A non-contact electroencephalogram monitoring method and system

Abstract

The present application relates to the field of EEG monitoring technology, and in particular to a non-contact EEG monitoring method and system, the method comprising: obtaining a head image corresponding to a target user at the current moment; determining the head posture of the target user at the current moment based on the head image corresponding to the current moment; and determining the position of an EEG cap based on the head posture at the current moment and the head posture corresponding to the previous moment, wherein the EEG cap includes multiple EEG electrodes, and the multiple EEG electrodes monitor the EEG data of the target user in the position corresponding to the EEG cap. This method can solve the problems of position offset and signal instability during head movement during non-contact EEG acquisition.

Description

Technical Field

[0001] The present application relates to the technical field of electroencephalogram (EEG) monitoring, and in particular to a non-contact EEG monitoring method and system. Background Art

[0002] Currently, EEG signal acquisition relies primarily on contact-type wet and dry electrodes. Wet electrodes require the use of conductive paste to ensure signal quality, which is not only cumbersome to operate, but also increases electrode impedance over time as the paste dries, affecting signal stability. Dry electrodes rely on a close contact with the scalp, which can also cause discomfort. Both methods have limitations in clinical application and are particularly unsuitable for long-term EEG monitoring in premature infants or newborns. Because newborn skin is delicate, contact electrodes can cause skin damage, increasing the risk of infection.

[0003] Compared with contact electrodes, non-contact electrodes are not directly attached to the scalp during signal acquisition, thus avoiding irritation and damage to the skin of newborns to a certain extent.

[0004] However, due to the lack of stable physical fixation, the relative position between the electrodes and the scalp may shift if the newborn's head moves, resulting in unstable signal acquisition. For example, an electrode originally used to collect EEG at the Fz position may instead collect signals from a nearby position, such as F4, after a slight deflection of the head, thus affecting the precise monitoring of activity in a specific brain region and the effectiveness of subsequent analysis. Summary of the Invention

[0005] One purpose of the present application is to propose a non-contact EEG monitoring method and system. The technical solution provided in this application can dynamically adjust the posture of the EEG cap and brain electrodes according to the real-time posture of the target user, thereby realizing the technical problem of collecting effective EEG data under a non-contact system.

[0006] According to an embodiment of the first aspect of the present application, a non-contact EEG monitoring method is provided, the method comprising: obtaining a head image corresponding to a target user at a current moment; determining the head posture corresponding to the target user at the current moment based on the head image corresponding to the current moment; determining the posture of an EEG cap based on the head posture at the current moment and the head posture corresponding to a previous moment, wherein the EEG cap comprises a plurality of EEG electrodes, and the plurality of EEG electrodes monitor the EEG data of the target user in the posture corresponding to the EEG cap.

[0007] In some embodiments, determining the position of the EEG cap based on the head posture at the current moment and the head posture corresponding to the previous moment includes:

[0008] Determining a distance between the head posture at the current moment and the head posture at the previous moment;

[0009] In response to the distance being greater than a preset threshold, adjusting the current posture of the EEG cap based on the head posture at the current moment, and the brain electrodes in the EEG cap continue to monitor the EEG data of the target user in the adjusted posture;

[0010] In response to the distance being no greater than a preset threshold, the EEG electrodes in the EEG cap continue to monitor the EEG data of the target user in the current posture.

[0011] In some embodiments, adjusting the current position of the EEG cap based on the head position at the current moment includes:

[0012] Taking the head posture of the target user at the current moment as the control target of the robotic arm;

[0013] The robotic arm controls and adjusts the current position and current direction of the EEG cap so that the EEG cap moves to a posture that matches the head position and head direction of the target user at the current moment, and the brain electrodes in the EEG cap collect the EEG data of the target user at the adjusted posture.

[0014] In some embodiments, the step of determining the head posture of the target user includes:

[0015] Determine a head edge point coordinate set of the target user based on the head image;

[0016] The head pose of the target user is determined based on the head edge point coordinate set.

[0017] In some embodiments, the method further comprises:

[0018] determining a head size of the target user based on the head image of the target user;

[0019] Determining a scaling factor of the EEG cap and a scaling factor of an arrangement of brain electrodes in the EEG cap based on a head size of the target user;

[0020] The size of the EEG cap is adjusted based on the scaling factor, and the coordinate position layout of the brain electrodes in the EEG cap is adjusted based on the arrangement scaling factor.

[0021] In some embodiments, determining the scaling factor of the EEG cap and the scaling factor of the arrangement of brain electrodes in the EEG cap based on the head size of the target user includes:

[0022] Determining the initial size of the EEG cap and the initial arrangement coordinates of the brain electrodes in the EEG cap;

[0023] determining a scaling factor of the EEG cap based on the head size of the target user and the initial size of the EEG cap, and adjusting the size of the EEG cap based on the scaling factor so that the size of the EEG cap matches the head size of the target user;

[0024] Based on the scaling coefficient of the EEG cap and the initial arrangement coordinates of the brain electrodes in the EEG cap, the arrangement scaling coefficient of the brain electrodes in the EEG cap is determined, and based on the arrangement scaling coefficient, the target coordinates of the brain electrodes are determined, so that the brain electrodes monitor the EEG data of the target user at the target coordinates.

[0025] In some embodiments, the head size of the target user includes a horizontal size of the head and a vertical size of the head;

[0026] The step of determining the head size of the target user includes:

[0027] Determining ear key points, nose key points, and head key points of the target user based on the head image, wherein the ear key points include left ear key points and right ear key points;

[0028] Determine the lateral size of the head of the target user based on the ear key points and the head key points;

[0029] The longitudinal size of the head of the target user is determined based on the nose key points and the head key points.

[0030] In some embodiments, the method further includes acquiring a head image of the target user based on a depth sensor;

[0031] The step of determining the shooting posture of the depth sensor includes:

[0032] Acquire a working plane image corresponding to a working plane and a plane normal vector corresponding to the working plane based on a depth sensor, wherein the working plane includes a plane corresponding to a working platform for monitoring EEG data of the target user;

[0033] The shooting position and shooting direction of the depth sensor are determined based on the on-site observation distance, the working distance of the depth sensor, and the plane normal vector.

