Closed-loop feedback training method and device for hypoglycemia perception reconstruction

Abstract

According to the closed-loop feedback training method and device for hypoglycemia perception reconstruction, a closed-loop training system integrating monitoring, stimulation, recording and evaluation is established, a patient is helped to reestablish the correct recognition and perception ability of the brain on hypoglycemia early signals, and the serious hypoglycemia risk is reduced fundamentally. The method comprises the following steps: (1) acquiring continuous blood glucose monitoring data of a user through a data interface, and judging whether a training trigger condition is met or not based on a blood glucose lowering trend of the data; (2) when it is judged that the training opportunity arrives, a preset specific tactile stimulus is applied to the user through a tactile feedback device; (3) when the tactile stimulation is applied, a guide instruction is sent to a user through a user interface, and a recording entrance is provided; (4) the blood glucose value / trend at the training time, the applied tactile stimulation mode and the subjective feeling recorded by the user are stored in an associated mode, a training log is formed, and the training log is analyzed regularly.

Description

Technical Field

[0001] This invention belongs to the technical field of medical rehabilitation, and particularly relates to a closed-loop feedback training method for hypoglycemia perception reconstruction, and a closed-loop feedback training device for hypoglycemia perception reconstruction based on this method. Background Technology

[0002] Impaired hypoglycemia perception is one of the most challenging aspects of diabetes management. Patients lose their ability to detect early signs of hypoglycemia, significantly increasing their risk of severe hypoglycemia. Currently, the main clinical approach is to strictly avoid hypoglycemic events, such as through close monitoring with continuous glucose monitoring systems. However, existing technologies primarily focus on "avoiding" the risk rather than addressing the underlying perceptual deficit in patients.

[0003] Currently, the existing technologies are continuous glucose monitoring systems and their early warning methods, as well as behavioral cognitive therapies based on these systems.

[0004] I. Continuous Blood Glucose Monitoring Systems and Early Warning Methods Taking CGM (Continuous Glucose Monitoring) products from companies like Dexcom and Abbott as examples, their workflow is as follows: Implementation: The glucose concentration in the interstitial fluid is monitored by a subcutaneous sensor, and the data is sent to a receiver or smartphone.

[0005] Method and Flow: 1. Data Acquisition: Real-time acquisition of blood glucose levels.

[0006] 2. Threshold determination: Compare the real-time blood glucose value with the preset alarm threshold (e.g., 3.9 mmol / L).

[0007] 3. Warning Trigger: When the blood glucose level reaches or falls below the threshold, the system triggers an audible, visual, or vibration alarm to remind the user that their blood glucose is too low.

[0008] II. CGM-based Sensory Education Therapy This is a clinical education method developed based on CGM.

[0009] Implementation method: When receiving a CGM hypoglycemia alert, the doctor instructs the patient not only to deal with the hypoglycemia, but also to consciously calm down and carefully experience and record any subtle sensations in the body at that moment.

[0010] Method and Flow: 1. Alarm occurs: CGM issues a hypoglycemia alarm.

[0011] 2. Active recall and recording: The patient, through their own will, tries to perceive and record the physical sensations at the moment of alarm (such as "numbness of the lips" or "slowed thinking").

[0012] 3. Establishing association: Through repeated exposure, it is hoped that patients can re-establish the association between "these subtle sensations" and "hypoglycemia" in their brains.

[0013] The aforementioned existing technologies have the following inherent and insurmountable drawbacks in achieving the fundamental therapeutic goal of "hypoglycemia perception reconstruction": Delayed warnings, missing the optimal training window: CGM's warning is based on the fact that "blood glucose has dropped to the threshold." For sensory reconstruction training, at this point, the patient's cognitive function may already be mildly affected, which is not the optimal physiological window for fine interoceptive training. Ideally, training should be conducted in the early stages when blood glucose begins to decrease but has not yet severely affected cognition.

