WO2024108669A1 - System and method for wakeful state detection - Google Patents

Abstract

Provided is a system and method for wakeful state detection. The system comprises: a physiological index detection apparatus (10) configured to generate a physiological detection result of a target physiological index; a body posture detection apparatus (20) configured to generate a posture detection result of the body posture; an athletic ability detection apparatus (30) configured to generate an athletic ability detection result of athletic information; a stimulation response detection apparatus (40) configured to generate a stimulation response detection result of the target stimulation signal; an emotional response detection apparatus (50) configured to generate an emotional response detection result of an emotion behavior characterization; a behavior pattern detection apparatus (60) configured to generate a behavior pattern detection result of a behavior pattern; and a wakeful state evaluation apparatus (70) configured to determine and display the wakeful state of the target detection subject on the basis of the physiological detection result, the posture detection result, the athletic ability detection result, the stimulation response detection result, the behavior pattern detection result, and the emotional response detection result.

Description

Awake state detection system and method

This application claims priority to the Chinese patent application filed with the China Patent Office on November 25, 2022, with application number 202211493320.6, the entire contents of which are incorporated by reference into this application.

Technical Field

The present application relates to the technical field of biomedical signal processing, for example, to a wakefulness state detection system and method.

Background technique

It is extremely important for individuals to maintain a good state of wakefulness and take appropriate defensive actions against harmful stimuli for both individual survival and species reproduction. However, under stress, neuropsychiatric diseases and extreme environments, such as the deep sea, deep space, and polar regions, individuals' basic life activities and brain wakefulness are easily affected, thus affecting task execution and even making it difficult to cope with threats to survival.

The regulatory mechanism of special brain states has always been one of the important frontier scientific issues that humans have not yet fully understood. Taking the brain state induced by general anesthesia as an example, the neural mechanism of awakening, loss of consciousness and recovery caused by it is an important content in neuroscience and clinical research.

In related technologies, a single indicator is generally used as the criterion for judging the state of wakefulness. First, since brain function is an overall state, a single indicator cannot fully reflect the overall activity level and functional state of the brain. Therefore, it is difficult to quickly and accurately judge the state of wakefulness in both scientific research and clinical diagnosis and treatment. Secondly, using this standard to judge the state of wakefulness is often prone to misjudgment, resulting in hypoxia, airway obstruction, and secondary intubation, which poses a safety risk.

Summary of the invention

The present application provides a wakefulness state detection system and method to solve the technical problem of inaccurate wakefulness state judgment.

The present application provides a wakefulness state detection system, which includes: a physiological indicator detection device, a body posture detection device, a motor ability detection device, a stimulus response detection device, an emotional response detection device, a behavior pattern detection device and a wakefulness state evaluation device; wherein the physiological indicator detection device is configured to collect target physiological indicators of a target detection object, generate physiological detection results corresponding to the target physiological indicators, and send the physiological detection results to the wakefulness state evaluation device; the body posture detection device is configured to detect the body posture of the target detection object, generate a posture detection result corresponding to the body posture, and send the posture detection result to the wakefulness state evaluation device. Evaluation device; the motor ability detection device is configured to detect the motor information of the target detection object, generate a motor ability detection result corresponding to the motor information, and send the motor ability detection result to the wakefulness evaluation device; the emotional response detection device is configured to detect the emotional information of the target detection object, generate an emotional response detection result corresponding to the emotional information, and send the emotional response detection result to the wakefulness evaluation device; the behavior pattern detection device is configured to detect the behavior structure and switching mode of the target detection object, generate a behavior pattern detection result corresponding to the behavior phenotype, and send the behavior pattern detection result to the wakefulness evaluation device; the stimulus response detection device is configured to generate a stimulus response detection result corresponding to the target stimulus signal based on the response information of the target detection object to the target stimulus signal, and send the stimulus response detection result to the wakefulness evaluation device, wherein the target stimulus signal includes a harmful stimulus signal; the wakefulness evaluation device is configured to determine the wakefulness of the target detection object based on the received physiological detection result, the posture detection result, the motor ability detection result, the stimulus response detection result, the behavior pattern detection result, and the emotional response detection result, and display the wakefulness.

The present application provides a method for detecting a wakefulness state, which is applied to a wakefulness state detection system, wherein the wakefulness state detection system includes a physiological indicator detection device, a body posture detection device, a motor ability detection device, a stimulus response detection device, a behavior pattern detection device, an emotional response detection device, and a wakefulness state evaluation device; wherein the method for detecting a wakefulness state includes: collecting target physiological indicators of a target detection object through the physiological indicator detection device, generating physiological detection results corresponding to the target physiological indicators, and sending the physiological detection results to the wakefulness state evaluation device; detecting the body posture of the target detection object through the body posture detection device, generating a posture detection result corresponding to the body posture, and sending the posture detection result to the wakefulness state evaluation device; detecting the motion information of the target detection object through the motor ability detection device, generating a motor ability detection result corresponding to the motion information, and sending the motor ability detection result to the wakefulness state evaluation device; detecting the target physiological indicators of a target detection object through the physiological indicator detection device, generating a physiological detection result corresponding to the target physiological indicators, and sending the physiological detection result to the wakefulness state evaluation device; The reaction detection device detects the emotional information of the target detection object, generates an emotional reaction detection result corresponding to the emotional information, and sends the emotional reaction detection result to the wakefulness state evaluation device; through the stimulus response detection device, based on the response information of the target detection object to the target stimulus signal, generates a stimulus response detection result corresponding to the target stimulus signal, and sends the stimulus response detection result to the wakefulness state evaluation device, wherein the target stimulus signal includes a harmful stimulus signal; through the behavior pattern detection device, the behavior structure and switching pattern of the target detection object are detected, and a behavior pattern detection result corresponding to the behavior phenotype is generated, and the behavior pattern detection result is sent to the wakefulness state evaluation device; through the wakefulness state evaluation device, the wakefulness state of the target detection object is determined based on the received physiological detection results, the posture detection results, the motor ability detection results, the stimulus response detection results, the behavior pattern detection results and the emotional reaction detection results, and the wakefulness state is displayed.