[0034] In some embodiments, after acquiring the working plane image corresponding to the working plane, the method further includes:

[0035] extracting a plurality of internal coordinate point sets from the work plane image based on a preset marking template;

[0036] The coordinate systems of the plurality of internal coordinate point sets are converted into a world coordinate system, and a plane normal vector corresponding to the working plane is determined based on the internal coordinate point sets in the world coordinate system.

[0037] The present application also provides a non-contact EEG monitoring system, which includes: a support module, a robotic arm module, an image acquisition module, a work platform module, an EEG cap module, and a control module;

[0038] The image acquisition module is mounted on the support module and is used to acquire a head image of a target user and / or an image of a work platform corresponding to the work platform module;

[0039] The EEG cap module is installed at the end of a robotic arm, and the robotic arm is used to adjust the position of the EEG cap. The electrodes in the EEG cap are used to monitor the EEG data of the target user.

[0040] The work platform module is used to carry target users;

[0041] The control module is used to control the robotic arm to adjust the posture of the EEG cap based on the head posture of the target user, and the brain electrodes in the EEG cap are used to monitor the EEG data of the target user.

[0042] In some embodiments, the brain electrodes are arranged in an EEG cap, and the position layout of the brain electrodes in the EEG cap is associated with the size of the EEG cap. When the size of the EEG cap changes, the position layout of the brain electrodes changes; the control module is used to send the size information of the EEG cap to the EEG cap, and the EEG cap adjusts the size of the EEG cap and the position layout of the brain electrodes in the EEG cap based on the received size information.

[0043] In some embodiments, the size of the EEG cap is adjustable, and the size of the EEG cap matches the head size of the target user; the control module determines the size information of the EEG cap based on the acquired head size of the target user, and sends the size information to the EEG cap to adjust the size of the EEG cap.

[0044] In some embodiments, the control module determines the posture of the EEG cap based on the head posture of the target user, and sends the posture of the EEG cap to the robotic arm. The robotic arm controls the posture of the electrode cap at the end of the robotic arm to match the head posture of the target user based on the received posture information.

[0045] In some embodiments, the control module determines the size information of the EEG cap based on the acquired head size of the target user, including: the control module determines the ear key points, nose key points, and head key points of the target user based on the head image acquired by the image acquisition module, wherein the ear key points include the left ear key points and the right ear key points;

[0046] The control module determines the lateral size of the head of the target user based on the ear key points and the head key points;

[0047] The control module determines the longitudinal size of the head of the target user based on the nose key points and the head key points;

[0048] The control module determines the head size of the target user based on the transverse size of the head and the longitudinal size of the head, and the size of the EEG cap matches the head size of the target user.

[0049] In some embodiments, the control module determines the position of the EEG cap based on the head position of the target user, including:

[0050] The control module obtains the head image corresponding to the target user at the current moment acquired by the image acquisition module;

[0051] The control module determines the head posture of the target user corresponding to the current moment based on the acquired head image corresponding to the current moment;

[0052] The control module determines the posture of the EEG cap based on the head posture at the current moment and the head posture corresponding to the previous moment, wherein the EEG cap includes multiple brain electrodes, and the multiple brain electrodes monitor the EEG data of the target user in the posture corresponding to the EEG cap.

[0053] In some embodiments, the control module determines the position of the EEG cap based on the head position at the current moment and the head position corresponding to the previous moment, including:

[0054] The control module determines a distance between the head posture at the current moment and the head posture at the previous moment;

[0055] In response to the distance being greater than a preset threshold, the control module controls the robotic arm to adjust the current posture of the EEG cap based on the head posture at the current moment, so that the electrodes in the EEG cap continue to monitor the EEG data of the target user in the adjusted posture;

[0056] In response to the distance being no greater than a preset threshold, the control module controls the brain electrodes in the EEG cap to continue monitoring the EEG data of the target user in the current posture.

[0057] In some embodiments, the controlling mechanical arm adjusts the current posture of the EEG cap based on the head posture at the current moment, including:

[0058] Taking the head posture of the target user at the current moment as the control target of the robotic arm;

[0059] The robotic arm controls and adjusts the current position and current direction of the EEG cap so that the EEG cap moves to a posture that matches the head position and head direction of the target user at the current moment, and the brain electrodes in the EEG cap collect the EEG data of the target user at the adjusted posture.

[0060] In some embodiments, the step of determining the head posture of the target user includes:

[0061] The control module determines a set of head edge point coordinates of the target user based on the head image;

[0062] The control module determines the head pose of the target user based on the head edge point coordinate set.

[0063] In some embodiments, the system further comprises:

[0064] The control module determines the head size of the target user based on the head image of the target user;

[0065] The control module determines a scaling factor of the EEG cap and a scaling factor of an arrangement of brain electrodes in the EEG cap based on a head size of the target user;

[0066] The control module sends the scaling factor to the EEG cap to adjust the size of the EEG cap, and adjusts the coordinate position layout of the brain electrodes in the EEG cap based on the arrangement scaling factor.

[0067] In some embodiments, the control module determines the scaling factor of the EEG cap and the scaling factor of the arrangement of the brain electrodes in the EEG cap based on the head size of the target user, including:

[0068] The control module determines the initial size of the EEG cap and the initial arrangement coordinates of the brain electrodes in the EEG cap;

[0069] The control module determines a scaling factor of the EEG cap based on the head size of the target user and the initial size of the EEG cap, and sends the scaling factor to the EEG cap to adjust the size of the EEG cap so that the size of the EEG cap matches the head size of the target user;

[0070] The control module determines the arrangement scaling coefficient of the EEG cap and the initial arrangement coordinates of the EEG electrodes in the EEG cap based on the scaling coefficient of the EEG cap. The control module determines the target coordinates of the EEG electrodes based on the arrangement scaling coefficient, so that the EEG electrodes monitor the EEG data of the target user at the target coordinates.

[0071] In some embodiments, the system further comprises:

[0072] Acquire a head image of the target user based on a depth sensor;

[0073] The step of determining the shooting posture of the depth sensor includes:

[0074] The control module acquires a working plane image corresponding to a working plane and a plane normal vector corresponding to the working plane based on a depth sensor, wherein the working plane includes a plane corresponding to a working platform for monitoring EEG data of the target user;

[0075] The control module determines a shooting position and a shooting direction of the depth sensor based on a field observation distance, a working distance of the depth sensor, and the plane normal vector.

