Balance ability evaluation method and device based on sensory conflict and brain network analysis

Abstract

The application relates to a balance ability evaluation method and device based on sensory conflict and brain network analysis, which uses virtual reality glasses and a rotating platform to regulate the visual direction and the body movement direction of a person to be evaluated, and constructs two test conditions of visual body movement consistency and visual body movement conflict; multi-channel electroencephalogram data, plantar pressure center data and self-motion perception data of the person to be evaluated under the test conditions are obtained; source analysis is performed on the electroencephalogram information activity, and a multivariate autoregressive model is established; information flow between each brain area related to balance regulation is quantified; and the balance control ability of the person to be evaluated is comprehensively evaluated according to the neural regulation ability, body stability and perception judgment ability of the person to be evaluated. The application is beneficial to fully mobilizing the balance system through multi-sensory conflict, starting from the neural mechanism of balance regulation, and comprehensively evaluating the balance ability of the person to be evaluated from multiple angles and in a comprehensive manner according to the neural regulation ability, body stability and perception judgment ability.

Description

TECHNICAL FIELD

[0001] The application relates to a balance ability evaluation balance method based on sensory conflict and brain network analysis, and relates to a balance comprehensive evaluation system based on a VR glasses and a rotating platform setting, which comprehensively collects brain electrical signals, COP and self-motion perception multi-modal data under a multi-sensory conflict condition. BACKGROUND

[0002] Maintaining standing balance is a complex task that requires complex interactions within and between the central nervous system, sensory system and motor system, and is the basic guarantee for human to carry out various daily activities. However, standing balance impairment is not uncommon due to pathological or aging effects, and falls are the fourth leading cause of injury death in China, and the leading cause among people over 65 years old. The evaluation of balance ability is crucial for preventing falls.

[0003] Maintaining standing balance requires the central nervous system (CNS) to integrate and coordinate the afferent information of multiple sensory systems such as vision, vestibular sense, proprioception and touch. However, because each sensory system has its own coordinate frame, specific time delay and reliability, sensory conflict may occur. Psychophysical experiments show that during multi-sensory processing, the brain needs to constantly judge the source of each modal sensory cue (causal inference), and arbitrate between sensory integration and isolation. In the case of common sources, signals should be integrated and weighted according to their relative sensory reliability. If they are independent sources, they should be processed independently. People with decreased balance ability usually cannot adapt to conflict first. Falls usually occur when sensory conflict occurs.

[0004] What is the neural substrate for multi-sensory integration and causal inference? A large number of neurophysiological studies have shown that in each of the two brain regions of the superior temporal area and the posterior parietal lobe, there are some neurons whose firing rates are linearly related to both vestibular and visual cues. And according to the trend difference, they can be divided into isomorphic neurons and opposite neurons. Isomorphic neurons are more active when the senses are consistent, and their firing curve is consistent with the model of sensory weighted integration. Opposite neurons are more active when there is a sensory conflict, and their combination with isomorphic neurons may help to judge the modal difference of the senses and help causal inference. In the superior temporal area, almost equal numbers of isomorphic neurons and opposite neurons are found, while in the posterior parietal lobe, almost all are consistent neurons. This suggests that the posterior parietal lobe may be more involved in linear weighting of homologous sensory cues, while the superior temporal gyrus is more involved in causal inference of the source of sensory cues.

[0005] Currently, the judgment of balance ability is less under sensory conflict, while the balance disorder under conflict is often the culprit of falls. Few people use the neural mechanisms of balance regulation to evaluate balance ability. SUMMARY

[0006] In order to solve the problems in the background art, the present application proposes a balance ability evaluation method and device based on sensory conflict and brain network analysis. The present application includes a balance disturbance test device and a data acquisition device. The present application relates to a test for regulating multisensory consistency using a VR glasses and a rotating platform setting; at the same time, a method for comprehensive evaluation of balance ability is provided by comprehensively analyzing multi-modal data such as electroencephalogram, COP and self-motion perception.

[0007] The specific technical solutions adopted by the present application are as follows:

[0008] In a first aspect, the present application provides a balance ability evaluation method based on sensory conflict and brain network analysis, which comprises:

[0009] S1: obtaining test data of the person to be evaluated under two test conditions, including multi-channel electroencephalogram data, foot pressure center data and self-motion perception data; in the two test conditions, in the sensory consistency test condition, the visual cues of the person to be evaluated for the rotation direction of the body are consistent with the actual body movement, and in the sensory conflict test condition, the visual cues of the person to be evaluated for the rotation direction of the body are inconsistent with the actual body movement direction;

[0010] S2, based on the foot pressure center data under the two test conditions, the time sequence change of the foot pressure center translation speed of the person to be evaluated under each test condition is calculated respectively, and the average value of the foot pressure center translation speed is taken as the representation value of body stability;

[0011] S3, based on the multi-channel electroencephalogram data obtained under the two test conditions, a first cortical functional connection network corresponding to the sensory consistency test condition and a second cortical functional connection network corresponding to the sensory conflict test condition are constructed; in each cortical functional connection network, a plurality of cortical functional regions related to balance control are included, each cortical functional region is taken as a node of the network, and the strength value of the edge connecting two nodes is the directional information interaction strength between the two cortical functional regions estimated according to the multi-channel electroencephalogram data;

[0012] S4, keeping the nodes of the cortical functional connection network unchanged, updating the strength value of any edge in the network to the change amount of the strength value of the edge in the second cortical functional connection network relative to the strength value of the edge in the first cortical functional connection network, thereby obtaining a balance adjustment network;

[0013] S5, combining the basic balance ability evaluation result and the balance adjustment ability evaluation result, obtaining the comprehensive evaluation result of the balance control ability of the person to be evaluated; wherein:

[0014] The body stability of the person to be evaluated under the sensory consistency test condition is taken as a measurement index in the basic balance ability evaluation result.

