A sleep regulation method and system

Abstract

This invention discloses a sleep regulation method and system, applicable to sleep regulation systems comprising a first terminal and a second terminal. The method includes: simultaneously outputting pulse signals through the second terminal and acquiring bioelectrical signals through the first terminal, determining an objective perception threshold based on time-locked analysis; acquiring historical regulation data to distinguish between novice adaptation mode and mature treatment mode; in novice adaptation mode, limiting the upper limit of output intensity based on the objective perception threshold, controlling intensity ramping through physiological relaxation state feedback, and performing intensity rollback when pain features are detected; in mature treatment mode, generating an adaptive stimulation prescription based on a dual-state assessment of resting period electrical signals combined with a general threshold and an individual historical baseline, and dynamically adjusting the output intensity according to real-time bioelectrical signals during the output process.

Description

Technical Field

[0001] This invention relates to the field of signal processing technology, and in particular to a sleep regulation method and system. Background Technology

[0002] Existing sleep regulation technologies can be broadly categorized into three types: first, sleep monitoring technologies based on bioelectrical signal acquisition, such as smart bracelets and head-mounted electroencephalogram (EEG) devices, which analyze sleep stages by monitoring physiological parameters such as heart rate and brain waves; second, physical therapy technologies based on neuromodulation, particularly percutaneous vagus nerve stimulation (PVS) devices, which apply microcurrents to the vagus nerve branches in the outer ear to regulate parasympathetic nerve activity; and third, acoustic sleep aid technologies, such as playing white noise, binaural beats, or guided meditation. In recent years, the trend of technological integration has become increasingly apparent, with the integration of electrical stimulation therapy, EEG monitoring, and acoustic intervention into miniature wearable devices becoming a key focus of industry development, aiming to achieve a closed-loop sleep regulation system that combines monitoring and intervention.

[0003] However, existing sleep regulation methods suffer from a significant difference in magnitude between electrical stimulation signals and electroencephalogram (EEG) signals. Stimulation signals are typically thousands of times stronger than microvolt-level EEG signals. Integrating stimulation and acquisition electrodes into the same device or placing them in extremely close proximity can cause severe electromagnetic interference, leading to the suppression of EEG signals. Current solutions often employ a time-sharing model of "stimulation first, monitoring later," failing to achieve real-time closed-loop control. Secondly, existing devices lack precise assessment mechanisms based on individual physiological baselines, often using fixed parameters for stimulation, ignoring individual differences in user stress levels and tolerance, resulting in poor intervention effects or even discomfort. Furthermore, the body's sensitivity to electrical current changes dynamically during sleep; existing devices cannot detect and adaptively adjust to the user's pain response in real time, posing a risk of awakening due to stinging, leading to a poor user experience. Summary of the Invention

[0004] This invention provides a sleep regulation method and system to improve the real-time performance and effectiveness of sleep regulation and enhance user experience.

[0005] To address the aforementioned technical problems, embodiments of the present invention provide a sleep regulation method applicable to a sleep regulation system including a first terminal and a second terminal, wherein the first terminal and the second terminal are disposed on the head of the target individual, comprising: The second terminal outputs a pulse signal to the target individual, while the first terminal collects the first electrical signal of the target individual and determines the objective perception threshold of the target individual based on the first electrical signal. Acquire historical regulation data of the target individual, and determine the regulation mode based on the historical regulation data. The regulation mode includes a first mode and a second mode. When the adjustment mode is the first mode, the upper limit of the output intensity of the second terminal is set based on the objective perception threshold, the output adjustment signal is controlled according to the upper limit of the output intensity and the preset ramping algorithm, pain feature detection is performed based on the real-time bioelectric signal obtained by the first terminal, and the output intensity of the second terminal is controlled to fall back when pain feature is detected. When the adjustment mode is the second mode, the target intensity is obtained by combining the resting period electrical signal collected by the first terminal with a preset general threshold and a preset individual historical baseline for dual state evaluation; the output intensity of the second terminal is controlled to increase toward the target intensity, and the output intensity of the second terminal is dynamically adjusted according to the real-time bioelectrical signal collected by the first terminal during the output process.

[0006] This invention determines the objective perception threshold by simultaneously outputting a pulse signal from a second terminal and acquiring a first electrical signal from a first terminal, thus achieving real-time coordination between stimulation and acquisition. This avoids the temporal fragmentation problem of "stimulation first, monitoring later" in traditional solutions. Furthermore, by acquiring historical adjustment data and determining the adjustment mode based on it, it achieves quantitative identification of the user's usage status. The adjustment mode is then divided into a first mode and a second mode, enabling differentiated guidance for new and experienced users and improving the targeting of the adjustment strategy. In the first mode, the upper limit of the output intensity of the second terminal is set based on the objective perception threshold to ensure that the stimulation intensity does not exceed the user's physiological tolerance range. Subsequently, the output adjustment signal is controlled according to the upper limit of the output intensity and a preset ramp-up algorithm, achieving a gradual increase in stimulation intensity and avoiding discomfort caused by sudden intensity changes. Pain feature detection is performed using real-time bioelectrical signals acquired from the first terminal, enabling real-time perception of user discomfort. A safety circuit breaker mechanism is established by controlling the output intensity of the second terminal to revert when pain features are detected, ensuring safety during use. In the second mode, a dual-state assessment is performed based on resting-period electrical signals acquired from the first terminal, combined with a preset universal threshold and an individual's historical baseline, achieving precise quantification of the user's current physiological state. A personalized stimulation prescription is generated by obtaining the target intensity. Furthermore, a smooth transition to stimulation intervention is achieved by controlling the output intensity of the second terminal to gradually increase towards the target intensity. A complete closed-loop feedback mechanism is formed by dynamically adjusting the output intensity of the second terminal based on the real-time bioelectrical signals acquired from the first terminal during the output process, ensuring the continuous safety and effectiveness of the adjustment process.

[0007] Furthermore, the step of outputting a pulse signal to the target individual based on the second terminal, simultaneously acquiring a first electrical signal of the target individual based on the first terminal, and determining the objective perception threshold of the target individual based on the first electrical signal includes: The second terminal is controlled to output a preset test pulse sequence to the target individual, and the trigger timestamp of each test pulse in the test pulse sequence is recorded; The first terminal is controlled to collect bioelectrical signal fragments of the target individual based on the trigger timestamp; Based on the bioelectric signal fragments, peripheral electromyographic evoked response values ​​with different pulse intensities were calculated, and event-related potential data under the same pulse intensity were determined; When the peripheral electromyographic evoked response value exceeds a preset electromyographic threshold, or the peak-to-peak value of the event-related potential data exceeds a preset evoked potential threshold, the pulse intensity of the current test pulse is determined as the objective perception threshold.