[0076] In some embodiments, after the image acquisition module acquires the working plane image corresponding to the working plane, the system further includes:

[0077] The control module extracts a plurality of internal coordinate point sets from the work plane image based on a preset marking template;

[0078] The control module converts the coordinate systems of the plurality of internal coordinate point sets into a world coordinate system, and determines a plane normal vector corresponding to the working plane based on the internal coordinate point sets in the world coordinate system.

[0079] The present application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the non-contact EEG monitoring method provided in any of the above embodiments.

[0080] A computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the non-contact EEG monitoring method provided in any one of the above embodiments are implemented.

[0081] A computer program product stores a program or instruction thereon, which, when executed by a processor, implements the steps of the non-contact EEG monitoring method provided in any one of the above embodiments.

[0082] The EEG monitoring method provided in this application can calculate the similarity between the current head posture and the previous N historical postures based on the current head posture and the previous N historical head postures, so as to determine whether the EEG cap needs to be adjusted and how to adjust the posture of the EEG cap to ensure that the brain electrodes can continuously and accurately monitor the monitored brain area, thereby continuously and stably monitoring the EEG signals of the target user.

[0083] The non-contact EEG monitoring method provided in this application can be applied to neonatal EEG detection, and provides a stable positioning non-contact electrode system for neonatal EEG monitoring, which can solve the problems of acquisition position offset and signal instability when the head moves during non-contact EEG acquisition.

[0084] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become obvious from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0085] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0086] Figure 1 1 is a flow chart of a non-contact EEG monitoring method provided in one embodiment of the present application;

[0087] Figure 2 1 is a flow chart of a method for adjusting the posture of an EEG cap provided in one embodiment of the present application;

[0088] Figure 3 is a flow chart of a non-contact EEG monitoring method provided in another embodiment of the present application;

[0089] Figure 4 is a schematic diagram of the non-contact EEG monitoring system provided by this application;

[0090] Figure 5 It is a structural diagram of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0091] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0092] The technical solutions between the various embodiments of the present invention can be combined with each other, but they must be based on the fact that ordinary technicians in this field can implement them. When the combination of technical solutions is mutually contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0093] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0094] See also Figure 1 The present application provides an EEG monitoring method that adopts a non-contact EEG signal acquisition method. During the EEG signal acquisition process, the brain electrodes are not directly attached to the scalp. The EEG signals of the monitored brain area are accurately monitored by adjusting the posture of the brain electrodes.

[0095] The process includes: S101, obtaining a head image corresponding to a target user at a current moment.

[0096] In some embodiments, target users may include infants or other users who require EEG monitoring.

[0097] In some embodiments, the head image at the current moment may include an image acquired in real time by a depth sensor or other image acquisition device.

[0098] In some embodiments, the image acquisition device can be fixed on a bracket, wherein the bracket is immovable, and the position of the image acquisition device can be adjusted.

[0099] S102: Determine the head posture of the target user corresponding to the current moment based on the head image corresponding to the current moment.

[0100] Among them, the pose includes position and orientation.

[0101] In some embodiments, after obtaining the head image corresponding to the target user at the current moment through the image acquisition device, it also includes performing posture analysis on the head image to determine the head position and head direction of the target user at the current moment.

[0102] S103, determining the posture of the EEG cap based on the head posture at the current moment and the head posture corresponding to the previous moment, wherein the EEG cap includes multiple brain electrodes, and the multiple brain electrodes monitor the EEG data of the target user in the posture corresponding to the EEG cap.

[0103] Among them, the EEG cap is similar to a helmet, and brain electrodes can be arranged inside the helmet, and each brain electrode can move horizontally and vertically.

[0104] In some embodiments, the previous moment is earlier than the current moment, and the head posture corresponding to the previous moment is a historical head position and direction calculated based on the head image collected at the previous moment.

[0105] In some embodiments, the EEG cap's position can be determined based on the current head position and the previous N historical head positions. The EEG cap includes multiple EEG electrodes, which are used to monitor the target user's EEG data. N is an integer greater than or equal to 1.

[0106] In some embodiments, the target user may include an infant. When collecting brain data from an infant, the infant's head is prone to uncontrolled movement, which may cause the relative position between the brain electrodes and the infant's scalp to shift, resulting in unstable position of the collected signal. Therefore, during the EEG monitoring process, it is necessary to continuously obtain an image of the infant's head. Based on the head image corresponding to the current moment, the infant's head position and head direction at the current moment are determined. The head posture at the current moment is compared with the historical posture at one or more previous moments to assess the magnitude of the change in the infant's head posture, and then determine whether the position and direction of the brain electrodes need to be adjusted to ensure the accuracy of the infant's brain data monitoring.

[0107] In the above embodiment, when the target user is a newborn or infant, non-contact EEG monitoring can be used to avoid irritation and damage to the skin of the newborn or infant. This non-contact EEG monitoring method prevents the EEG cap from directly contacting the infant's head. However, when the infant's head moves, the electrodes can easily deviate from the EEG monitoring area, resulting in inaccurate EEG data monitoring.

[0108] The EEG monitoring method provided in this application can calculate the similarity between the current head posture and the previous N historical postures based on the current head posture and the previous N historical head postures, so as to determine whether the EEG cap needs to be adjusted and how to adjust the posture of the EEG cap to ensure that the brain electrodes can continuously and accurately monitor the monitored brain area, thereby continuously and stably monitoring the EEG signals of the target user.

[0109] Figure 2 FIG. 1 is a flow chart of steps for determining the position of an EEG cap provided in one embodiment. Figure 2 As shown, in some embodiments, determining the position of the EEG cap based on the head posture at the current moment and the head posture corresponding to the previous moment includes:

[0110] S201: Determine the distance between the head posture at the current moment and the head posture at the previous moment.

[0111] S202: In response to the distance being greater than a preset threshold, the current posture of the EEG cap is adjusted based on the head posture at the current moment, and the brain electrodes in the EEG cap continue to monitor the EEG data of the target user in the adjusted posture.

[0112] S203 , in response to the distance being not greater than a preset threshold, the EEG electrodes in the EEG cap continue to monitor the EEG data of the target user in the current posture.