The present application provides an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the wakefulness state detection method described in any embodiment of the present application.

The present application provides a computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable a processor to implement the wakefulness state detection method described in any embodiment of the present application when executed.

BRIEF DESCRIPTION OF THE DRAWINGS

The following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

FIG1 is a schematic diagram of the structure of a wakefulness state detection system provided according to an embodiment of the present application;

FIG2 is a working principle diagram of the wakefulness state detection system according to an embodiment of the present application;

FIG3 is a flow chart of a method for detecting a wakefulness state according to an embodiment of the present application;

FIG. 4 is a schematic diagram of the structure of an electronic device that implements the awakening state detection method according to an embodiment of the present application.

Detailed ways

The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only embodiments of a part of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

Fig. 1 is a schematic diagram of the structure of a wakefulness state detection system provided in an embodiment of the present application. The wakefulness state detection system can be implemented in the form of hardware and/or software.

As shown in FIG1 , the wakefulness state detection system includes a physiological indicator detection device 10, a body posture detection device 20, a motor ability detection device 30, a stimulus response detection device 40, an emotional response detection device 50, a behavior pattern detection module 60, and a wakefulness state evaluation device 70. The physiological indicator detection device 10 is configured to collect target physiological indicators of a target detection object, generate physiological detection results corresponding to the target physiological indicators, and send the physiological detection results to the wakefulness state evaluation device 70; the body posture detection device 20 is configured to detect the body posture of the target detection object, generate a posture detection result corresponding to the body posture, and send the posture detection result to the wakefulness state evaluation device 70; the motor ability detection device 30 is configured to detect the motion information of the target detection object, generate a motor ability detection result corresponding to the motion information, and send the motor ability detection result to the wakefulness state evaluation device 70; the emotional response detection device 40 is configured to detect the emotional information of the target detection object, generate an emotional response detection result corresponding to the emotional information, and send the emotional response detection result to the wakefulness state evaluation device 70. state evaluation device 70; a stimulus response detection device 50, which is configured to generate a stimulus response detection result corresponding to the target stimulation signal based on the response information of the target detection object to the target stimulation signal, and send the stimulus response detection result to the wakefulness state evaluation device 70, wherein the target stimulation signal includes a harmful stimulation signal; a behavior pattern detection device 60, which is configured to detect the behavior structure and switching pattern of the target detection object, generate a behavior pattern detection result corresponding to the behavior phenotype, and send the behavior pattern detection result to the wakefulness state evaluation device 70; the wakefulness state evaluation device 70 is configured to determine the wakefulness state of the target detection object based on the received physiological detection results, the posture detection results, the motor ability detection results, the stimulus response detection results, the emotional response detection results and the behavior pattern detection results, and display the wakefulness state.

The technical solution of the embodiment of the present application, by setting up a physiological index detection device, a body posture detection device, a motor ability detection device, a stimulus response detection device, an emotional response detection device, a behavior pattern detection device and an awakening state evaluation device in the awakening state detection system, constructs a complete, multi-dimensional awakening state detection system. Through the physiological index detection device, the body posture detection device, the motor ability detection device, the stimulus response detection device, the emotional response detection device and the behavioral pattern detection device, the multi-dimensional indicators of physiological indicators, body posture, movement, stimulus response, emotion and behavior can be detected respectively. Then, through the awakening state evaluation device, the physiological detection results, the posture detection results, the motor ability detection results, the stimulus response detection device, the emotional response detection results and the behavioral pattern detection results are comprehensively analyzed, and the awakening state of the target detection object is more comprehensively detected, which solves the technical problem of inaccurate judgment of the awakening state by a single indicator, improves the detection accuracy of the awakening state, and provides a scientific and effective detection method for studying the neural mechanism of awakening and consciousness state.

In an embodiment of the present application, the wakefulness state evaluation device 70 is configured to align the received physiological detection results, the posture detection results, the motor ability detection results, the stimulus response detection results, the emotional reaction detection results and the behavioral pattern detection results in the time dimension, and then quantify the physiological detection results, the posture detection results, the motor ability detection results, the stimulus response detection results, the emotional reaction detection results and the behavioral pattern detection results in the same time period to obtain a single-dimensional evaluation index corresponding to each detection result, and then perform weighted fusion processing on the single-dimensional evaluation indicators corresponding to multiple detection results to obtain a comprehensive index for indicating the wakefulness state of the target detection object, and then match the comprehensive index with the indicator range corresponding to different wakefulness states to determine the wakefulness state of the target detection object and display the wakefulness state.

Exemplarily, the physiological index detection device 10 includes at least one of a body temperature detection module, a blood pressure detection module, a heart rate detection module, a respiratory rate detection module, and a blood oxygen saturation detection module. It should be noted that the physiological index detection device 10 can support a multi-modal detection device for multi-index detection, for example, a detection device that can be set to detect two or more physiological indicators such as body temperature, blood pressure, heart rate, respiratory rate, and blood oxygen saturation. In an embodiment of the present application, the detection of the body posture of the target detection object can be obtained by analyzing the video information of the target detection object. Optionally, the body posture detection device 20 includes a video acquisition module and a posture analysis module. The video acquisition module is configured to collect video information of the target detection object in a free activity or external stimulation state, and send the video information to the posture analysis module; the posture analysis module is configured to identify the posture of the target detection object through the video information and a preset artificial intelligence algorithm to obtain the posture detection result of the target detection object, and send the posture detection result to the awakening state evaluation device, wherein the posture detection result includes skeleton morphology information and/or body height information.