[0008] This invention establishes a standardized stimulation procedure for threshold calibration by controlling a second terminal to output a preset test pulse sequence to the target individual. Subsequently, by recording the trigger timestamp of each test pulse in the sequence, a time reference for the stimulation event is established. Next, by controlling a first terminal to acquire bioelectrical signal fragments from the target individual based on the trigger timestamps, time-locked acquisition of the stimulus-evoked signal is achieved, avoiding interference from asynchronous noise. Furthermore, based on the bioelectrical signal fragments, peripheral electromyographic evoked response values ​​at different pulse intensities are calculated, enabling a quantitative assessment of the stimulus-induced peripheral nerve response. By determining event-related potential data at the same pulse intensity, a quantitative assessment of the stimulus-induced central nervous system response is achieved. Finally, by determining the current test pulse intensity as the objective perception threshold when the peripheral electromyographic evoked response value exceeds a preset electromyographic threshold or the peak-to-peak value of the event-related potential waveform exceeds a preset evoked potential threshold, an objective and quantitative calibration of the user's perception threshold is achieved, providing a precise reference unit for subsequent personalized stimulation parameter settings.

[0009] Furthermore, the step of acquiring historical regulatory data of the target individual and determining a regulatory mode based on the historical regulatory data includes a first mode and a second mode, comprising: Obtain the historical usage records of the target individual, including at least the first use time and the interval between uses; When the target individual is using the treatment for the first time, or when the interval exceeds a preset period, the treatment mode is determined to be the first mode; Otherwise, the adjustment mode is determined to be the second mode.

[0010] This invention establishes a data foundation for user usage trajectories by acquiring the historical usage records of the target individual. By limiting the historical usage records to include at least the first use time and the interval time, key time features for pattern determination are extracted. When the target individual is using the technology for the first time or the interval time exceeds a preset period, the adjustment mode is determined to be the first mode, ensuring that new users or users who have not used the technology for a long time can enter the novice adaptation stage and avoid discomfort caused by directly using the mature intensity. When the above conditions are not met, the adjustment mode is determined to be the second mode, realizing the rapid entry of regular users into the mature treatment stage and improving the adjustment efficiency.

[0011] Furthermore, the step of controlling the output adjustment signal according to the upper limit of output intensity and the preset ramp-up algorithm, performing pain feature detection based on the real-time bioelectrical signal acquired by the first terminal, and controlling the output intensity of the second terminal to regress when pain features are detected includes: The output intensity of the second terminal is controlled to increase within the upper limit of the output intensity based on a preset step size. During the process of increasing output intensity, the real-time EEG signal and real-time EMG signal collected by the first terminal are acquired; Pain feature detection is performed based on the real-time EEG and real-time EMG signals. When pain features are detected, the output intensity of the second terminal is controlled to revert to the previous pain-free level.

[0012] This invention achieves a step-by-step, gradual increase in stimulation intensity by controlling the output intensity of the second terminal within a preset step size, ensuring a smooth and controllable escalation process. Subsequently, by acquiring real-time EEG and EMG signals from the first terminal during the output intensity increase, a real-time monitoring channel for multimodal physiological signals is established, providing a multidimensional data foundation for pain detection. Furthermore, by detecting pain features based on real-time EEG and EMG signals, a comprehensive discrimination of pain is achieved from both peripheral and central nervous system responses, improving the accuracy and reliability of pain recognition. Finally, by controlling the output intensity of the second terminal to revert to the previous pain-free level upon detecting pain features, an immediate safety protection mechanism is implemented, ensuring that the user always receives intervention within a comfortable threshold range.

[0013] Furthermore, the step of acquiring resting-period electrical signals based on the first terminal, and performing a dual-state assessment by combining a preset general threshold and a preset individual historical baseline to obtain a target intensity; controlling the output intensity of the second terminal to increase towards the target intensity, and dynamically adjusting the output intensity of the second terminal according to the real-time bioelectrical signals acquired by the first terminal during the output process, includes: The first terminal is controlled to collect resting EEG signals during the silent period before the electrical stimulation is initiated, and the current state index is calculated based on the resting EEG signals. The current state index is compared with a preset general threshold. If it exceeds the general threshold, it is marked as a high-pressure state. If the general threshold is not exceeded, the deviation of the current state index from the individual's historical baseline is calculated. If the deviation exceeds a preset deviation threshold, it is marked as a latent fatigue state. Based on the markers of the high-pressure state or the latent fatigue state, the corresponding target pulse intensity is matched from a preset mapping table; The output intensity of the second terminal is controlled to start from zero and increase linearly towards the target pulse intensity according to a preset gradual increase slope; During the increasing output intensity process, pain feature detection is performed based on the real-time bioelectric signal acquired by the first terminal, and the output intensity of the second terminal is controlled to decrease when pain features are detected.

[0014] This invention establishes a baseline of physiological state before intervention by controlling a first terminal to collect resting EEG signals during the silent period before electrical stimulation is initiated, providing a reference for subsequent assessment. Subsequently, a current state index is calculated using the resting EEG signals, achieving a quantitative representation of the user's current arousal level. Next, by comparing the current state index with a preset universal threshold, absolute stress state identification based on big data is achieved. When the universal threshold is exceeded, it is marked as a high-stress state, completing the first level of state determination. By calculating the deviation of the current state index from the individual's historical baseline when it does not exceed the universal threshold, a quantitative analysis of latent fatigue state is achieved. When the deviation exceeds a preset deviation threshold, it is marked as... The condition was marked as a latent fatigue state, completing the second stage of state determination. Then, by matching the corresponding target pulse intensity from a preset mapping table based on the markers of the high-pressure state or latent fatigue state, adaptive prescription generation based on the dual assessment results was achieved. Thus, by controlling the output intensity of the second terminal to linearly increase from zero to the target pulse intensity according to a preset gradual increase slope, a smooth and comfortable stimulation intervention process was ensured. By detecting pain features based on real-time bioelectrical signals acquired by the first terminal during the output intensity increase process, real-time safety monitoring of the treatment process was achieved. By controlling the output intensity of the second terminal to regress when pain features are detected, a dynamic safety guarantee mechanism was formed throughout the entire treatment process.

[0015] Secondly, the present invention provides a sleep regulation system, comprising a first terminal, a second terminal, and a control module, wherein the first terminal and the second terminal are disposed on the head of the target individual, and the control module is connected to the first terminal and the second terminal respectively, and the control module is used for: The second terminal outputs a pulse signal to the target individual, while the first terminal collects the first electrical signal of the target individual and determines the objective perception threshold of the target individual based on the first electrical signal. Acquire historical regulation data of the target individual, and determine the regulation mode based on the historical regulation data. The regulation mode includes a first mode and a second mode. When the adjustment mode is the first mode, the upper limit of the output intensity of the second terminal is set based on the objective perception threshold, the output adjustment signal is controlled according to the upper limit of the output intensity and the preset ramping algorithm, pain feature detection is performed based on the real-time bioelectric signal obtained by the first terminal, and the output intensity of the second terminal is controlled to fall back when pain feature is detected. When the adjustment mode is the second mode, the target intensity is obtained by combining the resting period electrical signal collected by the first terminal with a preset general threshold and a preset individual historical baseline for dual state evaluation; the output intensity of the second terminal is controlled to increase toward the target intensity, and the output intensity of the second terminal is dynamically adjusted according to the real-time bioelectrical signal collected by the first terminal during the output process.