[0113] In some embodiments, the position of the EEG cap can be determined based on the current head posture and the previous N historical head postures, including: determining the distance between the current head posture and the previous N head postures. If the distance is greater than a preset threshold, it indicates that the target user's head posture has changed significantly and the position of the EEG cap needs to be adjusted synchronously. Therefore, the position of the EEG cap can be adjusted based on the current head posture, and the EEG data of the target user's head can be continuously monitored based on the adjusted EEG cap posture, so that the position of the EEG cap always remains consistent with the target user's head posture.

[0114] In the above embodiment, EEG monitoring is performed on a specific area of the target user's head using the electrodes in the EEG cap. A pre-set EEG electrode deviation threshold is used to calculate the distance between the current head posture and the previous N head postures at the previous moment in real time. If the distance is greater than the preset threshold, the EEG cap position is adjusted based on the previous posture, allowing the EEG cap electrodes to continuously and accurately monitor the specific area of the target user's head. If the distance is less than or equal to the preset threshold, it indicates that the target user's posture is consistent or substantially consistent between the current moment and the previous moment. There is no need to adjust the EEG cap position or the EEG electrodes at the current moment, so EEG monitoring can continue at the current moment based on the EEG cap position at the previous moment. At the next moment, the target user's head posture can continue to be obtained through sensors, and the distance between the current head posture and the previous N head postures can be repeatedly determined. The difference between the current distance and the preset threshold is determined, and the judgment result determines whether to adjust the EEG cap posture.

[0115] It is understandable that the brain electrodes are set in the EEG cap, and adjusting the position of the EEG cap also adjusts the position of the brain electrodes.

[0116] In some embodiments, adjusting the current position of the EEG cap based on the head posture at the current moment includes: taking the head posture of the target user at the current moment as the control target of a robotic arm, and controlling the robotic arm to adjust the current position and current direction of the EEG cap so that the EEG cap moves to a position that matches the head position and head direction of the target user at the current moment, and the brain electrodes in the EEG cap collect EEG data of the target user at the adjusted position.

[0117] Specifically, the EEG cap can be placed at the end of a robotic arm, and its position can be controlled by the robotic arm. When it detects that the target user's head posture has changed significantly at the current moment, the robotic arm synchronously adjusts the EEG cap's position to match the target user's head posture at the current moment, enabling continuous and accurate detection of the target user's head EEG data.

[0118] In some embodiments, the step of determining the head pose of the target user includes: determining a set of head edge point coordinates of the target user based on the head image; and determining the head pose of the target user based on the set of head edge point coordinates.

[0119] In some embodiments, the authorized head image can be segmented based on an image segmentation algorithm to remove irrelevant information to obtain a target image, and then edge detection can be performed on the target image using an edge detection algorithm to obtain an edge point coordinate set of the head image, and the head posture of the target user can be determined based on the head edge point coordinate set.

[0120] It is understandable that the edge detection algorithm and the image segmentation algorithm can be existing mature algorithms and are not limited here.

[0121] In some embodiments, the method further includes: determining the head size of the target user based on the head image of the target user; determining the scaling factor of the EEG cap and the layout scaling factor of the brain electrodes in the EEG cap based on the head size of the target user; adjusting the size of the EEG cap based on the scaling factor, and adjusting the coordinate position layout of the brain electrodes in the EEG cap based on the layout scaling factor.

[0122] It is understandable that the head sizes of different target users are different, so different target users have different requirements for the size of the EEG cap. It is very important to set an EEG cap that matches the head size of the corresponding target user. This is the basic condition for obtaining accurate monitoring data.

[0123] In some embodiments, it also includes determining the head size of the target user based on the head image of the target user, and then adjusting the size of the EEG cap based on the target user's head size in a personalized and adaptive manner, so that the size of the EEG cap matches the head size of the target user.

[0124] The brain electrodes are set in the EEG cap, and the position of each brain electrode in the EEG cap can be changed. When the size of the EEG cap changes, the position of each brain electrode in the EEG cap will also change adaptively.

[0125] In some embodiments, the relative position relationship of the brain electrodes in the EEG cap is fixed. The initial layout coordinates of the brain electrodes in the EEG cap can be obtained first, and the target coordinates of the brain electrodes can be obtained by scaling the distance between the brain electrodes based on the scaling coefficient of the EEG cap.

[0126] In this way, the head size of the target user is determined based on the head image of the target user, and then the size of the EEG cap and the position of the brain electrodes in the EEG cap are adaptively adjusted, so that the final adjusted EEG cap and brain electrodes match the target user to monitor and obtain more accurate brain data.

[0127] In some embodiments, the head size of the target user includes a horizontal size of the head and a vertical size of the head;

[0128] The step of determining the head size of the target user includes: determining the ear key points, nose key points, and head key points of the target user based on the head image, wherein the ear key points include left ear key points and right ear key points; determining the horizontal size of the head of the target user based on the ear key points and the head key points; and determining the vertical size of the head of the target user based on the nose key points and the head key points.

[0129] In some embodiments, the head size can be determined based on the head key points. For example, after obtaining a head image based on a sensor, a trained key point detection model is used to output the coordinates of the head key points, nose key points, left ear key points, and right ear key points.

[0130] The coordinates of the left ear key point concave and the right ear key point are used with the coordinates of the head edge point set to fit the top of the head curve, and the length of the curve is calculated as the lateral size of the head.

[0131] Calculate the distance between the key point of the nose and the midpoint of the top curve along the surface of the head, and multiply it by 2 to get the longitudinal size of the head.

[0132] The head size of the target user is determined based on the horizontal size and the vertical size of the head of the target user, so as to determine the size of the EEG cap and the position coordinate arrangement of the brain electrodes according to the head size.

[0133] In some embodiments, the method further includes acquiring a head image of the target user based on a depth sensor;

[0134] The step of determining the shooting posture of the depth sensor includes: obtaining a working plane image corresponding to a working plane and a plane normal vector corresponding to the working plane based on the depth sensor, wherein the working plane includes a plane corresponding to a working platform for monitoring the EEG data of the target user; determining the shooting position and shooting direction of the depth sensor based on the on-site observation distance, the working distance of the depth sensor, and the plane normal vector.

[0135] In some embodiments, a head image of the target user may be captured by a depth sensor, and the head pose and head size of the target user may be calculated based on the head image.