[0015] The body stability, the neural regulation index and the perceptual judgment ability of the person to be evaluated under the sensory conflict test condition are taken as measurement indexes in the balance regulation ability evaluation result; the neural regulation index is the ratio between the degree of the superior temporal cortex and the degree of the posterior parietal cortex in the balance regulation network; the perceptual judgment ability is the perceptual grading score of the person to be evaluated for the movement direction under the sensory conflict test condition according to the self-motion perceptual data.

[0016] As a preferred embodiment of the first aspect, for the multi-channel electroencephalogram data under each test condition, the method for constructing the cortical functional connection network is as follows:

[0017] First, for the multi-channel electroencephalogram data, a low-resolution tomography (LORATE) method is applied for source analysis to obtain the potential activity data of the cortex; then, based on the cortical functional partition map in the brain, the potential activity data of the cortex is grouped according to the cortical functional regions related to balance control; finally, based on the grouped data, a directed transfer function (PDC) is used to estimate the directed information interaction strength between each cortical functional region, so as to construct the cortical functional connection network of the person to be evaluated during the test, with all the cortical functional regions related to balance control as nodes and the directed information interaction strength as the strength value of the edges between the nodes.

[0018] As a preferred embodiment of the first aspect, in the balance regulation network, the strength value edge trans of the edge e between any two nodes is calculated as follows:

[0019]

[0020] In the formula, edge represents the corresponding strength value of the edge e in the second cortical functional connection network, and edge represents the corresponding strength value of the edge e in the first cortical functional connection network.

[0021] As a preferred embodiment of the first aspect, the neural regulation index Nero adj is calculated as follows:

[0022] Nero adj =

[0023] In the formula, degree represents the degree of the node A corresponding to the superior temporal cortex in the balance regulation network, which is the sum of the strength values of all the edges connected to the node A; The degree of the node B corresponding to the posterior parietal cortex in the balance regulation network is the sum of the strength values of all edges connected to the node B.

[0024] As a preferred embodiment of the first aspect, the perceptual judgment ability is divided into three grades according to the answers of the person to be evaluated under the sensory conflict test condition, the third grade is that the person to be evaluated can correctly judge the movement direction and perceive that the visual cue and the body movement are in conflict; the second grade is that the person to be evaluated can correctly judge the movement direction but cannot perceive that the visual cue and the body movement are in conflict; and the first grade is that the person to be evaluated cannot correctly judge the movement direction; and the perceptual grading scores corresponding to the third grade, the second grade and the first grade monotonically decrease or increase.

[0025] As a preferred embodiment of the first aspect, the multi-channel electroencephalogram data and the plantar pressure center data need to be denoised and cleaned.

[0026] As a preferred embodiment of the first aspect, the several cortical functional regions related to balance control in the cortical functional connection network include seven regions, namely, the dorsolateral prefrontal cortex, the frontal eye field cortex, the motor cortex, the primary somatosensory cortex, the posterior parietal cortex, the superior temporal cortex and the visual cortex.

[0027] In a second aspect, the application provides a balance ability evaluation device based on sensory conflict and brain network analysis, which includes a balance interference device, a data acquisition device and a data evaluation device.

[0028] The balance interference device includes virtual reality glasses and a rotating platform; the rotating platform is used for standing and driving the person to be evaluated to rotate counterclockwise and clockwise around the vertical axis of the human body; the virtual reality glasses are used for being worn on the eyes of the person to be evaluated and displaying virtual reality visual scenes of counterclockwise and clockwise rotation to the person to be evaluated; two different test conditions are created for the person to be evaluated by cooperation of the virtual reality glasses and the rotating platform in one test period, in the sensory consistent test condition, the visual cue of the person to be evaluated for the rotation direction of the person to be evaluated is consistent with the actual body movement, and in the sensory conflict test condition, the visual cue of the person to be evaluated for the rotation direction of the person to be evaluated is inconsistent with the actual body movement direction.

[0029] The data acquisition device is used for acquiring multi-channel electroencephalogram data, plantar pressure center data and self-motion perception data under the two test conditions.

[0030] The data evaluation device is used for obtaining the comprehensive evaluation result of the balance control ability of the person to be evaluated according to the balance ability evaluation method of any one of the preceding first aspect.