[0016] Furthermore, the control module is used to output a pulse signal to the target individual based on the second terminal, and simultaneously acquire a first electrical signal of the target individual based on the first terminal, and determine the objective perception threshold of the target individual based on the first electrical signal, including: The second terminal is controlled to output a preset test pulse sequence to the target individual, and the trigger timestamp of each test pulse in the test pulse sequence is recorded; The first terminal is controlled to collect bioelectrical signal fragments of the target individual based on the trigger timestamp; Based on the bioelectric signal fragments, peripheral electromyographic evoked response values ​​with different pulse intensities were calculated, and event-related potential data under the same pulse intensity were determined; When the peripheral electromyographic evoked response value exceeds a preset electromyographic threshold, or the peak-to-peak value of the event-related potential data exceeds a preset evoked potential threshold, the pulse intensity of the current test pulse is determined as the objective perception threshold.

[0017] Furthermore, the control module is used to acquire historical regulation data of the target individual, and determine the regulation mode based on the historical regulation data. The regulation mode includes a first mode and a second mode, including: Obtain the historical usage records of the target individual, including at least the first use time and the interval between uses; When the target individual is using the treatment for the first time, or when the interval exceeds a preset period, the treatment mode is determined to be the first mode; Otherwise, the adjustment mode is determined to be the second mode.

[0018] Furthermore, the control module is used to control the output adjustment signal according to the upper limit of the output intensity and the preset ramp-up algorithm, to perform pain feature detection based on the real-time bioelectrical signal acquired by the first terminal, and to control the output intensity of the second terminal to regress when pain features are detected, including: The output intensity of the second terminal is controlled to increase within the upper limit of the output intensity based on a preset step size. During the process of increasing output intensity, the real-time EEG signal and real-time EMG signal collected by the first terminal are acquired; Pain feature detection is performed based on the real-time EEG and real-time EMG signals. When pain features are detected, the output intensity of the second terminal is controlled to revert to the previous pain-free level.

[0019] Furthermore, the control module is used to acquire resting-period electrical signals based on the first terminal, and to perform a dual-state assessment by combining a preset general threshold and a preset individual historical baseline to obtain a target intensity; control the output intensity of the second terminal to increase towards the target intensity, and dynamically adjust the output intensity of the second terminal according to the real-time bioelectrical signals acquired by the first terminal during the output process, including: The first terminal is controlled to collect resting EEG signals during the silent period before the electrical stimulation is initiated, and the current state index is calculated based on the resting EEG signals. The current state index is compared with a preset general threshold. If it exceeds the general threshold, it is marked as a high-pressure state. If the general threshold is not exceeded, the deviation of the current state index from the individual's historical baseline is calculated. If the deviation exceeds a preset deviation threshold, it is marked as a latent fatigue state. Based on the markers of the high-pressure state or the latent fatigue state, the corresponding target pulse intensity is matched from a preset mapping table; The output intensity of the second terminal is controlled to start from zero and increase linearly towards the target pulse intensity according to a preset gradual increase slope; During the increasing output intensity process, pain feature detection is performed based on the real-time bioelectric signal acquired by the first terminal, and the output intensity of the second terminal is controlled to decrease when pain features are detected. Attached Figure Description

[0020] Figure 1 A flowchart illustrating a sleep regulation method provided in an embodiment of the present invention. Figure 2 This is a schematic diagram of a structure for strength ramping, as provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of a dual-state evaluation method provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of a sleep regulation system according to an embodiment of the present invention. Detailed Implementation

[0021] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0022] The terms "first" and "second," etc., in the specification, claims, and drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such processes, methods, products, or apparatus.

[0023] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0024] Example 1 See Figure 1 , Figure 1 This is a flowchart illustrating a sleep regulation method provided by an embodiment of the present invention. The present invention provides a sleep regulation method applicable to a sleep regulation system including a first terminal and a second terminal, wherein the first terminal and the second terminal are disposed on the head of the target individual, and includes steps 101 to 104, as detailed below: Step 101: Output a pulse signal to the target individual based on the second terminal, and simultaneously collect the first electrical signal of the target individual based on the first terminal, and determine the objective perception threshold of the target individual based on the first electrical signal; In this embodiment, the step of outputting a pulse signal to the target individual based on the second terminal, simultaneously acquiring a first electrical signal of the target individual based on the first terminal, and determining the objective perception threshold of the target individual based on the first electrical signal includes: The second terminal is controlled to output a preset test pulse sequence to the target individual, and the trigger timestamp of each test pulse in the test pulse sequence is recorded; The first terminal is controlled to collect bioelectrical signal fragments of the target individual based on the trigger timestamp; Based on the bioelectric signal fragments, peripheral electromyographic evoked response values ​​with different pulse intensities were calculated, and event-related potential data under the same pulse intensity were determined; When the peripheral electromyographic evoked response value exceeds a preset electromyographic threshold, or the peak-to-peak value of the event-related potential data exceeds a preset evoked potential threshold, the pulse intensity of the current test pulse is determined as the objective perception threshold.

[0025] In this embodiment, the system controls the second terminal to output a test pulse sequence to the target individual. The intensity of the test pulse sequence gradually increases according to a preset step size, and the system records the trigger timestamp of each test pulse. The system controls the first terminal to extract a bioelectrical signal segment within a preset time window after stimulation, based on the trigger timestamp. The preset time window is set according to the response latency of the target physiological signal and includes a first window for detecting peripheral electromyographic evoked responses and a second window for detecting event-related potentials (ERPs). Subsequently, the system performs dual feature analysis based on the extracted bioelectrical signal segments: on the one hand, it calculates the signal energy ratio of the post-stimulation window to the pre-stimulation window as the peripheral electromyographic evoked response value; on the other hand, it averages multiple sets of EEG signal segments at the same pulse intensity and extracts the peak-to-peak amplitude of the evoked potential component in the average waveform as the ERP data. When the peripheral electromyographic evoked response value exceeds a preset electromyographic threshold, or the peak-to-peak amplitude of the ERP data exceeds a preset evoked potential threshold, the system determines the pulse intensity of the current test pulse as the objective perception threshold.

[0026] In this embodiment, firstly, the system controls the second terminal to output a series of linearly increasing test pulse sequences to the target individual. The intensity of the test pulse sequence increases smoothly in steps of 0.1 mA per second to ensure the continuity and comfort of the stimulus changes. Simultaneously, the system accurately records the time of emission of each test pulse in the test pulse sequence, denoted as a trigger timestamp.