[0136] In some embodiments, the posture setting of the sensor is very important. If the posture setting of the sensor is unreasonable, accurate head posture and head size data cannot be obtained from the captured head image, which may cause unreasonable posture of brain electrode monitoring and inaccurate brain data.

[0137] In some embodiments, the method further includes setting a shooting posture of the sensor. First, the sensor collects a working plane image corresponding to the working plane, and determines the shooting posture of the sensor based on the working plane image.

[0138] In some embodiments, after obtaining the working plane image corresponding to the working plane, the method further includes: extracting multiple internal coordinate point sets from the working plane image based on a preset marking template; converting the coordinate system of the multiple internal coordinate point sets into a world coordinate system, and determining the plane normal vector corresponding to the working plane based on the internal coordinate point set in the world coordinate system.

[0139] Specifically, the target user being inspected lies flat on the work platform, and the work platform is photographed by the RGBD sensor to obtain an image of the work plane. The 2D edge detection / image segmentation algorithm is combined with a marker template of known shape and size to obtain the internal point coordinates of n markers on the work plane and the corresponding depth information. In some embodiments, the coordinates of these points can be recorded as C_POINTS (camera_set_1, camera_set_2,…, camera_set_n), and then the extrinsic parameters are used to convert the 3D coordinates in the camera coordinate system to the world coordinate system W_POINTS (world_set_1, world _set_2,…, world_set_n) of the bracket base.

[0140] Using the coordinates of all points in W_POINTS, we perform plane fitting to obtain the plane normal vector N = [nx, ny, nz]. We then set the optimal observation distance d based on the sensor's working distance and field of view. We then calculate the center position of the work plane, P_c = [x_c, y_c, d_c], based on the set of marker points. The sensor's image position is then P1 = P_c + N * d, perpendicular to the work plane of the work platform. Based on this determined position and orientation, we determine the target sensor pose. The robotic arm then adjusts the sensor to this target pose to capture data from the target user's head.

[0141] In some embodiments, the present application provides an EEG monitoring method, comprising the following steps:

[0142] Step 1: The sensor collects the target user's head data, performs global head / other feature point detection such as binaural posture detection, and increases the detection counter by 1.

[0143] Step 2 checks whether the counter is 1, if so, go to step 3, otherwise go to step 5

[0144] Step 3: Record the timestamp and posture information of this detection as the initial posture;

[0145] Step 4 waits for time interval t and enters step 1 again;

[0146] Step 5: Calculate the distance between the current pose and the previous N historical poses (Euclidean distance / similarity)

[0147] Step 6: Check if the distance exceeds the set threshold d. If yes, go to step 7; otherwise, go to step 4.

[0148] Step 7 adjusts the EEG electrode posture according to the current posture, sets the detection counter to 1, sends all currently recorded posture information and time information to the EEG signal motion compensation module, and returns to step 4.

[0149] like Figure 4 As shown, the present application also provides a non-contact EEG monitoring system, which includes: a support module 402, a robotic arm module 401, an image acquisition module 403, a work platform module 405, an EEG cap module and a control module 406;

[0150] The image acquisition module 403 is installed on the support module 402 and is used to acquire a head image of a target user and / or an image of a work platform corresponding to the work platform module 405;

[0151] The EEG cap module is installed at the end of the robotic arm 401. The robotic arm 401 is used to adjust the posture of the EEG cap. The electrodes in the EEG cap are used to monitor the EEG data of the target user.

[0152] The work platform module 405 is used to carry target users;

[0153] The control module 406 controls the robotic arm 401 to adjust the posture of the EEG cap based on the head posture of the target user. The brain electrodes in the EEG cap are used to monitor the EEG data of the target user.

[0154] The end 404 of the robotic arm is used to clamp the EEG cap, and the brain electrodes in the EEG cap are used to collect EEG data of the target user.

[0155] The control module 406 is used to calculate posture information, size information, etc. based on the acquired image data, and control the movement of the robotic arm to adjust the posture of the EEG cap through the calculated posture information, and control the size of the EEG cap to adjust based on the calculated size information to adapt to the head size of the corresponding target user.

[0156] It should be noted that Figure 4 This is only an example architecture of the non-contact EEG monitoring system provided in this application, and this example architecture does not constitute a limitation to the system architecture of this application.

[0157] In some embodiments, the brain electrodes are arranged in an EEG cap, and the position layout of the brain electrodes in the EEG cap is associated with the size of the EEG cap. When the size of the EEG cap changes, the position layout of the brain electrodes changes; the control module is used to send the size information of the EEG cap to the EEG cap, and the EEG cap adjusts the size of the EEG cap and the position layout of the brain electrodes in the EEG cap based on the received size information.

[0158] In some embodiments, the size of the EEG cap is adjustable, and the size of the EEG cap matches the head size of the target user; the control module determines the size information of the EEG cap based on the acquired head size of the target user, and sends the size information to the EEG cap to adjust the size of the EEG cap.

[0159] In some embodiments, the control module determines the posture of the EEG cap based on the head posture of the target user, and sends the posture of the EEG cap to the robotic arm. The robotic arm controls the posture of the electrode cap at the end of the robotic arm to match the head posture of the target user based on the received posture information.

[0160] In some embodiments, the control module determines the size information of the EEG cap based on the acquired head size of the target user, including: the control module determines the ear key points, nose key points, and head key points of the target user based on the head image acquired by the image acquisition module, wherein the ear key points include the left ear key points and the right ear key points;

[0161] The control module determines the lateral size of the head of the target user based on the ear key points and the head key points;

[0162] The control module determines the longitudinal size of the head of the target user based on the nose key points and the head key points;

[0163] The control module determines the head size of the target user based on the transverse size of the head and the longitudinal size of the head, and the size of the EEG cap matches the head size of the target user.

[0164] In some embodiments, the control module determines the posture of the EEG cap based on the head posture of the target user, including:

[0165] The control module obtains the head image corresponding to the target user at the current moment acquired by the image acquisition module;

[0166] The control module determines the head posture of the target user corresponding to the current moment based on the acquired head image corresponding to the current moment;

[0167] The control module determines the posture of the EEG cap based on the head posture at the current moment and the head posture corresponding to the previous moment, wherein the EEG cap includes multiple brain electrodes, and the multiple brain electrodes monitor the EEG data of the target user in the posture corresponding to the EEG cap.