In the embodiment of the present application, there may be multiple ways to perform motion detection on the target object, and accordingly, there may be multiple structures of the motion ability detection device.

Exemplarily, the motor ability detection device can obtain the motor ability detection result of the target detection object by performing motor ability analysis on the video information of the target detection object. Optionally, the motor ability detection device 30 includes a video acquisition module and a motion analysis module. The video acquisition module is configured to capture the behavior video of the target detection object in a free activity or external stimulation state, and send the behavior video to the behavior analysis module; the behavior analysis module is configured to analyze the behavior of the target detection object in different states through the behavior video and a preset artificial intelligence algorithm to obtain the motor ability detection result of the target detection object, and send the motor ability detection result to the awakening state evaluation device 70, wherein the motor ability detection result includes at least one of the information such as body deflection angle information, movement distance information and movement speed information.

In an embodiment of the present application, the artificial intelligence algorithm may be at least one of a pre-trained neural network model, a deep learning algorithm, and a machine learning algorithm.

As another optional technical solution of the embodiment of the present application, on the basis of the above-mentioned multiple technical solutions, the athletic ability detection device 30 may include a motion detection module and a motion analysis module. Exemplarily, the motion detection module includes at least one of an electromyographic signal acquisition module, an experimental treadmill test module and a rotarod test module. The electromyographic signal acquisition module is configured to acquire the electromyographic signal of the target detection object, use the electromyographic signal as the first motion detection signal, and send the first motion detection signal to the motion analysis module. The experimental treadmill test module is configured to perform a running test on the target detection object, use the running test data as the second motion detection signal, and send the second motion detection signal to the motion analysis module. The rotarod test module is configured to test the target detection object, use the rotarod test data as the third motion detection signal, and send the third motion detection signal to the motion analysis module. The motion analysis module is configured to analyze the received motion detection signal, obtain the motion ability detection result of the target detection object, and send the motion ability detection result to the wakefulness state evaluation device 70, wherein the motion detection signal includes at least one of the first motion detection signal, the second motion detection signal and the third motion detection signal, and the motion ability detection result includes at least one of the muscle strength index, endurance index, coordination index and balance index of the target detection object.

The motion analysis module can obtain the muscle strength index of the target detection object by analyzing the received electromyographic signal. The motion analysis module can obtain the muscle strength index and endurance index of the target detection object by analyzing the received running test data. The motion analysis module can obtain the coordination index and balance index of the target detection object by analyzing the received rotarod test data.

Exemplarily, the emotional response detection device 40 may include a video acquisition module and an emotional analysis module. The video acquisition module is configured to acquire video information of the target detection object in a free activity or external stimulation state, and send the video information to the emotional analysis module; the emotional analysis module is configured to analyze the emotional response of the target detection object in different states through the video information and a preset artificial intelligence algorithm to obtain the emotional response detection result of the target detection object, and send the emotional response detection result to the awakening state evaluation device. The emotional response detection result may include at least one of the emotions such as sadness, pain, calmness or fear. In addition, the emotional response detection result may include at least one of the emotion occurrence time, emotion conversion time and emotion duration.

The emotional information of the target detection object is detected, an emotional response detection result corresponding to the emotional information is generated, and the emotional response detection result is sent to the wakefulness state evaluation device 70.

Behavior is the most direct external representation of the brain's state. Using data-driven sophisticated behavioral analysis can reflect the brain's internal state to a certain extent.

Similarly, the behavior pattern detection result of the target detection object can be obtained by performing behavior pattern analysis on the video information of the target detection object. Optionally, the behavior pattern detection device 60 includes a behavior video acquisition module and a behavior analysis module, wherein the video acquisition module is configured to acquire the behavior video of the target detection object in a free activity or external stimulation state, and send the behavior video to the behavior analysis module; the behavior analysis module is configured to analyze the behavior results and switching modes of the target detection object in different states through the behavior video and a preset artificial intelligence algorithm to obtain the behavior pattern detection result of the target detection object, and send the behavior pattern detection result to the wakefulness state evaluation device, wherein the behavior pattern detection result includes at least one of the information such as behavior action type information, action frequency information, behavior state transition information, and behavior pattern switching information.

Optionally, the stimulus response detection device 50 includes a stimulus unit, a response information collection unit, and a response result detection unit. The stimulus unit is configured to generate a target stimulus signal in response to a stimulus trigger instruction, and apply the target stimulus signal to the target stimulus object, wherein the target stimulus signal includes at least one of a visual stimulus signal, an olfactory stimulus signal, a sensory stimulus signal, and an auditory stimulus signal; the response information collection unit is configured to collect response information of the target detection object in response to the target stimulus signal, and send the response information to the response result detection unit; the response result detection unit is configured to generate a stimulus response detection result corresponding to the target stimulus signal according to the response information, and send the stimulus response detection result to the wakefulness state evaluation device 70.

The stimulation unit can generate a target stimulation signal according to actual needs, for example, a multimodal sensory stimulation signal. The stimulation unit can be provided with a user operation component and a display component. The user operation component can be a physical control component consisting of at least a stimulation parameter setting button and a stimulation start button and/or a stimulation stop button; or it can be a touch-operated component that supports stimulation parameter setting and stimulation triggering.

Exemplarily, the response information may include at least one of information such as a reaction latency, reaction intensity, and reaction duration of the target detection object to the target stimulation signal.

On the basis of the above-mentioned multiple technical solutions, the wakefulness state detection system can also analyze the wakefulness state of the target detection object through brain activity. Optionally, the wakefulness state detection system also includes an EEG signal detection device. The EEG signal detection device is configured to detect the EEG signal of the target detection object, generate an EEG detection result corresponding to the cortical EEG signal, and send the EEG detection result to the wakefulness state evaluation device 70; the wakefulness state evaluation device 70 is also configured to update the wakefulness state of the target detection object based on the EEG detection result.

