A method and system for automatically determining the sleep state of a small mouse and automatically waking up

Abstract

The application discloses a kind of automatic determination of mouse sleep state and automatic wake-up method and system, method includes: the time domain feature of digital electroencephalogram signal of mouse in current analysis window, frequency domain feature, first power ratio and second power ratio are calculated;The preliminary sleep state judgment result of mouse in current analysis window is calculated;The final sleep state judgment result of mouse in current analysis window is calculated based on the preliminary sleep state judgment result of mouse in current analysis window;Determine whether the final sleep state judgment result of mouse in current analysis window is preset target sleep state: if yes, then determine whether the time that mouse maintains preset target sleep state reaches preset time, if reaches, then preset wake-up mode is used to wake up mouse, the sleep state of mouse can be not only objectively, efficiently and accurately judged by the application, but also accurately wake up mouse.

Description

A method and system for automatically determining and waking up mice from their sleep state. Technical Field

[0001] This invention relates to the fields of neuroscience and drug development technology, and more specifically to a method and system for automatically determining the sleep state of mice and automatically waking them up. Background Technology

[0002] Currently, in experimental fields such as neuroscience and drug development, the study of mouse sleep status has become a key link in revealing the mechanisms of the nervous system and evaluating the efficacy and safety of drugs. The accuracy of the data directly affects the scientific validity and reliability of experimental conclusions.

[0003] Current methods for judging the sleep state of mice mainly rely on manual analysis of EEG signal waveform characteristics. This method not only suffers from problems such as strong subjectivity, low efficiency, and high misjudgment rate, but also cannot accurately distinguish between sub-stages such as non-rapid eye movement sleep (NREM) and rapid eye movement sleep (REM). Current wake-up methods mainly use single vibration wake-up, which easily leads to adaptation in mice and cannot accurately wake them up.

[0004] Therefore, how to provide a method and system for automatically determining and waking up mice, which can not only objectively, efficiently and accurately determine the sleep state of mice, but also accurately wake up mice, is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide a method and system for automatically determining the sleep state of a mouse and automatically waking it up.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] Firstly, a method is provided for automatically determining the sleep state of a mouse and automatically waking it up, including the following steps:

[0008] S1. Calculate the time-domain and frequency-domain characteristics of the digital EEG signal of the mouse in the current analysis window;

[0009] S2. Calculate the first power ratio and the second power ratio based on the frequency domain characteristics;

[0010] S3. Based on the first power ratio, the second power ratio, and the time-domain features, obtain the preliminary sleep state judgment result of the mouse in the current analysis window;

[0011] S4. Based on the preliminary sleep state judgment result of the mouse in the current analysis window, the final sleep state judgment result of the mouse in the historical analysis window, and the sleep state transition rule, obtain the final sleep state judgment result of the mouse in the current analysis window.

[0012] The sleep state transition rules are: transition from wakefulness to non-rapid eye movement (NREM) sleep, transition from NREM sleep to rapid eye movement (REM) sleep, and transition from REM sleep to wakefulness.

[0013] S5. Determine whether the final sleep state of the mouse in the current analysis window is the preset target sleep state:

[0014] If so, determine whether the mouse has maintained the preset target sleep state for a preset time. If so, wake the mouse using a preset wake-up method. The preset target sleep state is either non-rapid eye movement (NREM) sleep or rapid eye movement (REM) sleep.

[0015] Preferably, the digital electroencephalogram (EEG) signal of the mouse within the current analysis window is obtained based on the following steps:

[0016] Obtain simulated electroencephalogram (EEG) signals from mice;

[0017] The simulated EEG signals are preprocessed to obtain a digital EEG signal sequence;

[0018] The digital EEG signal sequence is divided into analysis windows of fixed duration to obtain the digital EEG signal of the mouse within the current analysis window.

[0019] Preferably, the time-domain features include the variance of the digital EEG signal of the mouse within the current analysis window; the frequency-domain features include Delta power, Theta power, and Beta power; and the digital EEG signal is an EEG signal.

[0020] Preferably, the formulas for calculating the first power ratio and the second power ratio are as follows:

[0021] F1 = θ / δ;

[0022] F2 = (δ + θ) / β;

[0023] Wherein, F1 represents the first power ratio; F2 represents the second power ratio; θ represents the Theta power; δ represents the Delta power; and β represents the Beta power.