[0168] In some embodiments, the control module determines the position of the EEG cap based on the head position at the current moment and the head position corresponding to the previous moment, including:

[0169] The control module determines a distance between the head posture at the current moment and the head posture at the previous moment;

[0170] In response to the distance being greater than a preset threshold, the control module controls the robotic arm to adjust the current posture of the EEG cap based on the head posture at the current moment, so that the electrodes in the EEG cap continue to monitor the EEG data of the target user in the adjusted posture;

[0171] In response to the distance being no greater than a preset threshold, the control module controls the brain electrodes in the EEG cap to continue monitoring the EEG data of the target user in the current posture.

[0172] In some embodiments, the controlling mechanical arm adjusts the current posture of the EEG cap based on the head posture at the current moment, including:

[0173] Taking the head posture of the target user at the current moment as the control target of the robotic arm;

[0174] The robotic arm controls and adjusts the current position and current direction of the EEG cap so that the EEG cap moves to a posture that matches the head position and head direction of the target user at the current moment, and the brain electrodes in the EEG cap collect the EEG data of the target user at the adjusted posture.

[0175] In some embodiments, the step of determining the head posture of the target user includes:

[0176] The control module determines a set of head edge point coordinates of the target user based on the head image;

[0177] The control module determines the head pose of the target user based on the head edge point coordinate set.

[0178] In some embodiments, the system further comprises:

[0179] The control module determines the head size of the target user based on the head image of the target user;

[0180] The control module determines a scaling factor of the EEG cap and a scaling factor of an arrangement of brain electrodes in the EEG cap based on a head size of the target user;

[0181] The control module sends the scaling factor to the EEG cap to adjust the size of the EEG cap, and adjusts the coordinate position layout of the brain electrodes in the EEG cap based on the arrangement scaling factor.

[0182] In some embodiments, the control module determines the scaling factor of the EEG cap and the scaling factor of the arrangement of the brain electrodes in the EEG cap based on the head size of the target user, including:

[0183] The control module determines the initial size of the EEG cap and the initial arrangement coordinates of the brain electrodes in the EEG cap;

[0184] The control module determines a scaling factor of the EEG cap based on the head size of the target user and the initial size of the EEG cap, and sends the scaling factor to the EEG cap to adjust the size of the EEG cap so that the size of the EEG cap matches the head size of the target user;

[0185] The control module determines the arrangement scaling coefficient of the EEG cap and the initial arrangement coordinates of the EEG electrodes in the EEG cap based on the scaling coefficient of the EEG cap. The control module determines the target coordinates of the EEG electrodes based on the arrangement scaling coefficient, so that the EEG electrodes monitor the EEG data of the target user at the target coordinates.

[0186] In some embodiments, the system further comprises:

[0187] Acquire a head image of the target user based on a depth sensor;

[0188] The step of determining the shooting posture of the depth sensor includes:

[0189] The control module acquires a working plane image corresponding to a working plane and a plane normal vector corresponding to the working plane based on a depth sensor, wherein the working plane includes a plane corresponding to a working platform for monitoring EEG data of the target user;

[0190] The control module determines a shooting position and a shooting direction of the depth sensor based on a field observation distance, a working distance of the depth sensor, and the plane normal vector.

[0191] In some embodiments, after the image acquisition module acquires the working plane image corresponding to the working plane, the system further includes:

[0192] The control module extracts a plurality of internal coordinate point sets from the work plane image based on a preset marking template;

[0193] The control module converts the coordinate systems of the plurality of internal coordinate point sets into a world coordinate system, and determines a plane normal vector corresponding to the working plane based on the internal coordinate point sets in the world coordinate system.

[0194] In some embodiments, the non-contact EEG monitoring system further includes: after the image acquisition module acquires the head image of the target user, the head image is sent to the control module, the control module determines the head posture of the target user at the current moment based on the head image corresponding to the current moment, determines the posture of the EEG cap based on the head posture at the current moment and the head posture corresponding to the previous moment, and controls the robotic arm module to adjust the posture of the EEG cap, wherein the EEG cap includes multiple brain electrodes, and the multiple brain electrodes monitor the EEG data of the target user in the posture corresponding to the EEG cap.

[0195] In some embodiments, the non-contact EEG monitoring system further includes:

[0196] The control module determines the position of the EEG cap based on the head posture at the current moment and the head posture corresponding to the previous moment, including: the control module determines the distance between the head posture at the current moment and the head posture at the previous moment; in response to the distance being greater than a preset threshold, the control module adjusts the current position of the EEG cap based on the head posture at the current moment, and the brain electrodes in the EEG cap continue to monitor the EEG data of the target user in the adjusted posture; in response to the distance being not greater than the preset threshold, the control module controls the brain electrodes in the EEG cap to continue monitoring the EEG data of the target user in the current posture.

[0197] In some embodiments, the non-contact EEG monitoring system further includes:

[0198] The control module adjusts the current position and orientation of the EEG cap based on the head posture at the current moment, including: taking the head posture of the target user at the current moment as the control target of the robotic arm; the robotic arm controls and adjusts the current position and current orientation of the EEG cap so that the EEG cap moves to a position that matches the head position and head orientation of the target user at the current moment, and the brain electrodes in the EEG cap collect EEG data of the target user at the adjusted position.

[0199] In some embodiments, the non-contact EEG monitoring system further includes:

[0200] The control module determines the head posture of the target user, comprising:

[0201] Determine a head edge point coordinate set of the target user based on the head image;

[0202] The head pose of the target user is determined based on the head edge point coordinate set.

[0203] In some embodiments, the non-contact EEG monitoring system further comprises: the size of the EEG cap is adjustable, and the position of the brain electrodes in the EEG cap is changeable. The non-contact EEG monitoring system further comprises:

[0204] The control module determines the head size of the target user based on the head image of the target user; determines the scaling factor of the EEG cap and the arrangement scaling factor of the brain electrodes in the EEG cap based on the head size of the target user;

[0205] The EEG cap adjusts the size of the EEG cap based on the scaling factor, and adjusts the coordinate position layout of the brain electrodes in the EEG cap based on the arrangement scaling factor.