The EEG signal detection device includes an EEG signal acquisition module, a neuron signal acquisition module and an EEG detection module, wherein the EEG signal acquisition module is configured to acquire the cortical EEG signal of the target detection object and send the cortical EEG signal to the EEG detection module; the neuron signal acquisition module is configured to obtain the neural activity information and activity change information of the subcortical brain area of the target detection object and send the neural activity information and the activity change information to the EEG detection module, wherein the neuron signal acquisition module includes a calcium ion fiber recording unit and/or a two-photon in vivo calcium imaging unit; the EEG detection module is configured to analyze the band characteristics of the cortical EEG signal within a preset band based on the cortical EEG signal and the neural activity information and activity change information of the subcortical brain area, use the band characteristics as the EEG detection result corresponding to the cortical EEG signal, and send the EEG detection result to the wakefulness state evaluation device 70, wherein the band characteristics include at least one of amplitude, frequency, energy value and neural activity change information.

By adopting this technical solution, the activity characteristics of the cerebral cortex can be analyzed through the EEG signal, and the activity information of the subcortical brain area can be analyzed through the neuron signal acquisition module. Combining the two can more accurately analyze the brain activity characteristics of the target detection object. Considering that EEG information can be divided into iconic specific bands, such as α, β, θ and γ waves, each specific band can be analyzed, thereby performing a refined analysis of EEG signals in different dimensions.

The wakefulness state evaluation device 70 can be configured to determine the wakefulness state of the target detection object based on the received physiological detection results, the posture detection results, the motor ability detection results, the stimulus response detection results, the emotional response detection results, the EEG detection results and the behavioral pattern detection results, and display the wakefulness state.

Since the eye movement change information can effectively reflect information such as the attention and alertness level of the target detection object, the wakefulness state of the target detection object can be detected based on the eye movement change information. Optionally, the wakefulness state detection system also includes an eye tracking device. The eye tracking device is configured to obtain the eye movement change information of the target detection object when it is in a state of free movement or receiving external stimulation, and send the eye movement change information to the wakefulness state evaluation device; the wakefulness state evaluation device is also configured to update the wakefulness state of the target detection object based on the eye movement change information. The eye movement change information includes at least one of pupil diameter change information, pupil displacement information and pupil deflection angle information.

Optionally, the wakefulness state detection system further comprises a target point regulation module, which is configured to regulate the activity state of the target neuron target point through in vivo optogenetics technology.

When the awakening state detection system in the embodiment of the present application is used for awakening detection, the neurons related to the awakening state can be determined by analyzing the data collected by the system, and the target neuron targets can be set. Then, the activity state of the target neuron targets can be regulated by the target control module based on in vivo optogenetics technology, such as activating neurons or inhibiting neuron activity. The change characteristics of the above multiple indicators of the target detection object during the process from anesthesia to awakening can be analyzed, and the awakening state can be further evaluated, and the evaluation system of the awakening state detection system can also be verified.

In order to facilitate intuitive understanding of the detection results of the wakefulness state, optionally, the wakefulness state detection system may also include at least one of a display device, a sound playback device, and a wireless communication device. The display device may be connected to the wakefulness state evaluation device and configured to display the wakefulness state of the target detection object. The sound playback device may be connected to the wakefulness state evaluation device and configured to voice broadcast the wakefulness state of the target detection object. The wireless communication device may be connected to the wakefulness state evaluation device and configured to send the wakefulness state of the target detection object to the target terminal.

In addition, the display device, the sound playing device and the wireless communication device can also be respectively connected to the physiological index detection device, the body posture detection device, the motor ability detection device, the stimulus response detection device, the emotional response detection device, the behavior pattern detection device, the EEG signal detection device, the eye tracking device and the target control module, and set to display the preset display information of the relevant devices.

FIG2 is a working principle diagram of the awakening state detection system according to the embodiment of the present application. As shown in FIG2, the awakening state detection system of the embodiment of the present application is particularly suitable for evaluating the awakening state after anesthesia, and mainly includes: (1) Based on the evaluation system of the awakening state detection system of the embodiment of the present application, the defense reaction induced by visual stimulation is applied to the awakening state judgment process under general anesthesia, and the visual stimulation that can induce the defense reaction is combined with the special brain state induced by general anesthesia; (2) The entire detection system is divided into three stages: awakening, recovery of righting reflex (RORR) and post-recovery of righting reflex (post-RORR). In each stage, visual stimulation is given to the animal in a timely manner, and its behavioral response is compared with each other; (3) The system simultaneously incorporates basic physiological indicators, behavioral phenotypes, EEG/EMG signal recording, mobile eye tracking, motor ability test, three-dimensional (3D) fine behavior analysis, fiber optic recording and optogenetic regulation, etc., which can realize multi-dimensional indicator detection.