[0024] Preferably, S3 specifically includes the following steps:

[0025] S31. Determine whether the first power ratio is greater than a first preset threshold;

[0026] If so, then execute S32;

[0027] If not, the preliminary sleep state assessment result of the mouse in the current analysis window is non-rapid eye movement sleep state;

[0028] S32. Determine whether the variance of the digital EEG signal of the mouse in the current analysis window is less than the second preset threshold.

[0029] If so, the preliminary sleep state assessment result of the mouse in the current analysis window is REM sleep.

[0030] If not, then execute S33:

[0031] S33. Determine whether the second power ratio is greater than the third preset threshold;

[0032] If so, the preliminary sleep state judgment result of the mouse in the current analysis window is non-rapid eye movement sleep state;

[0033] If not, the preliminary sleep state assessment of the mouse in the current analysis window is an awake state.

[0034] Preferably, S4 specifically includes the following steps:

[0035] S41. The sleep state that appears most frequently in the preliminary sleep state judgment result of the mouse in the current analysis window and the final sleep state judgment result of the mouse in the historical analysis window shall be taken as the intermediate sleep state judgment result of the mouse in the current analysis window.

[0036] S42. Determine whether the first preset situation, the second preset situation, and the third preset situation have occurred;

[0037] The first preset scenario is: the intermediate sleep state of the mouse in the current analysis window is determined to be REM sleep, and the final sleep state of the previous analysis window adjacent to the current analysis window is determined to be awake.

[0038] The second preset scenario is: the intermediate sleep state judgment result of the mouse in the current analysis window is the awake state, and the final sleep state judgment result of the previous analysis window adjacent to the current analysis window is the non-rapid eye movement sleep state.

[0039] The third preset scenario is: the intermediate sleep state judgment result of the mouse in the current analysis window is non-rapid eye movement sleep state, and the final sleep state judgment result of the previous analysis window that is adjacent to the current analysis window is rapid eye movement sleep state.

[0040] If the first, second, and third preset scenarios do not occur, the intermediate sleep state judgment result of the mouse in the current analysis window will be taken as the final sleep state judgment result of the mouse in the current analysis window.

[0041] If the first preset situation occurs, the final sleep state judgment result of the mouse in the current analysis window is non-rapid eye movement sleep state;

[0042] If the second preset situation occurs, the final sleep state judgment result of the mouse in the current analysis window is REM sleep state;

[0043] If the third preset scenario occurs, the final sleep state judgment result of the mouse in the current analysis window will be an awake state.

[0044] Preferably, the preset wake-up method includes one or more of vibration wake-up, fragrance wake-up, and sound wake-up.

[0045] Preferably, when the preset wake-up method is vibration wake-up, the vibration intensity and vibration duration need to be preset; when the preset wake-up method is fragrance wake-up, the fragrance type needs to be preset; when the preset wake-up method is sound wake-up, the sound type needs to be preset.

[0046] Preferably, S5 further includes the following steps:

[0047] Obtain the PWM wave corresponding to the preset vibration intensity and the preset vibration duration;

[0048] The PWM wave is input to the vibration module, so that the vibration module outputs a vibration wave that meets the preset vibration intensity and the preset vibration duration;

[0049] Open the solenoid valve of the fragrance storage unit to release the fragrance of the preset fragrance type;

[0050] Start the sound playback unit to play the preset sound type.

[0051] Secondly, a system for automatically determining the sleep state of a mouse and automatically waking it up is provided to implement the above-mentioned method, including a feature calculation module, a power ratio calculation module, a preliminary sleep state acquisition module, a final sleep state acquisition module, a judgment module, and a wake-up module.

[0052] The feature calculation module is used to calculate the time-domain and frequency-domain features of the digital EEG signal of the mouse within the current analysis window;

[0053] The power ratio calculation module is used to calculate the first power ratio and the second power ratio based on the frequency domain characteristics;

[0054] The preliminary sleep state acquisition module is used to obtain the preliminary sleep state judgment result of the mouse in the current analysis window based on the first power ratio, the second power ratio and the time domain features;

[0055] The final sleep state acquisition module is used to obtain the final sleep state judgment result of the mouse in the current analysis window based on the preliminary sleep state judgment result of the mouse in the current analysis window, the final sleep state judgment result of the mouse in the historical analysis window, and the sleep state transition rules.