[0031] As the preferred of the second aspect, the balance interference device, the virtual reality glasses simulate the real test room environment through the three-dimensional simulation software, and the horizontally arranged rotating platform can rotate counterclockwise and clockwise at a constant speed according to the set speed; when the sensory consistency test condition is executed, the rotating platform drives the to-be-evaluated person to rotate clockwise around the vertical axis continuously, and the virtual reality glasses display the virtual reality visual scene rotating counterclockwise to the to-be-evaluated person, so that the visual clues perceived by the to-be-evaluated person are consistent with the body movement; when the sensory conflict test condition is executed, the rotating platform drives the to-be-evaluated person to rotate clockwise around the vertical axis continuously, and the virtual reality glasses display the virtual reality visual scene rotating clockwise to the to-be-evaluated person, so that the visual clues perceived by the to-be-evaluated person are opposite to the body movement.

[0032] As the preferred of the second aspect, two rounds of tests are included in one test cycle, each round of test includes a baseline period, an interference period and a recovery period, and one test condition is applied in the interference period of each round of test, and the virtual reality glasses and the rotating platform are kept inoperable in the baseline period and the recovery period.

[0033] Compared with the prior art, the balance ability evaluation method and device based on sensory conflict and brain network analysis have the following beneficial effects:

[0034] The balance ability evaluation method and device based on sensory conflict and brain network analysis can fully mobilize the balance system through multi-sensory conflict, and evaluate the balance ability of the to-be-evaluated person from the neural mechanism of balance regulation, and comprehensively evaluate the balance ability of the to-be-evaluated person from the neural regulation ability, the body stability and the perceptual judgment ability. BRIEF DESCRIPTION OF DRAWINGS

[0035] Figure 1 It is a schematic diagram of the device of the application.

[0036] Wherein 1 is an EEG cap for collecting EEG, 2 is a virtual reality glasses, 3 is a Wii balance board, and 4 is a rotating platform with controllable speed and acceleration.

[0037] Figure 2 It is a timing diagram of the balance test.

[0038] Figure 3 Tendency of the sway speed of the young group.

[0039] Figure 4 Tendency of the sway speed of the old group.

[0040] Figure 5 Cortical functional connectivity of the young group.

[0041] Figure 6 Cortical functional connectivity of the old group. DETAILED DESCRIPTION

[0042] In order to make the above objectives, characteristics and advantages of the present application more apparent, concrete embodiments of the present application will be described in detail below with reference to the accompanying drawings. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present application. However, the present application can be practiced in a variety of ways other than those described herein without departing from the spirit of the present application, and those skilled in the art can make similar improvements without departing from the spirit of the present application. Therefore, the present application is not limited to the specific embodiments disclosed below. The technical features in each of the embodiments of the present application can be combined with each other without conflict, and the corresponding combinations are possible.

[0043] In a preferred embodiment of the present application, a balance ability evaluation device based on sensory conflict and brain network analysis is provided, which comprises a balance interference device, a data acquisition device and a data evaluation device.

[0044] The balance disturbance test device sets two balance interference test conditions by a rotating platform and a virtual reality (VR) glasses. The rotating platform is used for the standing of the to-be-evaluated personnel and drives the to-be-evaluated personnel to rotate counterclockwise and clockwise around the vertical axis of the human body; and the virtual reality glasses are used for wearing on the eyes of the to-be-evaluated personnel and displaying virtual reality visual scenes of counterclockwise and clockwise rotation to the to-be-evaluated personnel. In a test period, the to-be-evaluated personnel is created two different test conditions by the cooperation of the virtual reality glasses and the rotating platform. In the sensory consistent test condition, the visual clues of the to-be-evaluated personnel for the rotation direction of the self are consistent with the actual body movement, and in the sensory conflict test condition, the visual clues of the to-be-evaluated personnel for the rotation direction of the self are inconsistent with the actual body movement direction.

[0045] As a preferred implementation manner of the embodiment of the present application, the virtual visual scene can be presented by the VIVE Pro Eye virtual reality glasses produced by HTC Company. The virtual visual scene used is an environment simulating a real test device room written by a Unity3D program. The rotating platform can be a customized multi-degree-of-freedom rotating platform, which can realize counterclockwise rotation and clockwise rotation, and the maximum rotation speed is 96 degrees per second. In addition, the Unity3D program written can be used to control the activities of the rotating platform and the visual scene in the virtual reality glasses at the same time, and the consistency of the visual scene and the platform rotation is changed by setting the rotation direction and rotation speed of the rotating platform and the visual scene respectively, wherein a total of two test conditions of sensory consistency and sensory conflict are set. Specifically, the sensory consistency test condition refers to that the visual scene is counterclockwise rotation under the condition of continuous counterclockwise rotation of the rotating platform, and the visual scene is clockwise rotation under the condition of continuous clockwise rotation of the rotating platform, which is consistent with the actual visual perception when the human body rotates under normal circumstances; the visual scene is counterclockwise rotation under the condition of continuous counterclockwise rotation of the rotating platform, and the visual scene is clockwise rotation under the condition of continuous clockwise rotation of the rotating platform, which is contrary to the actual visual perception when the human body rotates under normal circumstances.

[0046] In addition, the data acquisition device is used to acquire multi-channel electroencephalogram data, center of pressure (COP) data, and self-motion perception data under the two test conditions.