Use physiological monitors to monitor the basic physiological indicators of the target detection object (the small animal in the picture) in different states, such as body temperature, blood pressure, heart rate, respiratory rate, and blood oxygen saturation. Using conventional electroencephalogram (EEG) signal acquisition equipment, combined with calcium ion fiber recording or two-photon in vivo calcium imaging technology, the cortical EEG signals of animals in different states and the neural activity and activity changes of the subcortical brain area can be obtained in real time, and the amplitude, frequency, energy value and strength of neural activity changes of specific bands (such as α, β, θ and γ waves, etc.) can be analyzed. The cortical signal and the subcortical signal are synchronized in the time dimension through an algorithm, and then the correlation between the cortical and subcortical activities (such as the order and degree of recovery) is analyzed, and the overall brain wakefulness state of the animal can be judged. Using the ultra-micro and easy-to-compatible eye tracking system independently developed by this laboratory, the eye movement change information of animals in free activities or receiving external stimuli can be obtained in real time, which can be used to judge the attention and alertness level of animals. The animal treadmill and rotarod are used to test the movement of animals, including coordination, balance, muscle strength and endurance, etc., and combined with the electromyography (EMG) signals collected by implanted electrodes, the animal's movement ability in different states can be comprehensively evaluated. The animals are subjected to noxious stimulation (such as tail clamping) at different stages, and the reaction latency, reaction intensity and reaction time required to respond to the stimulation are analyzed to evaluate the pain response of the animals at different stages and their ability to process malignant stimulation. By using the new system Behavior Atlas independently developed by our laboratory for high-precision animal behavior three-dimensional reconstruction and automated phenotypic identification, we can collect all-round behavioral videos of animals in free movement or under external stimulation, and then use artificial intelligence algorithms to segment, cluster, reconstruct and annotate the animal's behavior. We can perform a detailed analysis of the animal's behavior and body posture in different states, obtain multi-dimensional information such as the animal's skeleton, body height, deflection angle, movement distance and speed, movement type and frequency, state transition and behavior switching mode, and comprehensively evaluate the animal's behavioral awakening level during the process of anesthesia cessation-RORR-post-RORR until full recovery.

At the same time, in vivo optogenetics is used to artificially regulate specific targets, such as activating or inhibiting neuronal activity. In the operation, first, select the target detection object (the animal shown in Figure 2) that can make a normal defensive response to the approaching upper visual field shadow stimulation (looming) in the awake state, and then induce the animal into a state of general anesthesia with general anesthetics. After maintaining this state for 30 minutes, put the animal back into the behavior box and keep the loss of righting reflex (LORR) posture. Wait for its RORR moment and at an appropriate time point thereafter, give visual stimulation again, and record its behavioral response. Under technically permitted and manipulable conditions, the same animal is synchronously recorded and monitored for multi-dimensional indicators, such as a combination of physiological indicator detection + EEG/EMG recording + eye tracking + optogenetic regulation + fine behavior analysis. It can simultaneously obtain information in multiple dimensions on the same individual, match and correlate the multi-dimensional information in time or space scales, and comprehensively judge the awakening state of the mouse. If multiple horizontal indicators at a time point after the end of anesthesia are basically consistent with those in the awake state, it can be considered that the animal has recovered to a normal awakening level at that moment.

FIG3 is a flow chart of a wakefulness state detection method provided in an embodiment of the present application. This embodiment is applicable to the case of detecting the wakefulness state of a target detection object. The method can be applied to a wakefulness state detection system, wherein the wakefulness state detection system includes a physiological index detection device, a body posture detection device, a motor ability detection device, a stimulus response detection device, an emotional response detection device, a behavior pattern detection device, and a wakefulness state evaluation device. Optionally, the method can be performed by a wakefulness state detection device, which can be implemented in the form of hardware and/or software. The wakefulness state detection device can be configured in the wakefulness state detection system or in an electronic device independent of the wakefulness state detection system, or can be a program product. As shown in FIG3 , the method includes the following steps.

S201. Collect target physiological indicators of a target detection object through the physiological indicator detection device, generate physiological detection results corresponding to the target physiological indicators, and send the physiological detection results to the wakefulness state evaluation device.

S202. Detect the body posture of the target detection object through the body posture detection device, generate a posture detection result corresponding to the body posture, and send the posture detection result to the wakefulness state evaluation device.

S203, detecting the motion information of the target detection object through the motion ability detection device, generating a motion ability detection result corresponding to the motion information, and sending the motion ability detection result to the wakefulness state evaluation device.

S204, detecting the emotional information of the target detection object through the emotional response detection device, generating an emotional response detection result corresponding to the emotional information, and sending the emotional response detection result to the wakefulness state evaluation device.

S205. Generate a stimulus response detection result corresponding to the target stimulus signal based on the response information of the target detection object to the target stimulus signal through the stimulus response detection device, and send the stimulus response detection result to the wakefulness state evaluation device, wherein the target stimulus signal includes a harmful stimulus signal.

S206. Detect the behavior structure and switching pattern of the target detection object through the behavior pattern detection device, generate a behavior pattern detection result corresponding to the behavior phenotype, and send the behavior pattern detection result to the wakefulness state evaluation device.

S207. Determine the wakefulness state of the target detection object through the wakefulness state evaluation device based on the received physiological detection results, the posture detection results, the motor ability detection results, the stimulus response detection results, the behavior pattern detection results and the emotional reaction detection results, and display the wakefulness state.

The technical solution of the embodiment of the present application, by setting up a physiological index detection device, a body posture detection device, a motor ability detection device, a stimulus response detection device, an emotional response detection device and an awakening state evaluation device in the awakening state detection system, constructs a complete, multi-dimensional awakening state detection system. Through the physiological index detection device, the body posture detection device, the motor ability detection device, the stimulus response detection device, the emotional response detection device and the behavior pattern detection device, the multi-dimensional indicators of physiological indicators, body posture, movement, stimulus response and emotion can be detected respectively, and then, through the awakening state evaluation device, the physiological detection results, the posture detection results, the motor ability detection results, the stimulus response detection device, the emotional response detection results and the behavior pattern detection results are comprehensively analyzed, and the awakening state of the detection target object is more comprehensively detected, which solves the technical problem of inaccurate judgment of the awakening state by a single indicator, improves the detection accuracy of the awakening state, and provides a scientific and effective detection method for studying the neural mechanism of awakening and consciousness state.

Optionally, the body posture detection device includes a video acquisition module and a posture analysis module.

Correspondingly, the body posture of the target detection object is detected by the body posture detection device, a posture detection result corresponding to the body posture is generated, and the posture detection result is sent to the wakefulness state evaluation device, including: through the video acquisition module, video information of the target detection object in a free activity or external stimulation state is collected, and the video information is sent to the posture analysis module; through the posture analysis module, the posture of the target detection object is identified through the video information and a preset artificial intelligence algorithm to obtain the posture detection result of the target detection object, and the posture detection result is sent to the wakefulness state evaluation device, wherein the posture detection result includes skeleton morphology information and/or body height information.