[0014] Lack of standardized and precise sensory stimulation: Existing CGM vibration alarm modes are singular (usually just a simple "buzzing" vibration), and their purpose is only to "attract attention" rather than to serve as a "conditioned stimulus" in conditioned reflex training. It cannot provide differentiated and standardized tactile feedback to accurately "mark" the physiological state of hypoglycemia based on individual patient differences or different stages of hypoglycemia.

[0015] Relying on patient initiative makes it difficult to guarantee effectiveness: "CGM-based sensory education therapy" relies entirely on patients' willpower to complete the difficult process of perceiving and recording their inner feelings, even when their cognitive function may be impaired. This method lacks structured guidance, is cumbersome, has poor compliance, and cannot quantify or adaptively optimize the training effect, resulting in limited and unstable effects in reconstructing perception.

[0016] The system is isolated and lacks a closed-loop training mechanism: Existing technology is an open-loop system: "alarm → patient action." It lacks crucial feedback and optimization components. The system cannot know whether the patient has successfully perceived the internal signal, nor can it dynamically adjust the training difficulty based on the patient's training progress (such as providing early warnings or changing stimulus patterns), thus failing to achieve personalized and adaptive rehabilitation training.

[0017] In summary, existing technologies cannot provide a sensory reconstruction solution for patients with impaired hypoglycemia perception that can be implemented early, with precise stimulation, structured guidance, and closed-loop optimization. Summary of the Invention

[0018] To overcome the shortcomings of existing technologies, the technical problem to be solved by this invention is to provide a closed-loop feedback training method for hypoglycemia perception reconstruction. This method can solve the fundamental problem that existing technologies can only provide passive warnings and cannot actively repair perception defects. By creating a closed-loop training system that integrates monitoring, stimulation, recording, and evaluation, it helps patients rebuild the brain's ability to correctly identify and perceive early signs of hypoglycemia, thereby reducing the risk of severe hypoglycemia from the root.

[0019] The technical solution of this invention is: a closed-loop feedback training method for hypoglycemia perception reconstruction, comprising the following steps: (1) Obtain the user's continuous blood glucose monitoring data through the data interface, and determine whether the training trigger condition has been met based on the blood glucose decline trend of this data; (2) When the training opportunity is determined in step (1), a preset specific tactile stimulus is applied to the user through the tactile feedback device; (3) While applying tactile stimulation, guide instructions are given to the user through the user interface, and a recording entry is provided; (4) The blood glucose value / trend at the time of training, the applied tactile stimulation pattern and the subjective feelings recorded by the user are associated and stored to form a training log, and the training log is analyzed regularly.

[0020] This invention addresses the fundamental problem of existing technologies, which can only provide passive warnings but cannot actively repair perceptual deficiencies. By creating a closed-loop training system that integrates monitoring, stimulation, recording, and evaluation, it helps patients rebuild their brain's ability to correctly identify and perceive early signs of hypoglycemia, thereby reducing the risk of severe hypoglycemia at its source.

[0021] A closed-loop feedback training device for hypoglycemia perception reconstruction is also provided, the device comprising: The judgment module is configured to obtain the user's continuous blood glucose monitoring data through the data interface, and determine whether the training trigger condition has been met based on the blood glucose decline trend of this data. The feedback module is configured to apply a preset, specific tactile stimulus to the user when the training opportunity arises; The user interface is configured to issue guiding instructions to the user while applying tactile stimulation and to provide a recording entry; The storage and analysis module is configured to associate and store the blood glucose value / trend at the time of training, the applied tactile stimulation pattern, and the user's recorded subjective feelings to form a training log, which is then analyzed periodically. Attached Figure Description

[0022] Figure 1 This is a flowchart of the closed-loop feedback training method for hypoglycemia perception reconstruction according to the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0024] To make the description of this disclosure more detailed and complete, illustrative descriptions of embodiments and specific examples of the present invention are provided below; however, these are not the only forms of implementing or utilizing the specific examples of the present invention. The embodiments cover features of multiple specific examples and methods and steps for constructing and operating these specific examples, and their order. However, other specific examples may also be used to achieve the same or equivalent functions and order of steps.