[0027] Secondly, the system controls the first terminal to extract bioelectrical signal segments within a preset time window after stimulation, based on the trigger timestamp. Specifically, for the detection of electromyographic evoked responses, data from a window of 10 to 50 milliseconds after stimulation is extracted, covering the typical latency of the postauricular muscle reflex; for the detection of event-related potentials, data from a window of 50 to 300 milliseconds after stimulation is extracted, covering the typical latency of the N100 and P200 components of auditory or somatosensory evoked potentials.

[0028] Then, the baseline root mean square (RMS) value of the bioelectrical signal in the pre-stimulation window was calculated, and the response RMS value was calculated by extracting the bioelectrical signal in the post-stimulation window. The energy ratio of the response to the baseline was also calculated as the peripheral electromyographic evoked response value. Furthermore, multiple sets of EEG signal segments under the same pulse intensity were superimposed and averaged to eliminate random background noise, resulting in an average waveform. The peak-to-peak amplitudes of the N100 and P200 components in this average waveform were extracted as event-related potential (ERP) data.

[0029] Finally, when the peripheral electromyographic evoked response value exceeds a preset electromyographic threshold, preferably 1.5, meaning the electromyographic energy after stimulation is 50% higher than the resting baseline, it indicates that the stimulation has effectively activated the peripheral neural pathway; or, when the peak-to-peak value of the event-related potential data exceeds a preset evoked potential threshold, preferably 3 microvolts, this threshold is set based on the typical physiological amplitude range of the N100 component, capable of distinguishing effective evoked EEG from residual random background noise. When either condition is met, the system immediately stops outputting the test pulse and determines the pulse intensity of the current test pulse as the objective perception threshold of the target individual, while storing this threshold in the target individual's physiological record as a reference unit for subsequent personalized stimulation parameter settings.

[0030] In this embodiment, a standardized stimulation procedure for threshold calibration is established by controlling the second terminal to output a preset test pulse sequence to the target individual. Subsequently, a time reference for the stimulation event is established by recording the trigger timestamp of each test pulse in the test pulse sequence. Then, by controlling the first terminal to acquire bioelectrical signal fragments of the target individual based on the trigger timestamps, time-locked acquisition of the stimulus-evoked signal is achieved, avoiding interference from asynchronous noise. Furthermore, peripheral electromyographic evoked response values ​​at different pulse intensities are calculated based on the bioelectrical signal fragments, enabling a quantitative assessment of the stimulus-induced peripheral nerve response. By determining the event-related potential data under the same pulse intensity, a quantitative assessment of the stimulus-induced central nervous system response is achieved. Finally, when the peripheral electromyographic evoked response value exceeds a preset electromyographic threshold or the peak-to-peak value of the event-related potential waveform exceeds a preset evoked potential threshold, the current test pulse intensity is determined as the objective perception threshold, achieving an objective and quantitative calibration of the user's perception threshold and providing a precise reference unit for subsequent personalized stimulation parameter settings.

[0031] Step 102: Obtain historical regulation data of the target individual, and determine the regulation mode based on the historical regulation data. The regulation mode includes a first mode and a second mode. In this embodiment, the step of acquiring historical conditioning data of the target individual and determining a conditioning mode based on the historical conditioning data includes a first mode and a second mode, comprising: Obtain the historical usage records of the target individual, including at least the first use time and the interval between uses; When the target individual is using the treatment for the first time, or when the interval exceeds a preset period, the treatment mode is determined to be the first mode; Otherwise, the adjustment mode is determined to be the second mode.

[0032] In this embodiment, the system first accesses local storage or a cloud database to obtain the historical usage records of the target individual. The historical usage records include at least the timestamp of the user's first use and the timestamp of the most recent use. The system calculates the interval time based on the current time and the timestamp of the most recent use, and this interval time is used to characterize the duration of the user's interrupted use.

[0033] In this embodiment, when the target user is determined to be a first-time user (i.e., there are no usage records in the historical usage history), the system determines the adjustment mode as the first mode. This mode corresponds to the novice adaptation stage and is used to perform gradual ramp-up control with limited intensity. Alternatively, when the target user is not a first-time user but the interval exceeds a preset period, wherein the preset period is set according to the physiological laws of neural adaptation, preferably fourteen days, meaning that after the user has interrupted use for more than two weeks, the sensitivity of their nerve endings to electrical stimulation may have recovered to the initial level, the system also determines the adjustment mode as the first mode to ensure that the user can smoothly transition when resuming use and avoid discomfort caused by direct exposure to the previously effective intensity.

[0034] In this embodiment, when the target individual is not using the treatment for the first time and the interval does not exceed the preset period, the system determines the treatment mode as the second mode. This mode corresponds to the mature treatment stage, indicating that the user's neural adaptation has not yet subsided. The system can directly execute a closed-loop intervention process based on their historical physiological records, thereby skipping the adaptation period and improving treatment efficiency. Through the above-mentioned differentiated mode determination based on historical usage records, the system achieves accurate identification and adaptive guidance of the user's state.

[0035] In this embodiment, a data foundation for user usage trajectory is established by acquiring the historical usage records of the target individual. By limiting the historical usage records to include at least the first use time and the interval time, key time features for pattern determination are extracted. When the target individual is using the service for the first time or the interval time exceeds a preset period, the adjustment mode is determined to be the first mode, ensuring that new users or users who have not used the service for a long time can enter the novice adaptation stage and avoid discomfort caused by directly using the mature intensity. When the above conditions are not met, the adjustment mode is determined to be the second mode, realizing the rapid entry of regular users into the mature treatment stage and improving the adjustment efficiency.

[0036] Step 103: When the adjustment mode is the first mode, the upper limit of the output intensity of the second terminal is set based on the objective perception threshold, the output adjustment signal is controlled according to the upper limit of the output intensity and the preset ramping algorithm, pain feature detection is performed based on the real-time bioelectric signal obtained by the first terminal, and the output intensity of the second terminal is controlled to fall back when pain feature is detected. In this embodiment, controlling the output adjustment signal according to the upper limit of output intensity and a preset ramp-up algorithm, performing pain feature detection based on the real-time bioelectrical signal acquired by the first terminal, and controlling the output intensity of the second terminal to regress when pain features are detected includes: The output intensity of the second terminal is controlled to increase within the upper limit of the output intensity based on a preset step size. During the process of increasing output intensity, the real-time EEG signal and real-time EMG signal collected by the first terminal are acquired; Pain feature detection is performed based on the real-time EEG and real-time EMG signals. When pain features are detected, the output intensity of the second terminal is controlled to revert to the previous pain-free level.

[0037] In this embodiment, the system controls the output intensity of the second terminal to increase in a stepwise manner within the upper limit of the output intensity based on a preset step size, thereby achieving a gradual increase in stimulation intensity and avoiding user discomfort caused by sudden changes in intensity. During the increase in output intensity, the system simultaneously acquires real-time EEG and real-time EMG signals collected by the first terminal to construct a multimodal physiological monitoring channel. Based on the real-time EEG and real-time EMG signals, the system performs pain feature detection and comprehensively evaluates the user's physiological response to the current stimulation intensity. When physiological features representing pain are detected, the system immediately controls the output intensity of the second terminal to revert to the previous pain-free level, forming an immediate safety protection mechanism. Through the above closed-loop control, the system can gradually explore and establish the user's personalized tolerance intensity boundary while ensuring user comfort.