[0047] As a preferred implementation manner of the embodiment of the present application, the Wii balance board can be placed in the middle of the rotating platform, and the center of pressure of the foot of the person to be evaluated under the two test conditions is measured to obtain the time sequence data of the COP. The multi-channel electroencephalogram data is acquired by the ANTNeuro electroencephalogram device, including 32 electroencephalogram channels under the international 10-20 system. The self-motion perception data can be obtained by inquiring the subjective perception of the person to be evaluated on the motion, specifically, the person to be evaluated can be required to report the self-motion direction perceived after the balance test, and whether the person to be evaluated perceives the conflict between the visual clues and the body motion direction. Of course, an input module for the person to be evaluated to input the above information can also be separately set, which can be a touch screen input module with a UI interface or other key input module.

[0048] The data evaluation device is used to obtain the comprehensive evaluation result of the balance control ability of the person to be evaluated based on the test data acquired by the foregoing data acquisition device according to a balance ability evaluation method.

[0049] It should be noted that the hardware carrier of the data evaluation device can be a computing unit with computing capability, can be a physical machine such as a PC, a microcomputer, a single-chip microcomputer, or can be a cloud server for realizing calculation in the cloud. The specific balance ability evaluation method can be loaded on the physical machine or the cloud server in the form of a program module, used for processing the test data collected by the data collection device, and finally outputting the balance control ability comprehensive evaluation result of the person to be evaluated. At the same time, for the physical machine, the balance control ability comprehensive evaluation result of the person to be evaluated finally output can be externally displayed in the form of a paper printout or through a UI interface display, and for the cloud server, the balance control ability comprehensive evaluation result of the person to be evaluated finally output can be displayed through a web page or a message push.

[0050] The balance ability evaluation method for obtaining the balance control ability comprehensive evaluation result of the person to be evaluated in the above data evaluation device is described in detail below.

[0051] As a preferred implementation manner of an embodiment of the present application, a balance ability evaluation method based on sensory conflict and brain network analysis is provided, which comprises the following steps:

[0052] Step 1, testing the person to be evaluated and collecting data:

[0053] At the beginning of the test, the person to be evaluated is required to stand in the center of the rotating platform with a Wii balance board, hold his / her hands to his / her chest, and try to maintain balance. One test cycle includes two test tasks, each of which is divided into a baseline period, a disturbance period, and a recovery period, wherein the baseline period is set to 30s, the disturbance period is set to 36s, and the recovery period is set to 1 minute. The test condition is applied in the disturbance period, and the virtual reality glasses and the rotating platform are matched to present the two test conditions of sensory consistent test condition and sensory conflict test condition in random order. In the sensory consistent test condition, the visual cues of the person to be evaluated for the rotation direction of his / her own body are consistent with the actual body movement, and in the sensory conflict test condition, the visual cues of the person to be evaluated for the rotation direction of his / her own body are inconsistent with the actual body movement. Only one of the two test conditions is applied in the disturbance period of each test, and the virtual reality glasses and the rotating platform remain inactive in the baseline period and the recovery period of the two tests. In order to ensure the accuracy of the test, a 5-minute rest is provided during the two test tasks. The VR visual scene provided by the virtual reality glasses and the rotation speed of the rotating platform can be set to 40 degrees per second.

[0054] During the whole test period, the multi-modal data of the person to be evaluated are continuously collected in real time, including multi-channel electroencephalogram data, COP data, and self-motion perception data. The multi-channel electroencephalogram data and the COP data are directly collected by an electroencephalogram device and a Wii balance board respectively, and the self-motion perception data are obtained by inquiring and recording after the person to be evaluated completes the test, including the perceived self-motion direction, and whether the person perceives a conflict between the visual cues and the body motion direction.

[0055] Step 2: The collected multi-channel electroencephalogram data and COP data need to be preprocessed for data denoising and cleaning, and the preprocessing method is as follows:

[0056] For the COP data, a 4th order Butterworth filter is used for 20 Hz low-pass filtering, and a second difference reduction is used to remove the baseline; for the high-density multi-channel electroencephalogram EEG data, interference needs to be removed through band-pass filtering, re-reference, independent component analysis, and artifact spatial reconstruction. Then, the processed COP data and multi-channel electroencephalogram data are divided into baseline period, interference period, and recovery period according to the start and end points of the platform rotation, and the interference period data are extracted for subsequent calculation, thereby completing the preprocessing.

[0057] Step 3: Calculate the sway velocity based on the preprocessed COP data and multi-channel electroencephalogram data, and construct a cortical functional connection network.

[0058] The sway velocity is calculated by dividing the change trajectory of the foot pressure center by time, and since the sway velocity is constantly changing during the test, the change of the sway velocity in the time domain needs to be calculated. Specifically, the entire COP data can be segmented by a fixed sliding window, and the foot pressure center translation velocity, i.e. the sway velocity, is calculated based on the data points in each sliding window. The specific calculation formula is as follows:

[0059] MV

[0060] In the formula: represents the time length of the sliding window, and respectively represent the coordinates of the adjacent two foot pressure centers, and n represents the number of data points in the sliding window.

[0061] The body stability can be evaluated by using the size of the sway velocity. Specifically, for the COP data in the interference period under two test conditions, the time sequence change of the foot pressure center translation velocity of the person to be evaluated under each test condition can be calculated, and the average value of the foot pressure center translation velocity in the interference period is taken as the representation value of the body stability under the corresponding test condition.