[0025] like Figure 1 As shown, this closed-loop feedback training method for hypoglycemia perception reconstruction includes the following steps: (1) Obtain the user's continuous blood glucose monitoring data through the data interface, and determine whether the training trigger condition has been met based on the blood glucose decline trend of this data; (2) When the training opportunity is determined in step (1), a preset specific tactile stimulus is applied to the user through the tactile feedback device; (3) While applying tactile stimulation, guide instructions are given to the user through the user interface, and a recording entry is provided; (4) The blood glucose value / trend at the time of training, the applied tactile stimulation pattern and the subjective feelings recorded by the user are associated and stored to form a training log, and the training log is analyzed regularly.

[0026] This invention addresses the fundamental problem of existing technologies, which can only provide passive warnings but cannot actively repair perceptual deficiencies. By creating a closed-loop training system that integrates monitoring, stimulation, recording, and evaluation, it helps patients rebuild their brain's ability to correctly identify and perceive early signs of hypoglycemia, thereby reducing the risk of severe hypoglycemia at its source.

[0027] The specific advantages of this invention are as follows: 1. The core innovation of this solution lies not in inventing new sensors, but in the innovative integration and workflow design of existing components (CGM, tactile devices) in the new application scenario of "sensory reconstruction". At a minimum, only continuous blood glucose data and a wearable device capable of outputting specific tactile stimuli are needed to constitute the most basic sensory training system.

[0028] 2. Closed-loop process: The training loop is a complete, spiraling process, which is the key to achieving perception "reconstruction" rather than simple "early warning".

[0029] 3. Directly corresponds to the purpose of the invention: By implementing "Step One," proactive intervention was achieved, thus resolving the issue of delayed early warning.

[0030] Step Two provides standardized conditioned stimuli, offering a reliable signal basis for sensory reconstruction.

[0031] Guided perception recording was achieved through "Step Three," which solved the problem of relying on the patient's subjective initiative.

[0032] Step four enables closed-loop assessment and adaptive optimization, allowing the system to become increasingly "intelligent" through practice and to adapt to each patient in a personalized way.

[0033] Preferably, in step (1), a training opportunity is determined when the following two conditions are met simultaneously: the current blood glucose level is between 4.2 mmol / L and 5.0 mmol / L; and the blood glucose rate has decreased by more than 0.1 mmol / L / minute in the past 15 minutes; then, an instruction to start training is output.

[0034] Preferably, in step (2), a command is sent to the smart bracelet via Bluetooth. After receiving the command, the smart bracelet drives its vibration motor to generate a preset specific tactile stimulus. The stimulus pattern consists of two short vibrations with a one-second interval, followed by a long vibration.

[0035] Preferably, in step (3), the smartphone's App interface is lit up and a guide interface is displayed to guide the user to provide feedback on their feelings to the App.

[0036] Preferably, in step (4), the training log includes: blood glucose value at the trigger time, blood glucose rate of decrease, tactile stimulation pattern, and user's own feelings.

[0037] Preferably, in step (4), the user's training log is analyzed. When the blood glucose level drops from 5.0 mmol / L at a rate of more than 0.1 mmol / L / minute, and the probability of the user experiencing palpitations / accelerated heartbeat exceeds 60%, the user's training trigger condition is adjusted to 4.2 mmol / L - 5.2 mmol / L.

[0038] Preferably, the method further includes step (5): the smartphone App uploads the desensitized training logs to the cloud server; the cloud server aggregates the training data of many users and performs global optimization of tactile stimulation patterns and optimal training timing; the cloud server sends the optimized parameters to the smartphone Apps of all users.