[0038] In this embodiment, the system first acquires the resting bioelectrical signals collected by the first terminal before the electrical stimulation is initiated, and calculates the resting electromyographic baseline and relaxation baseline values. Based on the objective perception threshold, the system sets the upper limit of the output intensity of the second terminal to be between 50% and 80% of the objective perception threshold. This intensity is lower than the user's objective perception threshold and falls within the subthreshold stimulation range. Furthermore, the system controls the output intensity of the second terminal to increase stepwise within the upper limit of the output intensity in preset steps of 0.1 mA.

[0039] In this embodiment, during the increasing output intensity process, the system continuously acquires real-time EEG and real-time EMG signals collected by the first terminal, calculates the energy ratio of the Alpha and Beta bands in the real-time EEG signals as the physiological relaxation state value, and calculates the root mean square value of the real-time EMG signals. When the physiological relaxation state value is not lower than the relaxation baseline value and the root mean square value of the real-time EMG signals is not higher than the resting threshold set based on the resting EMG baseline, the system records that day as an effective adaptation day. When the cumulative effective adaptation days reach three days, the upper limit of the output intensity is increased by a gradient, which is 10% of the objective perception threshold.

[0040] In this embodiment, the system performs time-locked analysis on the real-time electromyography (EMG) signals and the real-time electroencephalography (EEG) signals to detect pain characteristics. Using the trigger timestamp of the output pulse from the second terminal as a reference, it detects whether there is an EMG burst or a Beta band energy surge synchronized with the pulse time within the stimulation window. When the EMG burst is detected (i.e., the root mean square value of EMG after stimulation exceeds three times the resting EMG baseline), or the Beta band energy surge is detected (i.e., the Beta band energy after stimulation increases by more than 50% compared to the resting baseline), the system determines it as a pain trigger, immediately controls the output intensity of the second terminal to revert to the previous pain-free level, and locks this intensity as the maximum permissible treatment intensity for the current stage. Through this method, the system achieves progressive training of novice users' neural adaptability while ensuring user comfort and safety.

[0041] Please refer to Figure 2 , Figure 2 This is a schematic diagram of a structure for strength ramping, as provided in an embodiment of the present invention.

[0042] In one specific embodiment, the novice adaptation period includes two stages: a subthreshold desensitization period and a suprathreshold climbing period. The system establishes an intensity benchmark based on the user's objective perception threshold and achieves gradual intensity improvement through a check-in mechanism for effective adaptation days.

[0043] First, during the subthreshold desensitization period, the system locks the upper limit of the output intensity of the second terminal to between 50% and 80% of the user's objectively perceived threshold. During this phase, the system continuously records the user's usage. When the user reaches a physiologically relaxed state for three consecutive days—that is, when the energy ratio of the Alpha band to the Beta band during stimulation is not lower than the baseline value of relaxation and the electromyography level is not higher than the resting threshold—the system determines that the effective adaptation days have been accumulated, and then automatically enters the suprathreshold climbing period.

[0044] During the suprathreshold climbing phase, the system increases the upper limit of output intensity at a rate of one gradient per day, with each gradient representing 10% of the user's objectively perceived threshold. If the user's objectively perceived threshold is 200 microamps, the intensity climbing process during the suprathreshold climbing phase is as follows: on day 4, the upper limit of output intensity increases to 90% of the objectively perceived threshold, i.e., 180 microamps; on day 5, it increases to 100%, i.e., 200 microamps; on day 6, it increases to 110%, i.e., 220 microamps; and on day 7, it increases to 120%, i.e., 240 microamps. During the climbing process, the system continuously monitors the user's real-time bioelectrical signals. Once it detects pain characteristics such as electromyographic bursts or surges in Beta frequency energy, it immediately triggers a circuit breaker mechanism, reverting the output intensity back to the previous pain-free level and locking that intensity as the maximum permissible treatment intensity, while simultaneously extending the adaptation period accordingly.

[0045] In this embodiment, while ensuring user comfort and safety, the stimulation intensity is gradually increased from the subthreshold level to the effective treatment range, helping new users to establish neural adaptation to electrical stimulation and significantly reducing discomfort and dropout rate during initial use.

[0046] In this embodiment, by controlling the output intensity of the second terminal to increase within the upper limit of the output intensity based on a preset step size, a stepwise gradual increase in stimulation intensity is achieved, ensuring a smooth and controllable climbing process. Subsequently, by acquiring real-time EEG and EMG signals collected by the first terminal during the output intensity increase process, a real-time monitoring channel for multimodal physiological signals is established, providing a multidimensional data foundation for pain detection. Furthermore, by detecting pain features based on real-time EEG and EMG signals, a comprehensive discrimination of pain is achieved from both peripheral nerve response and central nerve response dimensions, improving the accuracy and reliability of pain recognition. By controlling the output intensity of the second terminal to revert to the previous pain-free level when pain features are detected, an immediate safety protection mechanism is implemented, ensuring that the user always receives intervention within the comfort threshold range.

[0047] Step 104: When the adjustment mode is the second mode, the target intensity is obtained by combining the resting period electrical signal collected by the first terminal with a preset general threshold and a preset individual historical baseline for dual state evaluation; the output intensity of the second terminal is controlled to increase towards the target intensity, and the output intensity of the second terminal is dynamically adjusted according to the real-time bioelectrical signal collected by the first terminal during the output process.

[0048] In this embodiment, the step of acquiring resting-period electrical signals based on the first terminal and performing a dual-state assessment by combining a preset general threshold and a preset individual historical baseline to obtain a target intensity; controlling the output intensity of the second terminal to increase towards the target intensity, and dynamically adjusting the output intensity of the second terminal according to the real-time bioelectrical signals acquired by the first terminal during the output process, includes: The first terminal is controlled to collect resting EEG signals during the silent period before the electrical stimulation is initiated, and the current state index is calculated based on the resting EEG signals. The current state index is compared with a preset general threshold. If it exceeds the general threshold, it is marked as a high-pressure state. If the general threshold is not exceeded, the deviation of the current state index from the individual's historical baseline is calculated. If the deviation exceeds a preset deviation threshold, it is marked as a latent fatigue state. Based on the markers of the high-pressure state or the latent fatigue state, the corresponding target pulse intensity is matched from a preset mapping table; The output intensity of the second terminal is controlled to start from zero and increase linearly towards the target pulse intensity according to a preset gradual increase slope; During the increasing output intensity process, pain feature detection is performed based on the real-time bioelectric signal acquired by the first terminal, and the output intensity of the second terminal is controlled to decrease when pain features are detected.