[0062] The method for constructing the cortical functional connectivity network belongs to the existing technology and can be implemented by any feasible existing technology. As a preferred implementation of the embodiment of the present invention, the method for constructing the cortical functional connectivity network is as follows:

[0063] First, the low-resolution tomography (LORATE) method is applied to perform source analysis on multi-channel EEG data to obtain cortical electrical potential activity data, namely source-space EEG data, to solve the field diffusion and volume leads of sensor-space EEG.

[0064] Then, for the source-space EEG data, a cortical functional partitioning map was established based on the Brodmann brain region partitioning method. Based on the cortical functional partitioning map in the brain, the cortical electrical activity data was grouped according to the cortical functional regions related to balance control. The grouping method was implemented using k-means clustering. Specifically, in this embodiment, the cortical functional regions related to balance control were divided into seven: the dorsolateral prefrontal cortex (DL-PFC; BA10, 46, 47), the frontal eye field cortex (FEF; BA8, 9), the motor cortex (MC; BA4, 6), the primary somatosensory cortex (S1; BA1, 2, 3), the posterior parietal cortex (PPC; BA5, 7), the superior temporal cortex (STC; BA22, 40), and the visual cortex (VC; BA17, 18, 19).

[0065] Finally, based on the grouped data, the directional transfer function (PDC) was used to estimate the directional information interaction strength between each cortical functional area, so as to construct the cortical functional connection network edge of the evaluated person during the test, with all cortical functional areas related to balance control as nodes and the directional information interaction strength as the strength value of the edge between nodes.

[0066] Each of the two test conditions described above requires the construction of a cortical functional connectivity network. For ease of description, the cortical functional connectivity network corresponding to the sensory consistency test condition is referred to as the first cortical functional connectivity network, and the cortical functional connectivity network corresponding to the sensory conflict test condition is referred to as the second cortical functional connectivity network. Each cortical functional connectivity network thus includes seven cortical functional areas related to balance control. Each cortical functional area serves as a node in the network, and the strength of the edge connecting two nodes is the strength of the directional information interaction between the two cortical functional areas, estimated based on the multi-channel EEG data under the corresponding test conditions.

[0067] Step 4: Comprehensively analyze the shaking speed, balance regulation brain network, and self-motion perception to comprehensively evaluate the balance control ability of the person being evaluated. At this stage, the present invention evaluates the balance ability of the person being evaluated from two perspectives: basic balance ability and balance regulation ability.

[0068] 4.1) Basic balance ability evaluation result

[0069] In the basic balance ability evaluation result, the body stability of the person to be evaluated under the sensory consistent test condition is taken as a measurement index of the basic balance ability.

[0070] 4.2) Balance adjustment ability evaluation result

[0071] The balance adjustment ability is measured from three angles of the body stability under conflict, the neural regulation index, and the perceptual judgment ability of the person to be evaluated, so in the balance adjustment ability evaluation result, the body stability under the sensory conflict test condition, the neural regulation index, and the perceptual judgment ability of the person to be evaluated are taken as measurement indexes.

[0072] The body stability under the sensory conflict test condition can also be represented by the average value of the foot bottom pressure center translation speed in the interference period calculated based on the COP data under the sensory conflict test condition in step 3.

[0073] The neural regulation index is used to measure the cortical functional connection regulation ability of the person to be evaluated in response to conflict. Specifically, first, the intensity change of the brain network connection under the conflict test condition relative to the consistent test is needed to form a balance adjustment brain network. The above balance adjustment brain network is obtained based on the second cortical functional connection network and the first cortical functional connection network. Since the cortical functional regions related to balance control in the second cortical functional connection network and the first cortical functional connection network are the same, the nodes and connection edges of the two networks are also the same. When calculating the balance adjustment brain network, the nodes of the cortical functional connection network are still kept unchanged, and only the intensity value of the edge needs to be updated. The intensity value of any edge in the balance adjustment brain network should be updated to the change amount of the intensity value of the edge in the second cortical functional connection network relative to the intensity value of the edge in the first cortical functional connection network, and the change amount can be calculated by the ratio of the intensity values. For any edge e between two nodes in the balance adjustment network, the calculation formula of the intensity value edge trans can be seen as follows:

[0074]

[0075] In the formula: represents the corresponding intensity value of edge e in the second cortical functional connection network, represents the corresponding intensity value of edge e in the first cortical functional connection network.

[0076] When the balance regulation network is obtained, the degrees of the upper temporal lobe cortex and the posterior parietal cortex corresponding nodes in the balance regulation brain network can be calculated. Since each edge has a strength value, the degree of a node is the sum of the strength values of all edges connected to the node. Tests show that the posterior parietal cortex is the center of multisensory weighted integration, and the upper temporal lobe cortex is the center of multisensory source analysis. During conflict, the relative optimal sensory processing with sensory consistency is to strengthen causal inference and weaken direct integration. Accordingly, the neural regulation index is defined as the ratio between the degree of the upper temporal lobe cortex and the degree of the posterior parietal cortex in the balance regulation network, and the calculation formula is:

[0077] Nero adj =

[0078] In the formula: represents the degree of the node A corresponding to the upper temporal lobe cortex in the balance regulation network, and is the sum of the strength values of all edges connected to the node A; represents the degree of the node B corresponding to the posterior parietal cortex in the balance regulation network, and is the sum of the strength values of all edges connected to the node B.

