diagram of the digital early identification system for critical and severe cerebral infarction provided in the embodiments of the present invention. Detailed Implementation
[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.
[0021] In the description of this application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.
[0022] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.
[0023] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.
[0024] See Figure 1 As shown, a digital early identification system for critical and severe stroke according to an embodiment of this application includes: The data acquisition module is configured to acquire limb movement data, heart rate data, and blood pressure data of the target patient. The identification module is configured to determine whether the target patient exhibits abnormal behavior. The early warning module is configured to issue early warnings based on the target patient's limb movement data, heart rate data, blood pressure data, and abnormal behavior.
[0025] It should be understood that the early warning module can also be configured to be based on the physiological and pathological changes of the target patient's cerebral blood vessels, such as the diameter of the cerebral blood vessels, blood flow, comparison of the physiological and pathological changes of the bilateral cerebral blood vessels, and the relationship between cerebral blood vessel changes and the affected and healthy limbs.
[0026] In some specific embodiments, the limb movement data includes stride length data and cadence data.
[0027] In some specific embodiments, the acquisition module is also configured to acquire environmental information of the target patient, including temperature information and humidity information.
[0028] In some specific embodiments, the identification module obtains whether the target patient exhibits abnormal behavior, including: When the target patient is at the target residence, abnormal behaviors of the target patient are monitored, including drooling.
[0029] It should be understood that wearable devices (such as smart bracelets, accelerometers, etc.) are used to monitor a patient's stride length (the span of each step) and cadence (the number of steps per unit time) in real time to analyze limb motor coordination. If the stride length or cadence is lower than the preset "limb safety threshold range" (such as a sudden decrease in stride length or unstable cadence), the system determines that the patient may have motor dysfunction, indicating an early risk of stroke.
[0030] Temperature and humidity data of the patient's environment are obtained through temperature and humidity sensors or smart home devices (such as air conditioners and humidifiers). Extreme temperatures (too high or too low) or humidity (too high or too low) may increase the burden on cerebrovascular systems. The system combines environmental data to assess the impact of external factors on the patient's condition.
[0031] When the patient is in the target residence (such as at home), the system monitors abnormal behavior, such as drooling (which may be caused by facial muscle weakness or nerve damage), through cameras or sensors (such as facial expression recognition, voice analysis, etc.).
[0032] If abnormal behaviors such as drooling are detected, the system will further combine other data (such as heart rate and blood pressure) to determine whether it is a precursor to a stroke.
[0033] In some specific embodiments, when the early warning module issues an early warning based on the target patient's limb movement data, heart rate data, blood pressure data, and abnormal behavior, it includes: When the target patient is at the target residence, and the identification module detects abnormal behavior in the target patient, the early warning module sends a first early warning signal to the target patient's emergency contact and determines whether the target patient's heart rate and blood pressure data are within the safe threshold range. Otherwise, the first warning signal will not be sent to the emergency contact of the target patient.
[0034] In some specific embodiments, when the early warning module sends a first early warning signal to the emergency contact of the target patient and determines whether the target patient's heart rate and blood pressure data are within a safe threshold range, it includes: When at least one of the target patient's heart rate and blood pressure data is greater than or less than the safety threshold range, the early warning module sends a second early warning signal to the target patient's emergency contact. Otherwise, a second warning signal will not be issued to the emergency contact of the target patient.
[0035] In some specific embodiments, when the target patient is not at the target residence, and at least one of the target patient's stride length data and cadence data is less than the limb safety threshold range, the target patient's heart rate data, blood pressure data, and environmental information are determined. Otherwise, the heart rate data, blood pressure data, and environmental information of the target patient will not be assessed.
[0036] In some specific embodiments, when at least one of the target patient's stride length data and cadence data is less than the limb safety threshold range, the determination of the target patient's heart rate data, blood pressure data, and environmental information includes: When at least one of the target patient's stride length data and cadence data is less than the limb safety threshold range, and at least one of the target patient's heart rate data and blood pressure data is greater than or less than the safety threshold range, the environmental information of the target patient is determined. Otherwise, the environmental information of the target patient will not be determined.
[0037] In some specific embodiments, when at least one of the target patient's stride length data and cadence data is less than a limb safety threshold range, and at least one of the target patient's heart rate data and blood pressure data is greater than or less than the safety threshold range, the determination of the target patient's environmental information includes: When the temperature information in the environment where the target patient is located is greater than the temperature threshold range, and the humidity information in the environment where the target patient is located is less than or equal to the humidity threshold range, the early warning module sends a third early warning signal to the emergency contact of the target patient. When the temperature information in the environment where the target patient is located is less than or equal to the temperature threshold range, and the humidity information in the environment where the target patient is located is greater than the humidity threshold range, the early warning module sends a fourth early warning signal to the emergency contact of the target patient.
[0038] In some specific embodiments, when at least one of the target patient's stride length data and cadence data is less than a limb safety threshold range, and at least one of the target patient's heart rate data and blood pressure data is greater than or less than the safety threshold range, the determination of the target patient's environmental information further includes: When the temperature information in the environment where the target patient is located is greater than the temperature threshold range, and the humidity information in the environment where the target patient is located is greater than the humidity threshold range, the early warning module sends a fifth early warning signal to the emergency contact of the target patient. When the temperature information in the environment where the target patient is located is less than or equal to the temperature threshold range, and the humidity information in the environment where the target patient is located is less than or equal to the humidity threshold range, the warning module sends a sixth warning signal to the emergency contact of the target patient.