[0039] A closed-loop feedback training device for hypoglycemia perception reconstruction is also provided, the device comprising: The judgment module is configured to obtain the user's continuous blood glucose monitoring data through the data interface, and determine whether the training trigger condition has been met based on the blood glucose decline trend of this data. The feedback module is configured to apply a preset, specific tactile stimulus to the user when the training opportunity arises; The user interface is configured to issue guiding instructions to the user while applying tactile stimulation and to provide a recording entry; The storage and analysis module is configured to associate and store the blood glucose value / trend at the time of training, the applied tactile stimulation pattern, and the user's recorded subjective feelings to form a training log, which is then analyzed periodically.

[0040] Preferably, in the judgment module, a training opportunity is determined when the following two conditions are met simultaneously: the current blood glucose level is between 4.2 mmol / L and 5.0 mmol / L; and the blood glucose rate has decreased by more than 0.1 mmol / L / minute in the past 15 minutes; then, an instruction to start training is output.

[0041] Preferably, the device further includes a cloud server configured to receive desensitized training logs from the smartphone app; the cloud server aggregates training data from many users and performs global optimization of tactile stimulation patterns and optimal training timing; the cloud server then distributes the optimized parameters to the smartphone app of all users.

[0042] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0043] This closed-loop feedback training method for hypoglycemia perception reconstruction includes the following steps: Step 1: Monitoring Physiological State and Determining Training Timing The system obtains the user's continuous blood glucose monitoring data through a data interface and determines whether the training trigger conditions have been met based on this data.

[0044] Triggering conditions: The triggering conditions are not a single fixed blood glucose threshold, but a dynamic judgment based on the blood glucose decreasing trend. For example, when the system predicts that the probability of the user experiencing hypoglycemia within a specific time in the future (such as 15-30 minutes) exceeds a preset threshold, and / or the current blood glucose value is in the normal low range (such as 4.0-5.5 mmol / L) and continues to decrease rapidly, it is determined to be the best time for training.

[0045] Step 2: Application of specific tactile conditioning stimuli When the training opportunity is determined in step one, the system immediately applies a preset specific tactile stimulus to the user through a wearable haptic feedback device (such as a smart bracelet or a dedicated vibration patch).

[0046] Stimulus characteristics: This stimulus is different from ordinary alarm vibrations and has a unique, identifiable pattern, such as a specific vibration frequency and beat (e.g., "short-long-short"), which is intended to serve as a conditioned stimulus signal.

[0047] Step 3: Guided Body Perception and Recording While applying tactile stimulation, the system issues guiding instructions to the user through a user interface (such as a smartphone app) and provides a convenient entry point for recording information.

[0048] Guiding instructions: Instruct users to pause their current activity, turn their attention inward, and feel and identify any subtle bodily sensations at the moment (such as "Feel your lips, fingers, or heartbeat, is there anything unusual?").

[0049] Recording function: Users can quickly select from preset options (such as "lip numbness", "heart palpitations", "slow thinking", "no special feeling") or make a brief voice recording, following the guidance. This operation must be completed before dealing with hypoglycemia (such as eating).

[0050] Step 4: Training Data Loop Closure and Model Adaptation The system stores and analyzes the data from this training session and uses it to optimize subsequent training.

[0051] Data association and storage: The system associates and stores the blood glucose value / trend at the time of training, the applied tactile stimulation pattern, and the user's recorded subjective feelings to form a training log.

[0052] Adaptive optimization: The system periodically analyzes training logs. For example, if the system detects that a user repeatedly records specific sensations (such as "palpitations") related to hypoglycemia during a particular blood glucose drop phase (e.g., a rapid decrease from 5.0 mmol / L), then in subsequent training, it can prioritize triggering stimuli during this blood glucose phase to reinforce the correct perceptual association. Conversely, the stimulation pattern or timing can be adjusted.