Optionally, the motion ability detection device includes a video acquisition module and a motion analysis module. Accordingly, the motion information of the target detection object is detected by the motion ability detection device, a motion ability detection result corresponding to the motion information is generated, and the motion ability detection result is sent to the wakefulness state evaluation device, including: collecting the behavior video of the target detection object in a free activity or external stimulation state by the video acquisition module, and sending the behavior video to the behavior analysis module; analyzing the behavior of the target detection object in different states by the behavior video and a preset artificial intelligence algorithm by the behavior analysis module to obtain the motion ability detection result of the target detection object, and sending the motion ability detection result to the wakefulness state evaluation device, wherein the motion ability detection result includes at least one of body deflection angle information, movement distance information and movement speed information.

Optionally, the athletic ability detection device includes a motion detection module and a motion analysis module, and the motion test module includes at least one of an electromyographic signal acquisition module, an experimental treadmill test module and a rotarod test module.

Correspondingly, the motion information of the target detection object is detected through the motion ability detection device, a motion ability detection result corresponding to the motion information is generated, and the motion ability detection result is sent to the wakefulness state evaluation device, including: collecting the electromyographic signal of the target detection object through the electromyographic signal acquisition module, using the electromyographic signal as the first motion detection signal, and sending the first motion detection signal to the motion analysis module; performing a running test on the target detection object through the experimental treadmill test module, and using the running test data as the second motion detection signal, and sending the second motion detection signal to the motion analysis module; A testing module tests the target detection object, and uses the rotarod test data as a third motion detection signal, and sends the third motion detection signal to the motion analysis module; the received motion detection signal is analyzed by the motion analysis module to obtain a motion ability detection result of the target detection object, and the motion ability detection result is sent to the wakefulness state evaluation device, wherein the motion detection signal includes at least one of the first motion detection signal, the second motion detection signal and the third motion detection signal, and the motion ability detection result includes at least one of the muscle strength index, endurance index, coordination index and balance index of the target detection object.

Optionally, the stimulus response detection device 50 includes a stimulation unit, a response information acquisition unit and a response result detection unit.

Correspondingly, the stimulus response detection device 50 generates a stimulus response detection result corresponding to the target stimulus signal based on the response information of the target detection object to the target stimulus signal, and sends the stimulus response detection result to the wakefulness state evaluation device, wherein the target stimulus signal includes a harmful stimulus signal, including: generating a target stimulus signal through the stimulation unit in response to a stimulus trigger instruction, and applying the target stimulus signal to the target stimulus object, wherein the target stimulus signal includes at least one of a visual stimulus signal, an olfactory stimulus signal, a sensory stimulus signal and an auditory stimulus signal; collecting response information of the target detection object in response to the target stimulus signal through the response information collection unit, and sending the response information to the response result detection unit; generating a stimulus response detection result corresponding to the target stimulus signal through the response result detection unit according to the response information, and sending the stimulus response detection result to the wakefulness state evaluation device.

Optionally, the behavior pattern detection device includes a behavior video acquisition module and a behavior analysis module.

Correspondingly, the behavior structure and switching pattern of the target detection object are detected by the behavior pattern detection device, a behavior pattern detection result corresponding to the behavior phenotype is generated, and the behavior pattern detection result is sent to the wakefulness state evaluation device, including: collecting the behavior video of the target detection object in a free activity or external stimulation state through the video acquisition module, and sending the behavior video to the behavior analysis module; the behavior analysis module is configured to analyze the behavior results and switching patterns of the target detection object in different states through the behavior video and a preset artificial intelligence algorithm to obtain the behavior pattern detection result of the target detection object, and send the behavior pattern detection result to the wakefulness state evaluation device, wherein the behavior pattern detection result includes at least one of the information such as behavior action type information, action frequency information, behavior state transition information and behavior pattern switching information.

Optionally, the wakefulness state detection system further includes an electroencephalogram (EEG) signal detection device. Accordingly, the wakefulness state detection method may further include: detecting the EEG signal of the target detection object through the cortical EEG signal detection device, generating an EEG detection result corresponding to the cortical EEG signal, and sending the EEG detection result to the wakefulness state evaluation device; and updating the wakefulness state of the target detection object based on the EEG detection result through the wakefulness state evaluation device.

Optionally, the cortical EEG signal detection device includes an EEG signal acquisition module, a neuron signal acquisition module and an EEG detection module.

Correspondingly, the cortical EEG signal detection device detects the EEG signal of the target detection object, generates an EEG detection result corresponding to the cortical EEG signal, and sends the EEG detection result to the wakefulness state evaluation device, including: collecting the cortical EEG signal of the target detection object through the cortical EEG signal acquisition module, and sending the cortical EEG signal to the EEG detection module; acquiring the neural activity information and activity change information of the subcortical brain area of the target detection object through the neuron signal acquisition module, and sending the neural activity information and the activity change information to the EEG detection module; The method is to send the neuron signal to the EEG detection module, wherein the neuron signal acquisition module includes a calcium ion fiber recording unit and/or a two-photon in vivo calcium imaging unit; through the EEG detection module, based on the cortical EEG signal, the neural activity information of the subcortical brain area and the activity change information, analyze the band characteristics of the cortical EEG signal within a preset band, use the band characteristics as the EEG detection result corresponding to the cortical EEG signal, and send the EEG detection result to the wakefulness state evaluation device, wherein the band characteristics include at least one of amplitude, frequency, energy value and change information of neural activity.