[0056] The judgment module is used to determine whether the final sleep state judgment result of the mouse in the current analysis window is the preset target sleep state:

[0057] If so, determine whether the mouse has maintained the preset target sleep state for a preset time. If it has, wake the mouse using a preset wake-up method. The preset target sleep state is either non-rapid eye movement (NREM) sleep or rapid eye movement (REM) sleep.

[0058] The wake-up module is used to wake up the mouse using the preset wake-up method.

[0059] As can be seen from the above technical solutions, compared with the prior art, the present invention discloses a method and system for automatically judging the sleep state of mice and automatically waking them up. It can not only objectively, efficiently and accurately judge the detailed sleep state of mice, but also accurately wake up mice. Attached Figure Description

[0060] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0061] Figure 1 is a flowchart of a method for automatically determining the sleep state of a mouse and automatically waking it up, provided by the present invention. Detailed Implementation

[0062] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0063] As shown in Figure 1, this invention discloses a method for automatically determining and waking up a mouse from its sleep state, comprising the following steps:

[0064] S1. Calculate the time-domain and frequency-domain characteristics of the digital EEG signal of the mouse in the current analysis window;

[0065] In one embodiment, the digital electroencephalogram (EEG) signal of the mouse within the current analysis window is obtained based on the following steps:

[0066] Obtain simulated electroencephalogram (EEG) signals from mice;

[0067] It is understandable that implanting miniature brain electrodes into the scalp of mice allows for the real-time acquisition of simulated brainwave signals from the mice.

[0068] The analog EEG signals are preprocessed to obtain digital EEG signal sequences;

[0069] The preprocessing specifically includes: amplifying the analog EEG signal using a miniature preamplifier; filtering the amplified analog EEG signal using an analog bandpass filter to remove DC drift, power frequency interference, and high-frequency noise; and performing analog-to-digital conversion on the filtered analog EEG signal using a high-precision ADC to obtain a digital EEG signal sequence.

[0070] The digital EEG signal sequence is divided into analysis windows of fixed duration to obtain the digital EEG signal of the mouse within the current analysis window.

[0071] It is understandable that adjacent analysis windows can overlap.

[0072] In one embodiment, the time-domain features include the variance of the digital EEG signal of the mouse within the current analysis window; the frequency-domain features include Delta power, Theta power, and Beta power; the digital EEG signal is an EEG signal, which is directly acquired through EEG electrodes.

[0073] It is understandable that Delta power, Theta power, and Beta power can be calculated by performing Fast Fourier Transform (FFT) or Power Spectral Density (PSD) estimation on the digital EEG signal of the mouse in the current analysis window.

[0074] It is understandable that: Delta power (δ) is the power integral of 0.5-4 Hz; Theta power (θ) is the power integral of 4-8 Hz; and Beta power (β) is the power integral of 13-30 Hz.

[0075] S2. Calculate the first power ratio and the second power ratio based on frequency domain characteristics;

[0076] In one embodiment, the formulas for calculating the first power ratio and the second power ratio are as follows:

[0077] F1 = θ / δ;

[0078] F2 = (δ + θ) / β;

[0079] Where F1 represents the first power ratio; F2 represents the second power ratio; θ represents the Theta power; δ represents the Delta power; and β represents the Beta power.

[0080] S3. Based on the first power ratio, the second power ratio, and time-domain characteristics, obtain the preliminary sleep state judgment results of the mice in the current analysis window;

[0081] In one embodiment, S3 specifically includes the following steps:

[0082] S31. Determine whether the first power ratio is greater than the first preset threshold;

[0083] If so, then execute S32;

[0084] If not, the preliminary sleep state assessment result of the mouse in the current analysis window is non-rapid eye movement sleep state;

[0085] S32. Determine whether the variance of the digital EEG signal of the mouse in the current analysis window is less than the second preset threshold.

[0086] If so, the preliminary sleep state assessment result of the mouse in the current analysis window is REM sleep.

[0087] If not, then execute S33:

[0088] S33. Determine whether the second power ratio is greater than the third preset threshold;

[0089] If so, the preliminary sleep state judgment result of the mouse in the current analysis window is non-rapid eye movement sleep state;

[0090] If not, the preliminary sleep state assessment of the mouse in the current analysis window is an awake state.