[0053] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A closed-loop feedback training method for hypoglycemia perception reconstruction, characterized in that: It includes the following steps: (1) Obtain the user's continuous blood glucose monitoring data through the data interface, and determine whether the training trigger condition has been met based on the blood glucose decline trend of this data; (2) When the training opportunity is determined in step (1), a preset specific tactile stimulus is applied to the user through the tactile feedback device; (3) While applying tactile stimulation, guide instructions are given to the user through the user interface, and a recording entry is provided; (4) The blood glucose value / trend at the time of training, the applied tactile stimulation pattern and the subjective feelings recorded by the user are associated and stored to form a training log, and the training log is analyzed regularly.

2. The closed-loop feedback training method for hypoglycemia perception reconstruction according to claim 1, characterized in that: In step (1), a training opportunity is determined when the following two conditions are met simultaneously: the current blood glucose level is between 4.2 mmol / L and 5.0 mmol / L; and the rate of decrease in blood glucose level exceeds 0.1 mmol / L / minute in the past 15 minutes. Then, output the command to start training.

3. The closed-loop feedback training method for hypoglycemia perception reconstruction according to claim 2, characterized in that: In step (2), a command is sent to the smart bracelet via Bluetooth. After receiving the command, the smart bracelet drives its vibration motor to generate a preset specific tactile stimulus. The stimulus pattern consists of two short vibrations with a one-second interval, followed by a long vibration.

4. The closed-loop feedback training method for hypoglycemia perception reconstruction according to claim 3, characterized in that: In step (3), the smartphone's App interface is lit up and a guide interface is displayed to guide the user to provide feedback on their feelings to the App.

5. The closed-loop feedback training method for hypoglycemia perception reconstruction according to claim 4, characterized in that: In step (4), the training log includes: blood glucose value at the trigger time, blood glucose rate of decrease, tactile stimulation pattern, and user's own feelings.

6. The closed-loop feedback training method for hypoglycemia perception reconstruction according to claim 5, characterized in that: In step (4), the user's training log is analyzed. When the blood glucose level drops from 5.0 mmol / L at a rate of more than 0.1 mmol / L / minute, and the probability of the user experiencing palpitations / accelerated heartbeat exceeds 60%, the user's training trigger condition is adjusted to 4.2 mmol / L - 5.2 mmol / L.

7. The closed-loop feedback training method for hypoglycemia perception reconstruction according to claim 6, characterized in that: The method also includes step (5), in which the smartphone app uploads the desensitized training logs to the cloud server; The cloud server aggregates training data from many users and performs global optimization of tactile stimulation patterns and optimal training timing. The cloud server will distribute the optimized parameters to the smartphone app for all users.

8. A closed-loop feedback training device for hypoglycemia perception reconstruction, characterized in that: It includes: The judgment module is configured to obtain the user's continuous blood glucose monitoring data through the data interface, and determine whether the training trigger condition has been met based on the blood glucose decline trend of this data. The feedback module is configured to apply a preset, specific tactile stimulus to the user when the training opportunity arises; The user interface is configured to issue guiding instructions to the user while applying tactile stimulation and to provide a recording entry; The storage and analysis module is configured to associate and store the blood glucose value / trend at the time of training, the applied tactile stimulation pattern, and the user's recorded subjective feelings to form a training log, which is then analyzed periodically.

9. The closed-loop feedback training device for hypoglycemia perception reconstruction according to claim 8, characterized in that: In the judgment module, a training opportunity is determined when the following two conditions are met simultaneously: the current blood glucose level is between 4.2 mmol / L and 5.0 mmol / L; and the blood glucose rate has decreased by more than 0.1 mmol / L / minute in the past 15 minutes. Then, output the command to start training.

10. The closed-loop feedback training device for hypoglycemia perception reconstruction according to claim 9, characterized in that: The device also includes a cloud server configured to receive desensitized training logs from smartphone apps; the cloud server aggregates training data from many users and performs global optimization of tactile stimulation patterns and optimal training timing; the cloud server then distributes the optimized parameters to the smartphone apps of all users.

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