[0079] The perceptual judgment ability is used to represent the perception ability of the to-be-evaluated person for the direction of self-rotation motion in the test process. The perceptual judgment ability can be a perceptual classification score of the to-be-evaluated person for the direction of motion under the condition of sensory conflict test determined according to the self-motion perception data. Specifically, the to-be-evaluated person can be divided into three perceptual classifications according to the recorded self-motion perception data after the conflict test adjustment: the third classification: can correctly judge the direction of motion, and perceive that the visual information and the body motion are in conflict; the second classification: can correctly judge the direction of motion, but cannot perceive that the visual information and the body motion are in conflict; and the first classification: cannot correctly judge the direction of self-motion. As a preferred implementation manner of the embodiment of the present application, the perceptual classification scores corresponding to the third classification, the second classification and the first classification can be monotonically decreasing or increasing, so as to directly reflect the perceptual judgment ability of the to-be-evaluated person through the score.

[0080] Thus, combined with the basic balance ability evaluation result and the balance adjustment ability evaluation result, the balance control ability comprehensive evaluation result of the person to be evaluated can be obtained, the balance control ability comprehensive evaluation result contains one index (body stability under the sensory consistent test condition, i.e., the average sway speed under the sensory consistent test condition) representing the basic balance ability and three indexes (the body stability under the sensory conflict, i.e., the average sway speed, the neural regulation index, and the perceptual judgment ability) representing the conflict adaptation ability. Among the four indexes, the greater the sway speed, the worse the body stability; the greater the neural regulation index, the stronger the conflict coping ability; the perceptual judgment ability value is positively or negatively correlated with the perceptual judgment ability (specifically, the perceptual judgment ability: the third grade > the second grade > the first grade, depending on the assignment of the score value).

[0081] Therefore, for any person to be evaluated, the balance control ability comprehensive evaluation result thereof can be obtained through the above-mentioned balance ability evaluation device and method based on the sensory conflict and brain network analysis of the present application. The balance ability evaluation device and method can be used for non-diagnostic purposes, such as scientific research, high balance ability population screening, etc., and can also be used for auxiliary diagnostic purposes, such as obtaining the balance ability evaluation result of the subject. However, it should be noted that even if the device and method are used for auxiliary diagnostic purposes, the result cannot directly reflect the disease, but only serves as an intermediate result.

[0082] In order to further demonstrate the technical effects that can be achieved by the balance ability evaluation device and method based on the sensory conflict and brain network analysis in the above-mentioned embodiments of the present application, the following will specifically combine it into a specific application example, so as to facilitate the technical personnel in the art to understand its specific implementation and advantages.

[0083] Embodiment

[0084] This embodiment is implemented on the premise of the technical solutions given in the above-mentioned embodiments of the present application (i.e., the aforementioned balance ability evaluation device based on the sensory conflict and brain network analysis and the balance ability evaluation method of steps 1-4), and part of the technical solutions will not be repeated, and the detailed operation process and data results are mainly given.

[0085] The subject personnel in this embodiment are as follows:

[0086] The young group and the old group are selected as two groups of controls with different balance abilities. The subjects are in good physical health, have no nerve damage and other chronic diseases, have not engaged in strenuous exercise within 24 hours before the experiment, and have no muscle fatigue phenomenon. Before the experiment, the height, weight, and dominant side of all subjects were measured. All subjects agreed to participate in the experiment voluntarily and signed the informed consent form. The specific characteristics are as follows: 22 young people, aged 23±2.3, 11 men and 11 women. 22 people in the old group, aged 65±3, 11 men and 11 women.

[0087] The balance ability evaluation test procedure of the embodiment is as follows:

[0088] The subject is asked to stand on the Wii balance board 3 placed in the middle of the rotating platform 4 with controllable speed and acceleration, and is required to stand quietly with his hands on his chest and maintain balance, as shown in Figure 1 The subject is reminded to judge the direction of his own movement during the test. Next, the rotating platform and VR glasses are used to give the subject two test conditions of visual-body movement consistency and visual-body movement conflict in random order. The specific timing is shown in Figure 2 Each test period includes two rounds of testing, each round of testing including a 30s baseline period, a 36s interference period and a one-minute recovery period; the two rounds of testing are separated by 5 minutes. At the end of each round of testing, the subject is asked to perceive the direction of his own movement, and whether he feels a conflict between visual and body movement. The sampling rate of COP is 100HZ, and the sampling rate of EEG is 1000HZ.