[0206] In some embodiments, the non-contact EEG monitoring system further includes:

[0207] The control module determines a scaling factor of the EEG cap and a scaling factor of an arrangement of brain electrodes in the EEG cap based on the head size of the target user, including:

[0208] Determining the initial size of the EEG cap and the initial arrangement coordinates of the brain electrodes in the EEG cap;

[0209] determining a scaling factor of the EEG cap based on the head size of the target user and the initial size of the EEG cap, and adjusting the size of the EEG cap based on the scaling factor so that the size of the EEG cap matches the head size of the target user;

[0210] Based on the scaling coefficient of the EEG cap and the initial arrangement coordinates of the brain electrodes in the EEG cap, the arrangement scaling coefficient of the brain electrodes in the EEG cap is determined, and based on the arrangement scaling coefficient, the target coordinates of the brain electrodes are determined, so that the brain electrodes monitor the EEG data of the target user at the target coordinates.

[0211] In some embodiments, the non-contact EEG monitoring system further includes:

[0212] The head size of the target user includes a horizontal size and a vertical size of the head;

[0213] The step of determining the head size of the target user in the control module includes:

[0214] Determining ear key points, nose key points, and head key points of the target user based on the head image, wherein the ear key points include left ear key points and right ear key points;

[0215] Determine the lateral size of the head of the target user based on the ear key points and the head key points;

[0216] The longitudinal size of the head of the target user is determined based on the nose key points and the head key points.

[0217] In some embodiments, the non-contact EEG monitoring system further includes:

[0218] Acquire a head image of the target user based on a depth sensor;

[0219] The step of determining the shooting posture of the depth sensor includes:

[0220] Acquire a working plane image corresponding to a working plane and a plane normal vector corresponding to the working plane based on a depth sensor, wherein the working plane includes a plane corresponding to a working platform for monitoring EEG data of the target user;

[0221] The shooting position and shooting direction of the depth sensor are determined based on the on-site observation distance, the working distance of the depth sensor, and the plane normal vector.

[0222] In some embodiments, the non-contact EEG monitoring system further includes:

[0223] extracting a plurality of internal coordinate point sets from the work plane image based on a preset marking template;

[0224] The coordinate systems of the plurality of internal coordinate point sets are converted into a world coordinate system, and a plane normal vector corresponding to the working plane is determined based on the internal coordinate point sets in the world coordinate system.

[0225] The technical solution of the present application is described below with a specific embodiment. Specifically, the non-contact EEG monitoring system mainly includes an electrode support structure, a head support structure and a positioning calculation module.

[0226] The support module (module 1) has an overall support structure similar to a helmet. The electrodes are arranged within the helmet, and each electrode can move horizontally and vertically. The initial electrode positions are arranged according to the set brain electrode coordinate system. The electrode support structure as a whole also has the ability to move. The depth / image sensor is fixed to the support module and cannot be moved. The relative initial position of the sensor and the electrode is fixed. The sensor and the base of the support module are calibrated to obtain external parameters, and the sensor internal parameters are known. It can be understood that the sensor can be a depth sensor, which is a type of image acquisition device used to capture depth images.

[0227] The head calibration and support module (module 2) is separate from the bracket module. The module's edges are made of a non-deformable material, while the center is soft. Several unique shapes and colors are designed along the edges as calibration markers.

[0228] Positioning module (module three): The positioning module uses several depth / image sensors to obtain module two and the head data of the examinee, calculates its spatial posture, and feeds the calculation results back to module one to adjust the electrode position. This module performs real-time calculations.

[0229] like Figure 3 As shown, in some embodiments, the process of performing EEG monitoring based on the provided non-contact EEG monitoring system is as follows:

[0230] Step 1: The sensor performs calibration marker detection to obtain the position of the working plane in the world coordinate system: Module 2 is placed on a stable platform, and the examinee lies flat on Module 2. The RGBD sensor installed on Module 1 takes a picture of Module 2. Using a 2D edge detection / image segmentation algorithm, combined with a marker template of known shape and size, the internal point coordinates of all n markers and the corresponding depth information C_POINTS (camera_set_1, camera_set_2,…,camera_set_n) are obtained. The 3D coordinates in the camera coordinate system are converted to the world coordinate system W_POINTS (world_set_1, world _set_2,…, world_set_n) of the bracket base using external parameters.

[0231] Step 2: Obtain the initial observation pose of Module 1 and adjust the sensor's data acquisition pose: Use the coordinate information of all points in W_POINTS to perform plane fitting and obtain the plane normal vector N=[nx,ny,nz]. Set the optimal observation distance d based on the sensor's working distance and field of view. Calculate the center position of Module 2, P_c=[x_c, y_c, d_c], based on the set of marker points. Module 1's sensor capture position is P1=P_c+N*d, perpendicular to the plane of Module 2. This determines the sensor's target pose. Module 1 adjusts the sensor to this target pose to acquire head data.

[0232] Step 3 adjusts the EEG electrode position and arrangement distance in module 1, and the work is ready: the RGBD image obtained in step 2 is segmented to obtain the head edge point coordinate set and calculate the head pose; using the trained key point detection model, the coordinates of the head root point, the left preauricular concave point, and the right preauricular concave point are output. The top of the head curve is fitted using the coordinates of the left and right preauricular concave points and the coordinates of the top of the head edge point set, and the length of the curve is calculated as the horizontal dimension of the head. Next, the nasion point and the midpoint of the top of the head curve are selected, the distance between the two points along the head surface is calculated, and multiplied by 2 to obtain the longitudinal dimension of the head. Based on the head pose and the horizontal and vertical dimensions of the head, module 1 adjusts and arranges the EEG electrode position and starts EEG data acquisition. Initialize the head detection counter to 0.

[0233] Step 4 Head motion detection: Module 1 sensor collects head data and performs global head / other feature point detection such as binaural posture detection, and the detection counter is increased by 1;

[0234] Step 5 checks whether the counter is 1, if so, go to step 6, otherwise go to step 8;

[0235] Step 6 records the timestamp and posture information of this detection as the initial posture;

[0236] Step 7 waits for time interval t and enters step 4 again;

[0237] Step 8 Calculate the distance between the current pose and the previous N historical poses (Euclidean distance / similarity);

[0238] Step 9: Whether the distance exceeds the set threshold d, if yes, go to step 10, otherwise go to step 7;

[0239] Step 10 adjusts the EEG electrode posture according to the current posture, sets the detection counter to 1, sends all currently recorded posture information and time information to the EEG signal motion compensation module, and returns to step 5.