Optionally, the wakefulness state detection system also includes an eye tracking device. Accordingly, the wakefulness state detection method may also include: obtaining eye movement change information of the target detection object in a state of free movement or receiving external stimulation through the eye tracking device, and sending the eye movement change information to the wakefulness state evaluation device, wherein the eye movement change information includes at least one of pupil diameter change information, pupil displacement information and pupil deflection angle information; the wakefulness state evaluation device is also configured to update the wakefulness state of the target detection object based on the eye movement change information.

Optionally, the wakefulness state detection system further includes a target regulation module. Accordingly, the wakefulness state detection method may further include: regulating the activity state of the target neuron target through in vivo optogenetics technology by means of the target regulation module.

Fig. 4 shows a block diagram of an electronic device 10 that can be used to implement an embodiment of the present application. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and/or required herein.

As shown in FIG. 4 , the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform a variety of appropriate actions and processes according to the computer program stored in the ROM 12 or the computer program loaded from the storage unit 18 to the RAM 13. In the RAM 13, a variety of programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input/output (I/O) interface 15 is also connected to the bus 14.

A number of components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices through a computer network such as the Internet and/or various telecommunication networks.

The processor 11 may be a variety of general and/or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), a variety of dedicated artificial intelligence (AI) computing chips, a variety of processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 performs the multiple methods and processes described above, such as the wakefulness state detection method.

In some embodiments, the wakefulness state detection method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed on the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the wakefulness state detection method described above may be performed. Optionally, in other embodiments, the processor 11 may be configured to perform the wakefulness state detection method in any other appropriate manner (e.g., by means of firmware).

Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard parts (ASSPs), system on chip systems (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These embodiments can include: being implemented in one or more computer programs that can be executed and/or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, at least one input device, and at least one output device.

Computer programs for implementing the methods of the present application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions/operations specified in the flow chart and/or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

In the context of the present application, a computer readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or apparatus. A computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. Alternatively, a computer readable storage medium may be a machine readable signal medium. Examples of machine readable storage media may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a RAM, a ROM, an Erasable Programmable Read-Only Memory (EPROM) or flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a cathode ray tube (CRT) or a liquid crystal display (LCD) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: Local Area Network (LAN), Wide Area Network (WAN), blockchain network, and the Internet.

A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and virtual private servers (VPS) services.

It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the multiple steps recorded in this application can be executed in parallel, sequentially or in different orders, as long as the expected results of the technical solution of this application can be achieved, and this document is not limited here.

Claims (11)

1. A wakefulness state detection system includes: a physiological index detection device, a body posture detection device, a motor ability detection device, a stimulus response detection device, a behavior pattern detection device, an emotional response detection device and an wakefulness state evaluation device; wherein,

   The physiological index detection device is configured to collect a target physiological index of a target detection object, generate a physiological detection result corresponding to the target physiological index, and send the physiological detection result to the wakefulness state evaluation device;

   The body posture detection device is configured to detect the body posture of the target detection object, generate a posture detection result corresponding to the body posture, and send the posture detection result to the wakefulness state evaluation device;

   The motor ability detection device is configured to detect the motor information of the target detection object, generate a motor ability detection result corresponding to the motor information, and send the motor ability detection result to the wakefulness state evaluation device;

   The emotional response detection device is configured to detect emotional information of the target detection object, generate an emotional response detection result corresponding to the emotional information, and send the emotional response detection result to the wakefulness state evaluation device;

   The stimulus response detection device is configured to generate a stimulus response detection result corresponding to the target stimulus signal based on the response information of the target detection object to the target stimulus signal, and send the stimulus response detection result to the wakefulness state evaluation device, wherein the target stimulus signal includes a harmful stimulus signal;

   The behavior pattern detection device is configured to detect the behavior structure and switching pattern of the target detection object, generate a behavior pattern detection result corresponding to the behavior phenotype, and send the behavior pattern detection result to the wakefulness state evaluation device;

   The wakefulness state evaluation device is configured to determine the wakefulness state of the target detection object based on the received physiological detection results, the posture detection results, the motor ability detection results, the stimulus response detection results, the emotional reaction detection results and the behavioral pattern detection results, and display the wakefulness state.
2. The wakefulness state detection system according to claim 1, wherein the body posture detection device comprises a video acquisition module and a posture analysis module, wherein:

   The video acquisition module is configured to collect video information of the target detection object in a free activity state or in a state of external stimulation, and send the video information to the posture analysis module;

   The posture analysis module is configured to identify the posture of the target detection object through the video information and a preset artificial intelligence algorithm to obtain a posture detection result of the target detection object, and send the posture detection result to the wakefulness state evaluation device, wherein the posture detection result includes at least one of skeleton morphology information and body height information.
3. The wakefulness state detection system according to claim 1, wherein the motion ability detection device comprises a video acquisition module and a motion analysis module, wherein:

   The video acquisition module is configured to acquire a behavior video of the target detection object in a free activity or external stimulation state, and send the behavior video to the motion analysis module;

   The motion analysis module is configured to analyze the motion state of the target detection object in different states through the behavior video and a preset artificial intelligence algorithm to obtain the motion ability detection result of the target detection object, and send the motion ability detection result to the wakefulness state evaluation device, wherein the motion ability detection result includes at least one of body deflection angle information, motion distance information and motion speed information.
4. According to the wakefulness state detection system of claim 3, the motor ability detection device comprises a motion detection module and a motion analysis module, the motion detection module comprises at least one of an electromyographic signal acquisition module, an experimental treadmill test module and a rotarod test module, wherein:

   The electromyographic signal acquisition module is configured to acquire the electromyographic signal of the target detection object, use the electromyographic signal as the first motion detection signal, and send the first motion detection signal to the motion analysis module;

   The experimental treadmill test module is configured to perform a running test on the target detection object, and use the running test data as a second motion detection signal, and send the second motion detection signal to the motion analysis module;