[0039] It should be understood that when the patient is at the target residence, the system prioritizes monitoring abnormal behaviors (such as drooling). If abnormal behavior is detected, a first warning signal is triggered (notifying emergency contacts), and further checks are made to see if heart rate and blood pressure data exceed safe thresholds. If physiological data are abnormal, a second warning signal (enhanced warning) is triggered. When the patient is not at home, the system uses stride length and cadence data to determine whether motor function is normal. If stride length or cadence is below the threshold, a combined assessment of physiological data (heart rate, blood pressure) and environmental information (temperature and humidity) is initiated.
[0040] In a home setting, unusual behavior (such as drooling) is the starting point for triggering an alert; heart rate and blood pressure data are then used to determine the severity of the condition. In a non-home setting, abnormal gait / cadence is a risk signal, requiring comprehensive analysis in conjunction with heart rate, blood pressure, and ambient temperature and humidity data. For example: If the stride is abnormal and the heart rate / blood pressure is abnormal, then different warning levels (third to sixth warning signals) are given based on the ambient temperature and humidity.
[0041] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.
Claims
1. A digital early identification system for critical and severe stroke, characterized in that, include: The data acquisition module is configured to acquire limb movement data, heart rate data, and blood pressure data of the target patient. The identification module is configured to determine whether the target patient exhibits abnormal behavior. The early warning module is configured to issue early warnings based on the target patient's limb movement data, heart rate data, blood pressure data, and abnormal behavior.
2. The digital early identification system for critical and severe cerebral infarction according to claim 1, characterized in that, The limb movement data includes stride length data and cadence data.
3. The digital early identification system for critical and severe cerebral infarction according to claim 2, characterized in that, The acquisition module is also configured to acquire environmental information of the target patient, including temperature and humidity information.
4. The digital early identification system for critical and severe cerebral infarction according to claim 3, characterized in that, The identification module obtains whether the target patient exhibits abnormal behavior, including: When the target patient is at the target residence, abnormal behaviors of the target patient are monitored, including drooling.
5. The digital early identification system for critical and severe cerebral infarction according to claim 4, characterized in that, When the early warning module issues an early warning based on the target patient's limb movement data, heart rate data, blood pressure data, and abnormal behavior, it includes: When the target patient is at the target residence, and the identification module detects abnormal behavior in the target patient, the early warning module sends a first early warning signal to the target patient's emergency contact and determines whether the target patient's heart rate and blood pressure data are within the safe threshold range. Otherwise, the first warning signal will not be sent to the emergency contact of the target patient.
6. The digital early identification system for critical and severe cerebral infarction according to claim 5, characterized in that, When the early warning module sends a first early warning signal to the emergency contact of the target patient and determines whether the target patient's heart rate and blood pressure data are within a safe threshold range, it includes: When at least one of the target patient's heart rate and blood pressure data is greater than or less than the safety threshold range, the early warning module sends a second early warning signal to the target patient's emergency contact. Otherwise, a second warning signal will not be issued to the emergency contact of the target patient.
7. The digital early identification system for critical and severe cerebral infarction according to claim 6, characterized in that, When the target patient is not at the target residence, and at least one of the target patient's stride length data and cadence data is less than the limb safety threshold range, the target patient's heart rate data, blood pressure data, and environmental information are determined. Otherwise, the heart rate data, blood pressure data, and environmental information of the target patient will not be assessed.
8. The digital early identification system for critical and severe cerebral infarction according to claim 7, characterized in that, When at least one of the target patient's stride length and cadence data is less than the limb safety threshold range, the determination of the target patient's heart rate data, blood pressure data, and environmental information includes: When at least one of the target patient's stride length data and cadence data is less than the limb safety threshold range, and at least one of the target patient's heart rate data and blood pressure data is greater than or less than the safety threshold range, the environmental information of the target patient is determined. Otherwise, the environmental information of the target patient will not be determined.
9. A digital early identification system for critical and severe cerebral infarction according to claim 8, characterized in that, When at least one of the target patient's stride length and cadence data is less than the limb safety threshold range, and at least one of the target patient's heart rate and blood pressure data is greater than or less than the safety threshold range, the determination of the target patient's environmental information includes: When the temperature information in the environment where the target patient is located is greater than the temperature threshold range, and the humidity information in the environment where the target patient is located is less than or equal to the humidity threshold range, the early warning module sends a third early warning signal to the emergency contact of the target patient. When the temperature information in the environment where the target patient is located is less than or equal to the temperature threshold range, and the humidity information in the environment where the target patient is located is greater than the humidity threshold range, the early warning module sends a fourth early warning signal to the emergency contact of the target patient.
10. A digital early identification system for critical and severe cerebral infarction according to claim 9, characterized in that, When at least one of the target patient's stride length and cadence data is less than the limb safety threshold range, and at least one of the target patient's heart rate and blood pressure data is greater than or less than the safety threshold range, the determination of the target patient's environmental information further includes: When the temperature information in the environment where the target patient is located is greater than the temperature threshold range, and the humidity information in the environment where the target patient is located is greater than the humidity threshold range, the early warning module sends a fifth early warning signal to the emergency contact of the target patient. When the temperature information in the environment where the target patient is located is less than or equal to the temperature threshold range, and the humidity information in the environment where the target patient is located is less than or equal to the humidity threshold range, the warning module sends a sixth warning signal to the emergency contact of the target patient.