[0240] The present application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the non-contact EEG monitoring method provided in any of the above embodiments.

[0241] A computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the non-contact EEG monitoring method provided in any one of the above embodiments are implemented.

[0242] A computer program product stores a program or instruction thereon, which, when executed by a processor, implements the steps of the non-contact EEG monitoring method provided in any one of the above embodiments.

[0243] The EEG monitoring method provided in this application can calculate the similarity between the current head posture and the previous N historical postures based on the current head posture and the previous N historical head postures, so as to determine whether the EEG cap needs to be adjusted and how to adjust the posture of the EEG cap to ensure that the brain electrodes can continuously and accurately monitor the monitored brain area, thereby continuously and stably monitoring the EEG signals of the target user.

[0244] The non-contact EEG monitoring method provided in this application can be applied to neonatal EEG detection, and provides a stable positioning non-contact electrode system for neonatal EEG monitoring, which can solve the problems of acquisition position offset and signal instability when the head moves during non-contact EEG acquisition.

[0245] It can be understood that the computer device provided in this application can be a server, and its internal structure diagram can be as follows: Figure 5 As shown. The computer device includes a processor, a memory, and a network interface connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store relevant data. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, the method provided in the present application is implemented.

[0246] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0247] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the above-described method embodiments. Any reference to memory, storage, database, or other media used in the embodiments provided herein may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0248] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0249] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A non-contact EEG monitoring method, characterized in that: The method comprises: Obtain the head image of the target user at the current moment; Determining the head posture of the target user corresponding to the current moment based on the head image corresponding to the current moment; Determining the position of the EEG cap based on the head posture at the current moment and the head posture corresponding to the previous moment, including: determining the distance between the head posture at the current moment and the head posture at the previous moment; in response to the distance being greater than a preset threshold, adjusting the current position of the EEG cap based on the head posture at the current moment, and the brain electrodes in the EEG cap continue to monitor the EEG data of the target user in the adjusted position; in response to the distance being not greater than the preset threshold, the brain electrodes in the EEG cap continue to monitor the EEG data of the target user in the current position; wherein the EEG cap includes multiple brain electrodes, and the multiple brain electrodes monitor the EEG data of the target user in the posture corresponding to the EEG cap.

2. The method according to claim 1, characterized in that The adjusting the current posture of the EEG cap based on the head posture at the current moment includes: Taking the head posture of the target user at the current moment as the control target of the robotic arm; The robotic arm controls and adjusts the current position and current direction of the EEG cap so that the EEG cap moves to a posture that matches the head position and head direction of the target user at the current moment, and the brain electrodes in the EEG cap collect the EEG data of the target user at the adjusted posture.

3. The method according to claim 1, characterized in that The step of determining the head posture of the target user includes: Determine a head edge point coordinate set of the target user based on the head image; The head pose of the target user is determined based on the head edge point coordinate set.

4. The method according to claim 1, wherein The method further comprises: determining a head size of the target user based on the head image of the target user; Determining a scaling factor of the EEG cap and a scaling factor of an arrangement of brain electrodes in the EEG cap based on a head size of the target user; The size of the EEG cap is adjusted based on the scaling factor, and the coordinate position layout of the brain electrodes in the EEG cap is adjusted based on the arrangement scaling factor.

5. The method according to claim 4, characterized in that The step of determining a scaling factor of the EEG cap and a scaling factor of an arrangement of brain electrodes in the EEG cap based on the head size of the target user includes: Determining the initial size of the EEG cap and the initial arrangement coordinates of the brain electrodes in the EEG cap; determining a scaling factor of the EEG cap based on the head size of the target user and the initial size of the EEG cap, and adjusting the size of the EEG cap based on the scaling factor so that the size of the EEG cap matches the head size of the target user; Based on the scaling coefficient of the EEG cap and the initial arrangement coordinates of the brain electrodes in the EEG cap, the arrangement scaling coefficient of the brain electrodes in the EEG cap is determined, and based on the arrangement scaling coefficient, the target coordinates of the brain electrodes are determined, so that the brain electrodes monitor the EEG data of the target user at the target coordinates.

6. The method according to claim 5, characterized in that The head size of the target user includes a horizontal size and a vertical size of the head; The step of determining the head size of the target user includes: Determining ear key points, nose key points, and head key points of the target user based on the head image, wherein the ear key points include left ear key points and right ear key points; Determine the lateral size of the head of the target user based on the ear key points and the head key points; The longitudinal size of the head of the target user is determined based on the nose key points and the head key points.

7. The method according to claim 1, characterized in that The method further includes acquiring a head image of the target user based on a depth sensor; The step of determining the shooting posture of the depth sensor includes: Acquire a working plane image corresponding to a working plane and a plane normal vector corresponding to the working plane based on a depth sensor, wherein the working plane includes a plane corresponding to a working platform for monitoring EEG data of the target user; The shooting position and shooting direction of the depth sensor are determined based on the on-site observation distance, the working distance of the depth sensor, and the plane normal vector.

8. The method according to claim 7, characterized in that After obtaining the working plane image corresponding to the working plane, the method further includes: extracting a plurality of internal coordinate point sets from the work plane image based on a preset marking template; The coordinate systems of the plurality of internal coordinate point sets are converted into a world coordinate system, and a plane normal vector corresponding to the working plane is determined based on the internal coordinate point sets in the world coordinate system.

9. A non-contact EEG monitoring system, characterized in that: The system is used to implement the method according to any one of claims 1 to 8, and the system further includes: Bracket module, robotic arm module, image acquisition module, work platform module, EEG cap module and control module; The image acquisition module is mounted on the support module and is used to acquire a head image of a target user and / or to acquire an image of a work platform corresponding to the work platform module; The EEG cap module is installed at the end of a robotic arm, and the robotic arm is used to adjust the position of the EEG cap. The electrodes in the EEG cap are used to monitor the EEG data of the target user. The work platform module is used to carry the target user; The control module is used to control the robotic arm to adjust the posture of the EEG cap based on the head posture of the target user, and the brain electrodes in the EEG cap are used to monitor the EEG data of the target user.

Images