   The rotarod test module is configured to test the target detection object, use the rotarod test data as the third motion detection signal, and send the third motion detection signal to the motion analysis module;

   The motion analysis module is configured to analyze the received motion detection signal, obtain the motion ability detection result of the target detection object, and send the motion ability detection result to the wakefulness state evaluation device, wherein the motion detection signal includes at least one of the first motion detection signal, the second motion detection signal and the third motion detection signal, and the motion ability detection result includes at least one of the muscle strength index, endurance index, coordination index and balance index of the target detection object.
5. According to the wakefulness state detection system of claim 1, wherein the behavior pattern detection device comprises a behavior video acquisition module and a behavior analysis module, wherein:

   The video acquisition module is configured to acquire a behavior video of the target detection object in a free activity or external stimulation state, and send the behavior video to the behavior analysis module;

   The behavior analysis module is configured to analyze the behavior results and switching patterns of the target detection object in different states through the behavior video and a preset artificial intelligence algorithm to obtain the behavior pattern detection result of the target detection object, and send the behavior pattern detection result to the wakefulness state evaluation device, wherein the behavior pattern detection result includes at least one of behavior action type information, action frequency information, behavior state transition information and behavior pattern switching information.
6. The wakefulness state detection system according to claim 1, wherein the stimulus response detection device comprises a stimulation unit, a response information acquisition unit and a response result detection unit, wherein:

   The stimulation unit is configured to generate a target stimulation signal in response to a stimulation trigger instruction, and apply the target stimulation signal to the target stimulation object, wherein the target stimulation signal includes at least one of a visual stimulation signal, an olfactory stimulation signal, a pain stimulation signal, and an auditory stimulation signal;

   The response information acquisition unit is configured to acquire response information of the target detection object in response to the target stimulation signal, and send the response information to the response result detection unit;

   The response result detection unit is configured to generate a stimulation response detection result corresponding to the target stimulation signal according to the response information, and send the stimulation response detection result to the wakefulness state evaluation device.
7. The wakefulness state detection system according to claim 1 further comprises: an electroencephalogram signal detection device, wherein:

   The EEG signal detection device is configured to detect the EEG signal of the target detection object, generate an EEG detection result corresponding to the EEG signal, and send the EEG detection result to the wakefulness state evaluation device;

   The wakefulness state evaluation device is further configured to update the wakefulness state of the target detection object based on the EEG detection result.
8. According to the wakefulness state detection system of claim 7, the EEG signal detection device comprises an EEG signal acquisition module, a neuron signal acquisition module and an EEG detection module, wherein:

   The EEG signal acquisition module is configured to acquire the cortical EEG signal of the target detection object and send the cortical EEG signal to the EEG detection module;

   The neuron signal acquisition module is configured to obtain the neural activity information and activity change information of the subcortical brain area of the target detection object, and send the neural activity information and the activity change information to the EEG detection module, wherein the neuron signal acquisition module includes at least one of a calcium ion optical fiber recording unit and a two-photon in vivo calcium imaging unit;

   The EEG detection module is configured to analyze the band characteristics of the cortical EEG signal within a preset band based on the cortical EEG signal, the neural activity information of the subcortical brain area, and the activity change information, and use the band characteristics as the EEG detection results corresponding to the cortical EEG signal, and send the EEG detection results to the wakefulness state evaluation device, wherein the band characteristics include at least one of amplitude, frequency, energy value, and neural activity change information.
9. The wakefulness state detection system according to claim 1, further comprising: an eye tracking device, wherein:

   The eye tracking device is configured to obtain eye movement change information of the target detection object when the target detection object is in a free movement state or receiving external stimulation, and send the eye movement change information to the wakefulness state evaluation device; wherein the eye movement change information includes at least one of pupil diameter change information, pupil displacement information and pupil deflection angle information;

   The wakefulness state evaluation device is further configured to update the wakefulness state of the target detection object based on the eye movement change information.
10. The wakefulness state detection system according to claim 1 further comprises: a target control module, wherein:

    The target regulation module is configured to regulate the activity state of the target neuron target through in vivo optogenetics technology.
11. A method for detecting a state of wakefulness is applied to a system for detecting a state of wakefulness, wherein the system comprises a physiological index detection device, a body posture detection device, a motor ability detection device, a behavior pattern detection device, a stimulus response detection device, an emotional response detection device, and a state of wakefulness evaluation device; wherein the method for detecting a state of wakefulness comprises:

    The target physiological index of the target detection object is collected through the physiological index detection device, and a physiological detection result corresponding to the target physiological index is generated, and the physiological detection result is sent to the wakefulness state evaluation device;

    The body posture of the target detection object is detected by the body posture detection device, a posture detection result corresponding to the body posture is generated, and the posture detection result is sent to the wakefulness state evaluation device;

    The motion information of the target detection object is detected by the motion ability detection device, a motion ability detection result corresponding to the motion information is generated, and the motion ability detection result is sent to the wakefulness state evaluation device;

    The emotional response detection device detects emotional information of the target detection object, generates an emotional response detection result corresponding to the emotional information, and sends the emotional response detection result to the wakefulness state evaluation device;

    The behavior pattern detection device detects the behavior structure and switching pattern of the target detection object, generates a behavior pattern detection result corresponding to the behavior phenotype, and sends the behavior pattern detection result to the wakefulness state evaluation device;

    By means of the stimulus response detection device, based on the response information of the target detection object to the target stimulus signal, a stimulus response detection result corresponding to the target stimulus signal is generated, and the stimulus response detection result is sent to the wakefulness state evaluation device, wherein the target stimulus signal includes a harmful stimulus signal;

    Through the wakefulness state evaluation device, the wakefulness state of the target detection object is determined based on the received physiological detection results, the posture detection results, the motor ability detection results, the stimulus response detection results, the behavior pattern detection results and the emotional reaction detection results, and the wakefulness state is displayed.

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