[0091] In one embodiment, S31-S33 are implemented using a three-level decision tree.

[0092] S4. Based on the preliminary sleep state judgment results of the mice in the current analysis window, the final sleep state judgment results of the mice in the historical analysis window, and the sleep state transition rules, obtain the final sleep state judgment results of the mice in the current analysis window.

[0093] The sleep state transition rules are: transition from wakefulness to non-rapid eye movement (NREM) sleep, transition from NREM sleep to rapid eye movement (REM) sleep, and transition from REM sleep to wakefulness.

[0094] It is understandable that the method for obtaining the final sleep state judgment result of the mouse in the historical analysis window is the same as the method for obtaining the final sleep state judgment result of the mouse in the current analysis window.

[0095] In one embodiment, the historical analysis window includes N analysis windows that are immediately adjacent to the current analysis window, where N = 3-5.

[0096] In one embodiment, S4 specifically includes the following steps:

[0097] S41. The sleep state that appears most frequently between the preliminary sleep state judgment result of the mouse in the current analysis window and the final sleep state judgment result of the mouse in the historical analysis window is taken as the intermediate sleep state judgment result of the mouse in the current analysis window.

[0098] S42. Determine whether the first preset situation, the second preset situation, and the third preset situation have occurred;

[0099] The first preset scenario is: the intermediate sleep state of the mouse in the current analysis window is determined to be REM sleep, and the final sleep state of the previous analysis window adjacent to the current analysis window is determined to be awake.

[0100] The second preset scenario is: the intermediate sleep state judgment result of the mouse in the current analysis window is the awake state, and the final sleep state judgment result of the previous analysis window that is adjacent to the current analysis window is the non-rapid eye movement sleep state.

[0101] The third preset scenario is: the intermediate sleep state of the mouse in the current analysis window is judged as non-rapid eye movement sleep state, and the final sleep state of the previous analysis window adjacent to the current analysis window is judged as rapid eye movement sleep state.

[0102] If the first, second, and third preset scenarios do not occur, the intermediate sleep state judgment result of the mouse in the current analysis window will be taken as the final sleep state judgment result of the mouse in the current analysis window.

[0103] If the first preset scenario occurs, the final sleep state judgment result of the mouse in the current analysis window will be non-rapid eye movement sleep state;

[0104] If the second preset scenario occurs, the final sleep state judgment result of the mouse in the current analysis window will be REM sleep state;

[0105] If the third preset scenario occurs, the final sleep state judgment result of the mouse in the current analysis window will be the awake state.

[0106] S5. Determine whether the final sleep state of the mouse in the current analysis window matches the preset target sleep state:

[0107] If so, determine whether the mouse has maintained the preset target sleep state for the preset time. If it has, wake the mouse using the preset wake-up method. The preset target sleep state is either non-rapid eye movement (NREM) sleep or rapid eye movement (REM) sleep.

[0108] In one embodiment, the preset time is the time for three consecutive analysis windows, i.e., at least 6-8 seconds.

[0109] In one embodiment, the preset wake-up method includes one or more of vibration wake-up, fragrance wake-up, and sound wake-up.

[0110] In one embodiment, when the preset wake-up method is vibration wake-up, the vibration intensity and vibration duration need to be preset; when the preset wake-up method is fragrance wake-up, the fragrance type needs to be preset; when the preset wake-up method is sound wake-up, the sound type needs to be preset.

[0111] In one embodiment, S5 further includes the following step:

[0112] Obtain the PWM wave corresponding to the preset vibration intensity and preset vibration duration;

[0113] The PWM wave is input to the vibration module, so that the vibration module outputs a vibration wave that meets the preset vibration intensity and preset vibration duration.

[0114] Open the solenoid valve of the fragrance storage unit to release the preset fragrance type.

[0115] Start the sound playback unit to play a preset sound type.

[0116] In one embodiment, the vibration module is a micro vibration motor; the fragrance storage unit is a micro liquid reservoir; the sound playback unit is a micro speaker; and the fragrance stored in the micro liquid reservoir is released through a micro diffuser.

[0117] In one embodiment, the following steps are also included:

[0118] S6. After waking the mouse using the preset wake-up method, repeat S1-S4. If the final sleep state judgment result of the mouse in the current analysis window obtained in S4 is an awake state, then the mouse has been successfully woken up.