[0049] In this embodiment, the system controls the first terminal to collect resting EEG signals during the silent period before the electrical stimulation is initiated, and calculates the current state index based on the resting EEG signals. The current state index is used to quantitatively characterize the user's current level of cortical arousal.

[0050] In this embodiment, the system compares the current state index with a preset general threshold. If it exceeds the general threshold, it is marked as a high-stress state, which indicates that the user's absolute stress level has exceeded the medical norm range. If it does not exceed the general threshold, the system further calculates the deviation of the current state index from the individual's historical baseline. If the deviation exceeds a preset deviation threshold, it is marked as a latent fatigue state, which indicates that although the user has not reached an absolute high-stress level, their physiological state has significantly deviated from their normal state.

[0051] In this embodiment, the system matches the corresponding target pulse intensity from a preset mapping table based on the markers of the high-pressure state or the latent fatigue state, thereby achieving precise prescription generation based on the individual's real-time state. Subsequently, the system controls the output intensity of the second terminal to linearly increase from zero to the target pulse intensity according to a preset gradual increase slope, ensuring a smooth and comfortable stimulation intervention process. During the output intensity increase process, the system performs pain feature detection based on the real-time bioelectrical signals acquired by the first terminal, and controls the output intensity of the second terminal to regress when pain features are detected, forming a dynamic safety assurance mechanism throughout the entire treatment process. Through the above dual evaluation and closed-loop regulation, the system achieves a complete closed loop from state recognition to safe intervention.

[0052] Please refer to Figure 3 , Figure 3 This is a schematic diagram of a dual-state evaluation method provided in an embodiment of the present invention.

[0053] As a specific example of an embodiment of the present invention, the first terminal is controlled to continuously collect resting EEG signals for 60 seconds during the silent period before the electrical stimulation is initiated. The collected resting EEG signals are subjected to a Fast Fourier Transform (FFT) to calculate the power of the Beta band (13 Hz to 30 Hz) and the power of the Alpha band (8 Hz to 13 Hz). The ratio of these two values ​​is used as the current state index; a higher index value indicates greater tension and anxiety in the user, while a lower value indicates greater relaxation.

[0054] Subsequently, the current state index is compared with a preset universal threshold of 2.0. If the current state index exceeds 2.0, it is marked as a high-stress state, and a strong sedation mode is matched, corresponding to a higher intensity target pulse. If the current state index does not exceed 2.0, the system performs a second comparison, calculating the deviation of the current state index from the individual's historical baseline. The individual historical baseline is the average lowest state index recorded by the system during the user's historical use when in a deep sleep or deep relaxation state. The deviation is calculated by dividing the difference between the current state index and the individual historical baseline by the individual historical baseline and then multiplying by 100%.

[0055] If the deviation exceeds the preset deviation threshold by 30%, it is marked as a latent fatigue state and matched with a mild adjustment mode, corresponding to a target pulse of medium intensity.

[0056] If the deviation is less than 30%, it is marked as normal and matched to maintain the sleep aid mode, corresponding to a lower intensity target pulse.

[0057] Then, after matching the corresponding target pulse intensity from the preset mapping table according to the marking status, the output intensity of the second terminal is controlled to start from zero and linearly increase towards the target pulse intensity at a gradual ramp rate of 0.1 mA per second.

[0058] In this embodiment, during the output intensity increase process, the system uses the trigger timestamp of the second terminal output pulse as a reference to extract electromyographic signal segments from 10 to 50 milliseconds after stimulation and electroencephalogram (EEG) signal segments from 50 to 300 milliseconds after stimulation, calculates the root mean square value of the electromyographic signal segments and the energy change rate of the Beta band in the EEG signal segments relative to the resting baseline.

[0059] When the root mean square value of the electromyographic signal segment exceeds three times the resting electromyographic baseline, or the energy change rate of the Beta band exceeds 50%, the system determines that pain has been triggered. It immediately controls the output intensity of the second terminal to decrease by 0.2 mA and locks the intensity so that it does not increase further, ensuring that the user can complete the intervention in a painless and comfortable state. This achieves accurate identification of the user's physiological state and safe closed-loop control of the output intensity.

[0060] In this embodiment, by controlling the first terminal to collect resting EEG signals during the silent period before the initiation of electrical stimulation, a baseline of physiological state before intervention is established, providing a reference benchmark for subsequent evaluation. Subsequently, the current state index is calculated using the resting EEG signals, achieving a quantitative representation of the user's current arousal level. Then, by comparing the current state index with a preset universal threshold, absolute stress state identification based on big data is achieved. When the universal threshold is exceeded, it is marked as a high-stress state, completing the first level of state determination. By calculating the deviation of the current state index from the individual's historical baseline when it does not exceed the universal threshold, a quantitative analysis of latent fatigue state is achieved. When the deviation exceeds a preset deviation threshold... This is then marked as a latent fatigue state, completing the second stage of state determination. Furthermore, by matching the corresponding target pulse intensity from a preset mapping table based on the high-pressure state or latent fatigue state markers, adaptive prescription generation based on dual evaluation results is achieved. Thus, by controlling the output intensity of the second terminal to linearly increase from zero to the target pulse intensity according to a preset gradual increase slope, a smooth and comfortable stimulation intervention process is ensured. By detecting pain features based on real-time bioelectrical signals acquired by the first terminal during the output intensity increase process, real-time safety monitoring of the treatment process is achieved. By controlling the output intensity of the second terminal to regress when pain features are detected, a dynamic safety guarantee mechanism is formed throughout the entire treatment process.

[0061] Please refer to Figure 4 , Figure 4 This is a schematic diagram of a sleep regulation system according to an embodiment of the present invention.

[0062] In this embodiment, the system includes a first terminal, a second terminal, and a smart terminal. The first terminal and the second terminal are worn on the left and right ears of the target individual, respectively. They establish a wireless connection with the control module via a Bluetooth communication module, forming a closed-loop control circuit.

[0063] As a specific example of an embodiment of the present invention, the first terminal and the second terminal are respectively presented in the form of earphones, and are respectively connected to the control module via wireless connection.

[0064] The first terminal is the treatment device, typically worn on the right ear, and integrates a tVNS pulse generator, a current feedback circuit, and a Bluetooth communication module. The tVNS pulse generator outputs transcutaneous vagus nerve electrical stimulation pulses, the current feedback circuit monitors the stability of the output current, and the Bluetooth communication module receives stimulation commands from the smart terminal and reports its operating status.

[0065] The second terminal is a monitoring device, typically worn in the left ear, and integrates an EEG acquisition module, an EEG signal processing module, and a Bluetooth communication module. The EEG acquisition module collects the user's bioelectrical signals through flexible dry electrodes placed on the earphone shell. The EEG signal processing module filters, amplifies, and performs analog-to-digital conversion on the acquired signals. The Bluetooth communication module is used to transmit the processed bioelectrical signals to the smart terminal in real time.