[0089] Calculation of balance ability related features:

[0090] During the balance test in the previous step, the COP data and multi-channel EEG activity of the subject under the two test conditions are obtained. First, the COP data is low-pass filtered at 20Hz, and then the mean value is removed; the COP data is segmented using a 15s window length and 1s step sliding window, and the sway speed of each segment is calculated. The sway speed is the change trajectory length of the foot pressure center divided by the time, and the specific formula is as described above. The sway speed of the young group and the elderly over time is shown in Figure 3 and Figure 4 It can be seen that the body stability of the elderly under the two test conditions decreases. But it is particularly obvious under the conflict condition. It is possible that the basic balance ability of the elderly is still largely retained, but the sensory processing ability under conflict decreases significantly. Therefore, the sway speed data of the interference period under each test condition after the above preprocessing is extracted, and the sway speed mean value is calculated, which is used as the body stability representation under the two test conditions.

[0091] For multi-channel EEG signals, first use a 1-50hz window to band-pass filter the EEG signals, and interpolate channels with abnormally high standard deviation (standard deviation > 7) or no correlation with all other channels (Pearson correlation coefficient < 40%). Then, the EEG data is re-referenced according to the common reference. Then, independent component analysis (ICA) is used to remove eye movement, ECG and other non-homologous signal interference in the EEG signal. Finally, wavelet filtering and second difference reduction are used to further clean up the baseline drift and high valued interference.

[0092] For each multi-channel EEG data after the above preprocessing under each test condition, the data of the interference period is extracted, and the cortical functional connection network is constructed according to the following process respectively:

[0093] The EEG source analysis is performed by resolution tomography (LORETA) to obtain the source space EEG data to solve the field diffusion and volume lead of the sensor space EEG. For the source space EEG data, according to the Brodmann brain region division method, the k-means clustering is used to group into each balanced function related brain area. In this embodiment, a total of 7 function groups related to balance are set, which are 7 cortical regions such as dorsolateral prefrontal cortex (DL-PFC; BA10, 46, 47), frontal eye field (FEF; BA8, 9), motor cortex (MC; BA4, 6), primary somatosensory cortex (S1; BA1, 2, 3), posterior parietal cortex (PPC; BA5, 7), superior temporal cortex (STC; BA22, 40) and visual cortex (VC; BA17, 18, 19), each of which is a node of the network. All channels in the source space EEG data are grouped according to the 7 categories for subsequent information interaction estimation. Finally, the directed transfer function (PDC) is used to estimate the directed information interaction between the cortical functional regions in each frequency band to construct the cortical functional connection network edge of the to-be-evaluated person during the test.

[0094] In this embodiment, the significance analysis is performed on the changes of the cortical functional connection network under the sensory conflict test condition compared with the cortical functional connection network under the sensory consistent test condition. It can be found that the young people have significantly enhanced functional connection centered on the temporal lobe under conflict, and the information out of the parietal lobe is significantly weakened, as shown in Figure 4 . The elderly have less connection changes in the posterior parietal cortex and the superior temporal cortex, which are the multi-sensory processing regions, as shown in Figure 5 . Accordingly, the intensity change of the brain network connection under the conflict test condition relative to the consistent test is calculated, which is used as the edge intensity value in the balance regulation brain network, and the calculation formula of the edge is referred to in the foregoing. trans Finally, the degree of the superior temporal cortex and the posterior parietal cortex in the balance regulation brain network is calculated, and the ratio of the degrees of the superior temporal cortex and the posterior parietal cortex is defined as the neuroregulation index Nero adj .

[0095] Finally, the perceptual judgment ability is divided into 3 grades according to the answers of the to-be-evaluated person after the conflict test regulation. III: can correctly judge the motion direction, and perceive that the visual information and the body movement are in conflict. II: can correctly judge the motion direction, but cannot perceive that the visual information and the body movement are in conflict. I: cannot correctly judge the motion direction.

[0096] The comprehensive evaluation of the balance ability is as follows:

[0097] The balance ability of the young group and the old group is comprehensively evaluated by the sway speed, the neuromodulation and the self-motion perception. The comprehensive evaluation result of the balance control ability contains one index representing the basic balance ability (the body stability under the sensory consistent test condition, i.e. the sway speed average under the sensory consistent test condition) and three indexes representing the conflict adaptation ability (the body stability under the sensory conflict, i.e. the sway speed average, the neuromodulation index and the perception judgment ability). The perception judgment ability I, II and III are set as the score values 1, 2 and 3 respectively. The closer the average perception judgment ability value of the young group and the old group is to 3, the stronger the perception judgment ability is. The greater the sway speed is, the worse the body stability is, and the greater the neuromodulation index is, the stronger the conflict coping ability is.

[0098] The specific evaluation results of the young group and the old group in the embodiment are as follows:

[0099]

[0100] The above-described embodiment is only a preferred scheme of the present application, and is not intended to limit the present application. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present application. Therefore, any technical scheme obtained by equivalent replacement or equivalent transformation falls within the protection scope of the present application.