[0119] In another embodiment, the present invention discloses a system for automatically determining the sleep state of a mouse and automatically waking it up, for implementing the above-mentioned method, including a feature calculation module, a power ratio calculation module, a preliminary sleep state acquisition module, a final sleep state acquisition module, a judgment module, and a wake-up module;

[0120] The feature calculation module is used to calculate the time-domain and frequency-domain features of the digital EEG signals of the mouse within the current analysis window;

[0121] The power ratio calculation module is used to calculate the first power ratio and the second power ratio based on frequency domain characteristics;

[0122] The preliminary sleep state acquisition module is used to obtain the preliminary sleep state judgment result of the mice in the current analysis window based on the first power ratio, the second power ratio, and time domain characteristics.

[0123] The final sleep state acquisition module is used to obtain the final sleep state judgment result of the mouse in the current analysis window based on the preliminary sleep state judgment result of the mouse in the current analysis window, the final sleep state judgment result of the mouse in the historical analysis window, and the sleep state transition rules.

[0124] The judgment module is used to determine whether the final sleep state of the mouse in the current analysis window matches the preset target sleep state.

[0125] If so, determine whether the mouse has maintained the preset target sleep state for the preset time. If it has, wake the mouse using the preset wake-up method. The preset target sleep state is either non-rapid eye movement (NREM) sleep or rapid eye movement (REM) sleep.

[0126] The wake-up module is used to wake up the mouse using a preset wake-up method.

[0127] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0128] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for automatically determining the sleep state of a mouse and automatically waking it up, characterized in that, The process includes the following steps: S1, calculating the time-domain and frequency-domain features of the digital EEG signal of the mouse within the current analysis window; the time-domain features include the variance of the digital EEG signal of the mouse within the current analysis window; S2, calculating a first power ratio and a second power ratio based on the frequency-domain features; the calculation formulas for the first power ratio and the second power ratio are: F1=θ / δ; F2=(δ+θ) / β; where F1 represents the first power ratio; F2 represents the second power ratio; θ represents the Theta power; δ represents the Delta power; β represents the Beta power; S3, obtaining a preliminary sleep state judgment result of the mouse within the current analysis window based on the first power ratio, the second power ratio, and the time-domain features; S4, based on the... The initial sleep state judgment result of the mouse, the final sleep state judgment result of the mouse in the historical analysis window, and the sleep state transition rules are used to obtain the final sleep state judgment result of the mouse in the current analysis window; the sleep state transition rules are: transition from wakefulness to non-rapid eye movement (NREM) sleep, transition from NREM sleep to rapid eye movement (REM) sleep, and transition from REM sleep to wakefulness; S5, determine whether the final sleep state judgment result of the mouse in the current analysis window is a preset target sleep state: if so, determine whether the time the mouse maintains the preset target sleep state has reached a preset time; if so, wake the mouse using a preset wake-up method; wherein, the preset target sleep state is either NREM sleep or REM sleep.

2. The method for automatically determining and waking up a mouse according to claim 1, characterized in that, The digital EEG signal of the mouse in the current analysis window is obtained based on the following steps: acquiring the simulated EEG signal of the mouse; The simulated EEG signals are preprocessed to obtain a digital EEG signal sequence; The digital EEG signal sequence is divided into analysis windows of fixed duration to obtain the digital EEG signal of the mouse within the current analysis window.

3. The method for automatically determining the sleep state of a mouse and automatically waking it up according to claim 1, characterized in that, The frequency domain features include Delta power, Theta power, and Beta power; the digital EEG signal is an EEG signal.

4. The method for automatically determining the sleep state of a mouse and automatically waking it up according to claim 1, characterized in that, S3 specifically includes The following steps are performed: S31, determine whether the first power ratio is greater than a first preset threshold; if yes, proceed to S32; if no, the preliminary sleep state judgment result of the mouse in the current analysis window is non-rapid eye movement (NREM) sleep state; S32, determine whether the variance of the digital electroencephalogram (EEG) signal of the mouse in the current analysis window is less than a second preset threshold; if yes, the preliminary sleep state judgment result of the mouse in the current analysis window is rapid eye movement (REM) sleep state; if no, proceed to S33: S33, determine whether the second power ratio is greater than a third preset threshold; if yes, the preliminary sleep state judgment result of the mouse in the current analysis window is non-rapid eye movement (NREM) sleep state; if no, the preliminary sleep state judgment result of the mouse in the current analysis window is awake state.