[0066] The control module is a smart terminal, specifically a smartphone or cloud server, which internally stores physiological baseline data and runs adaptive decision-making algorithms and long-term models. The smart terminal receives bioelectrical signals uploaded by the second terminal, performs state assessment and prescription generation through the adaptive decision-making algorithm, analyzes historical data and iterates parameters through the long-term model, and sends control commands to the first terminal via a Bluetooth communication module.

[0067] Through the above heterogeneous design, the first terminal and the second terminal utilize the human head tissue as a natural high impedance barrier to achieve physical decoupling of the stimulation signal and the acquisition signal, thereby supporting real-time closed-loop control of simultaneous stimulation and monitoring.

[0068] This invention provides a sleep regulation system, including a first terminal, a second terminal, and a control module. The first and second terminals are disposed on the head of the target individual. The control module is connected to both the first and second terminals, and is used for: The second terminal outputs a pulse signal to the target individual, while the first terminal collects the first electrical signal of the target individual and determines the objective perception threshold of the target individual based on the first electrical signal. Acquire historical regulation data of the target individual, and determine the regulation mode based on the historical regulation data. The regulation mode includes a first mode and a second mode. When the adjustment mode is the first mode, the upper limit of the output intensity of the second terminal is set based on the objective perception threshold, the output adjustment signal is controlled according to the upper limit of the output intensity and the preset ramping algorithm, pain feature detection is performed based on the real-time bioelectric signal obtained by the first terminal, and the output intensity of the second terminal is controlled to fall back when pain feature is detected. When the adjustment mode is the second mode, the target intensity is obtained by combining the resting period electrical signal collected by the first terminal with a preset general threshold and a preset individual historical baseline for dual state evaluation; the output intensity of the second terminal is controlled to increase toward the target intensity, and the output intensity of the second terminal is dynamically adjusted according to the real-time bioelectrical signal collected by the first terminal during the output process.

[0069] In this embodiment, the control module is used to output a pulse signal to the target individual based on the second terminal, and simultaneously acquire a first electrical signal of the target individual based on the first terminal, and determine the objective perception threshold of the target individual based on the first electrical signal, including: The second terminal is controlled to output a preset test pulse sequence to the target individual, and the trigger timestamp of each test pulse in the test pulse sequence is recorded; The first terminal is controlled to collect bioelectrical signal fragments of the target individual based on the trigger timestamp; Based on the bioelectric signal fragments, peripheral electromyographic evoked response values ​​with different pulse intensities were calculated, and event-related potential data under the same pulse intensity were determined; When the peripheral electromyographic evoked response value exceeds a preset electromyographic threshold, or the peak-to-peak value of the event-related potential data exceeds a preset evoked potential threshold, the pulse intensity of the current test pulse is determined as the objective perception threshold.

[0070] In this embodiment, the control module is used to acquire historical regulation data of the target individual, and determine a regulation mode based on the historical regulation data. The regulation mode includes a first mode and a second mode, including: Obtain the historical usage records of the target individual, including at least the first use time and the interval between uses; When the target individual is using the treatment for the first time, or when the interval exceeds a preset period, the treatment mode is determined to be the first mode; Otherwise, the adjustment mode is determined to be the second mode.

[0071] In this embodiment, the control module is used to control the output adjustment signal according to the upper limit of the output intensity and a preset ramp-up algorithm, to perform pain feature detection based on the real-time bioelectrical signal acquired by the first terminal, and to control the output intensity of the second terminal to regress when pain features are detected, including: The output intensity of the second terminal is controlled to increase within the upper limit of the output intensity based on a preset step size. During the process of increasing output intensity, the real-time EEG signal and real-time EMG signal collected by the first terminal are acquired; Pain feature detection is performed based on the real-time EEG and real-time EMG signals. When pain features are detected, the output intensity of the second terminal is controlled to revert to the previous pain-free level.

[0072] In this embodiment, the control module is used to collect resting period electrical signals based on the first terminal, and perform dual state assessment by combining a preset general threshold and a preset individual historical baseline to obtain a target intensity; control the output intensity of the second terminal to increase towards the target intensity, and dynamically adjust the output intensity of the second terminal according to the real-time bioelectrical signals collected by the first terminal during the output process, including: The first terminal is controlled to collect resting EEG signals during the silent period before the electrical stimulation is initiated, and the current state index is calculated based on the resting EEG signals. The current state index is compared with a preset general threshold. If it exceeds the general threshold, it is marked as a high-pressure state. If the general threshold is not exceeded, the deviation of the current state index from the individual's historical baseline is calculated. If the deviation exceeds a preset deviation threshold, it is marked as a latent fatigue state. Based on the markers of the high-pressure state or the latent fatigue state, the corresponding target pulse intensity is matched from a preset mapping table; The output intensity of the second terminal is controlled to start from zero and increase linearly towards the target pulse intensity according to a preset gradual increase slope; During the increasing output intensity process, pain feature detection is performed based on the real-time bioelectric signal acquired by the first terminal, and the output intensity of the second terminal is controlled to decrease when pain features are detected.

[0073] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A sleep regulation method, characterized in that, A sleep regulation system including a first terminal and a second terminal, wherein the first terminal and the second terminal are disposed on the head of the target individual, comprising: The second terminal outputs a pulse signal to the target individual, while the first terminal collects the first electrical signal of the target individual and determines the objective perception threshold of the target individual based on the first electrical signal. Acquire historical regulation data of the target individual, and determine the regulation mode based on the historical regulation data. The regulation mode includes a first mode and a second mode. When the adjustment mode is the first mode, the upper limit of the output intensity of the second terminal is set based on the objective perception threshold, the output adjustment signal is controlled according to the upper limit of the output intensity and the preset ramping algorithm, pain feature detection is performed based on the real-time bioelectric signal obtained by the first terminal, and the output intensity of the second terminal is controlled to fall back when pain feature is detected. When the adjustment mode is the second mode, the target intensity is obtained by combining the resting period electrical signal collected by the first terminal with a preset general threshold and a preset individual historical baseline for dual state evaluation; the output intensity of the second terminal is controlled to increase toward the target intensity, and the output intensity of the second terminal is dynamically adjusted according to the real-time bioelectrical signal collected by the first terminal during the output process.

2. The sleep regulation method as described in claim 1, characterized in that, The step of outputting a pulse signal to the target individual based on the second terminal, simultaneously acquiring a first electrical signal of the target individual based on the first terminal, and determining the objective perception threshold of the target individual based on the first electrical signal includes: The second terminal is controlled to output a preset test pulse sequence to the target individual, and the trigger timestamp of each test pulse in the test pulse sequence is recorded; The first terminal is controlled to collect bioelectrical signal fragments of the target individual based on the trigger timestamp; Based on the bioelectric signal fragments, peripheral electromyographic evoked response values ​​with different pulse intensities were calculated, and event-related potential data under the same pulse intensity were determined; When the peripheral electromyographic evoked response value exceeds a preset electromyographic threshold, or the peak-to-peak value of the event-related potential data exceeds a preset evoked potential threshold, the pulse intensity of the current test pulse is determined as the objective perception threshold.