5. The method for automatically determining the sleep state of a mouse and automatically waking it up according to claim 4, characterized in that, S4 specifically includes the following steps: S41, taking the sleep state that appears most frequently between the preliminary sleep state judgment result of the mouse in the current analysis window and the final sleep state judgment result of the mouse in the historical analysis window as the intermediate sleep state judgment result of the mouse in the current analysis window; S42, determining whether a first preset situation, a second preset situation, and a third preset situation occur; wherein, the first preset situation is: the intermediate sleep state judgment result of the mouse in the current analysis window is REM sleep, and the final sleep state judgment result of the previous analysis window immediately adjacent to the current analysis window is awake; the second preset situation is: the intermediate sleep state judgment result of the mouse in the current analysis window is awake, and the final sleep state judgment result of the previous analysis window immediately adjacent to the current analysis window is non-REM sleep. The third preset scenario is as follows: the intermediate sleep state judgment result of the mouse in the current analysis window is non-rapid eye movement (NREM) sleep, and the final sleep state judgment result of the previous analysis window adjacent to the current analysis window is rapid eye movement (REM) sleep; if the first, second, and third preset scenarios do not occur, then the intermediate sleep state judgment result of the mouse in the current analysis window is taken as the final sleep state judgment result of the mouse in the current analysis window; if the first preset scenario occurs, then the final sleep state judgment result of the mouse in the current analysis window is NREM sleep; if the second preset scenario occurs, then the final sleep state judgment result of the mouse in the current analysis window is REM sleep; if the third preset scenario occurs, then the final sleep state judgment result of the mouse in the current analysis window is awake.

6. The method for automatically determining the sleep state of a mouse and automatically waking it up according to claim 1, characterized in that, The preset wake-up methods include one or more of vibration wake-up, fragrance wake-up, and sound wake-up.

7. The method for automatically determining the sleep state of a mouse and automatically waking it up according to claim 6, characterized in that, When the preset wake-up method is vibration wake-up, the vibration intensity and vibration duration need to be preset; when the preset wake-up method is fragrance wake-up, the fragrance type needs to be preset; when the preset wake-up method is sound wake-up, the sound type needs to be preset.

8. The method for automatically determining the sleep state of a mouse and automatically waking it up according to claim 7, characterized in that, S5 further includes the following steps: obtaining a PWM wave corresponding to the preset vibration intensity and vibration duration; inputting the PWM wave into the vibration module so that the vibration module outputs a vibration wave that satisfies the preset vibration intensity and vibration duration; opening the solenoid valve of the fragrance storage unit so that the fragrance storage unit releases the fragrance of the preset fragrance type; and starting the sound playback unit so that the sound playback unit plays the sound of the preset sound type.

9. A system for automatically determining the sleep state of a mouse and automatically waking it up, characterized in that, The method for implementing any one of claims 1-8 includes a feature calculation module, a power ratio calculation module, a preliminary sleep state acquisition module, a final sleep state acquisition module, a judgment module, and a wake-up module; the feature calculation module is used to calculate the time-domain features and frequency-domain features of the digital EEG signal of the mouse within the current analysis window; the time-domain features include the variance of the digital EEG signal of the mouse within the current analysis window; the power ratio calculation module is used to calculate a first power ratio and a second power ratio based on the frequency-domain features; the preliminary sleep state acquisition module is used to obtain a preliminary sleep state judgment result of the mouse within the current analysis window based on the first power ratio, the second power ratio, and the time-domain features; the final sleep state acquisition module... The sleep state acquisition module is used to obtain the final sleep state judgment result of the mouse in the current analysis window based on the preliminary sleep state judgment result of the mouse in the current analysis window, the final sleep state judgment result of the mouse in the historical analysis window, and the sleep state transition rules; the judgment module is used to determine whether the final sleep state judgment result of the mouse in the current analysis window is a preset target sleep state; if so, it determines whether the time the mouse maintains the preset target sleep state has reached a preset time; if so, it wakes the mouse using a preset wake-up method; wherein, the preset target sleep state is a non-rapid eye movement sleep state or a rapid eye movement sleep state; the wake-up module is used to wake the mouse using the preset wake-up method.

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