3. The sleep regulation method as described in claim 2, characterized in that, The process involves acquiring historical conditioning data of the target individual, determining a conditioning mode based on the historical conditioning data, and the conditioning mode including a first mode and a second mode, comprising: Obtain the historical usage records of the target individual, including at least the first use time and the interval between uses; When the target individual is using the treatment for the first time, or when the interval exceeds a preset period, the treatment mode is determined to be the first mode; Otherwise, the adjustment mode is determined to be the second mode.

4. The sleep regulation method as described in claim 3, characterized in that, The step of controlling the output adjustment signal according to the upper limit of output intensity and a preset ramp-up algorithm, performing pain feature detection based on the real-time bioelectrical signal acquired by the first terminal, and controlling the output intensity of the second terminal to regress when pain features are detected includes: The output intensity of the second terminal is controlled to increase within the upper limit of the output intensity based on a preset step size. During the process of increasing output intensity, the real-time EEG signal and real-time EMG signal collected by the first terminal are acquired; Pain feature detection is performed based on the real-time EEG and real-time EMG signals. When pain features are detected, the output intensity of the second terminal is controlled to revert to the previous pain-free level.

5. A sleep regulation method as described in claim 4, characterized in that, The process involves acquiring resting-period electrical signals from the first terminal and performing a dual-state assessment using a preset general threshold and a preset individual historical baseline to obtain a target intensity; controlling the output intensity of the second terminal to increase towards the target intensity, and dynamically adjusting the output intensity of the second terminal during the output process based on the real-time bioelectrical signals acquired by the first terminal, including: The first terminal is controlled to collect resting EEG signals during the silent period before the electrical stimulation is initiated, and the current state index is calculated based on the resting EEG signals. The current state index is compared with a preset general threshold. If it exceeds the general threshold, it is marked as a high-pressure state. If the general threshold is not exceeded, the deviation of the current state index from the individual's historical baseline is calculated. If the deviation exceeds a preset deviation threshold, it is marked as a latent fatigue state. Based on the markers of the high-pressure state or the latent fatigue state, the corresponding target pulse intensity is matched from a preset mapping table; The output intensity of the second terminal is controlled to start from zero and increase linearly towards the target pulse intensity according to a preset gradual increase slope; During the increasing output intensity process, pain feature detection is performed based on the real-time bioelectric signal acquired by the first terminal, and the output intensity of the second terminal is controlled to decrease when pain features are detected.

6. A sleep regulation system, characterized in that, The system includes a first terminal, a second terminal, and a control module. The first and second terminals are positioned on the head of the target individual. The control module is connected to both the first and second terminals and is used for: The second terminal outputs a pulse signal to the target individual, while the first terminal collects the first electrical signal of the target individual and determines the objective perception threshold of the target individual based on the first electrical signal. Acquire historical regulation data of the target individual, and determine the regulation mode based on the historical regulation data. The regulation mode includes a first mode and a second mode. When the adjustment mode is the first mode, the upper limit of the output intensity of the second terminal is set based on the objective perception threshold, the output adjustment signal is controlled according to the upper limit of the output intensity and the preset ramping algorithm, pain feature detection is performed based on the real-time bioelectric signal obtained by the first terminal, and the output intensity of the second terminal is controlled to fall back when pain feature is detected. When the adjustment mode is the second mode, the target intensity is obtained by combining the resting period electrical signal collected by the first terminal with a preset general threshold and a preset individual historical baseline for dual state evaluation; the output intensity of the second terminal is controlled to increase toward the target intensity, and the output intensity of the second terminal is dynamically adjusted according to the real-time bioelectrical signal collected by the first terminal during the output process.

7. A sleep regulation system as described in claim 6, characterized in that, The control module is used to output a pulse signal to the target individual based on the second terminal, and simultaneously acquire a first electrical signal of the target individual based on the first terminal, and determine the objective perception threshold of the target individual based on the first electrical signal, including: The second terminal is controlled to output a preset test pulse sequence to the target individual, and the trigger timestamp of each test pulse in the test pulse sequence is recorded; The first terminal is controlled to collect bioelectrical signal fragments of the target individual based on the trigger timestamp; Based on the bioelectric signal fragments, peripheral electromyographic evoked response values ​​with different pulse intensities were calculated, and event-related potential data under the same pulse intensity were determined; When the peripheral electromyographic evoked response value exceeds a preset electromyographic threshold, or the peak-to-peak value of the event-related potential data exceeds a preset evoked potential threshold, the pulse intensity of the current test pulse is determined as the objective perception threshold.

8. A sleep regulation system as described in claim 7, characterized in that, The control module is used to acquire historical regulation data of the target individual, and determine the regulation mode based on the historical regulation data. The regulation mode includes a first mode and a second mode, including: Obtain the historical usage records of the target individual, including at least the first use time and the interval between uses; When the target individual is using the treatment for the first time, or when the interval exceeds a preset period, the treatment mode is determined to be the first mode; Otherwise, the adjustment mode is determined to be the second mode.

9. A sleep regulation system as described in claim 8, characterized in that, The control module is used to control the output adjustment signal according to the upper limit of the output intensity and a preset ramp-up algorithm, to perform pain feature detection based on the real-time bioelectrical signal acquired by the first terminal, and to control the output intensity of the second terminal to regress when pain features are detected, including: The output intensity of the second terminal is controlled to increase within the upper limit of the output intensity based on a preset step size. During the process of increasing output intensity, the real-time EEG signal and real-time EMG signal collected by the first terminal are acquired; Pain feature detection is performed based on the real-time EEG and real-time EMG signals. When pain features are detected, the output intensity of the second terminal is controlled to revert to the previous pain-free level.

10. A sleep regulation system as described in claim 9, characterized in that, The control module is used to collect resting period electrical signals based on the first terminal, and to perform dual state evaluation by combining a preset general threshold and a preset individual historical baseline to obtain the target intensity. Controlling the output intensity of the second terminal to increase towards the target intensity, and dynamically adjusting the output intensity of the second terminal during the output process based on the real-time bioelectrical signals collected by the first terminal, includes: The first terminal is controlled to collect resting EEG signals during the silent period before the electrical stimulation is initiated, and the current state index is calculated based on the resting EEG signals. The current state index is compared with a preset general threshold. If it exceeds the general threshold, it is marked as a high-pressure state. If the general threshold is not exceeded, the deviation of the current state index from the individual's historical baseline is calculated. If the deviation exceeds a preset deviation threshold, it is marked as a latent fatigue state. Based on the markers of the high-pressure state or the latent fatigue state, the corresponding target pulse intensity is matched from a preset mapping table; The output intensity of the second terminal is controlled to start from zero and increase linearly towards the target pulse intensity according to a preset gradual increase slope; During the increasing output intensity process, pain feature detection is performed based on the real-time bioelectric signal acquired by the first terminal, and the output intensity of the second terminal is controlled to decrease when pain features are detected.

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