Claims

1. A balance ability assessment method based on sensory conflict and brain network analysis, characterized in that: include: S1: Acquire test data of the subject under two test conditions, including multi-channel EEG data, plantar pressure center data, and self-motion perception data; in the two test conditions, in the sensory consistency test condition, the subject's visual cues for their own rotation direction are consistent with their actual body movement, and in the sensory conflict test condition, the subject's visual cues for their own rotation direction are inconsistent with their actual body movement direction; S2. Based on the plantar pressure center data under the two test conditions, calculate the time series changes in the plantar pressure center translation velocity of the person to be evaluated under each test condition, and use the average plantar pressure center translation velocity as the representative value of body stability; S3. Based on the multi-channel EEG data obtained under the two test conditions, respectively, construct a first cortical functional connection network corresponding to the sensory consistency test condition and a second cortical functional connection network corresponding to the sensory conflict test condition; each cortical functional connection network includes several cortical functional areas related to balance control, each cortical functional area serves as a node of the network, and the strength value of the edge connecting two nodes is the directional information interaction strength between the two cortical functional areas estimated based on the multi-channel EEG data; S4, keeping the nodes of the cortical functional connectivity network unchanged, updating the strength value of any edge in the network to the change in the strength value of the edge in the second cortical functional connectivity network relative to the strength value of the edge in the first cortical functional connectivity network, thereby obtaining a balanced regulatory network; S5. Combine the basic balance ability assessment results and the balance regulation ability assessment results to obtain a comprehensive assessment result of the balance control ability of the person to be assessed; where: In the basic balance ability assessment results, the body stability of the person to be assessed under sensory consistency test conditions is used as a measurement indicator; In the balance regulation ability assessment results, the body stability, neuroregulation index and perceptual judgment ability of the person to be assessed under sensory conflict test conditions are used as measurement indicators; the neuroregulation index is the ratio between the degree of the superior temporal cortex and the degree of the posterior parietal cortex in the balance regulation network; the perceptual judgment ability is the perceptual grading score of the person to be assessed for the direction of movement under sensory conflict test conditions determined based on the self-motion perception data.

2. The balance ability assessment method based on sensory conflict and brain network analysis according to claim 1, characterized in that: For the multi-channel EEG data under each test condition, the method for constructing the cortical functional connectivity network is as follows: First, the low-resolution tomography (LORATE) method was applied to the multi-channel EEG data for source analysis to obtain the cortical electrical activity data. Then, based on the cortical functional zonation map in the brain, the cortical electrical activity data were grouped according to the cortical functional areas related to balance control. Finally, based on the grouped data, the directional transfer function (PDC) was used to estimate the directional information interaction strength between each cortical functional area. In this way, the cortical functional connection network of the person to be evaluated during the test was constructed, with all the cortical functional areas related to balance control as nodes and the directional information interaction strength as the strength value of the edges between nodes.

3. The balance ability assessment method based on sensory conflict and brain network analysis according to claim 1, characterized in that: In the balance regulation network, the strength value of the edge e between any two nodes is edge trans The calculation formula is: In the formula: edge ic Represents the strength value of edge e in the second cortical functional connection network, edge c Represents the strength value corresponding to edge e in the first cortical functional connection network.

4. The balance ability assessment method based on sensory conflict and brain network analysis according to claim 1, characterized in that: The neuromodulation index Nero adj The calculation formula is: In the formula: degeer t represents the degree of node A corresponding to the superior temporal cortex in the balance regulation network, taking the sum of the strength values ​​of all edges connecting node A; p The degree of node B corresponding to the posterior parietal cortex in the balance regulation network is the sum of the strength values ​​of all edges connecting node B.

5. The balance ability assessment method based on sensory conflict and brain network analysis according to claim 1, characterized in that: The perceptual judgment ability is divided into three levels according to the answers of the person to be evaluated under the sensory conflict test conditions. The third level is that the person can correctly judge the direction of movement and perceive that the visual cues and body movement are in conflict; the second level is that the person can correctly judge the direction of movement but cannot perceive that the visual cues and body movement are in conflict; the first level is that the person cannot correctly judge the direction of his or her own movement; and the perceptual grading scores corresponding to the third level, the second level, and the first level are monotonically decreasing or increasing.

6. The balance ability assessment method based on sensory conflict and brain network analysis according to claim 1, characterized in that: The multi-channel EEG data and plantar pressure center data need to be denoised and cleaned.

7. The balance ability assessment method based on sensory conflict and brain network analysis according to claim 1, characterized in that: In the cortical functional connection network, there are seven cortical functional areas related to balance control, namely the dorsolateral prefrontal cortex, frontal eye field cortex, motor cortex, primary somatosensory cortex, posterior parietal cortex, superior temporal cortex and visual cortex.

8. A balance ability assessment device based on sensory conflict and brain network analysis, characterized in that: It includes a balance interference device, a data acquisition device and a data evaluation device; The balance interference device includes virtual reality glasses and a rotating platform; the rotating platform is used for the person to be evaluated to stand and drive the person to be evaluated to rotate counterclockwise and clockwise around the vertical axis of the human body; the virtual reality glasses are used to be worn on the eyes of the person to be evaluated and display virtual reality visual scenes rotating counterclockwise and clockwise to the person to be evaluated; within a test cycle, two different test conditions are created for the person to be evaluated through the cooperation of the virtual reality glasses and the rotating platform: in the sensory consistency test condition, the visual clues of the person to be evaluated about the direction of his or her own rotation are consistent with the actual body movement; in the sensory conflict test condition, the visual clues of the person to be evaluated about the direction of his or her own rotation are inconsistent with the actual body movement direction; The data acquisition device is used to collect multi-channel EEG data, plantar pressure center data, and self-motion perception data under two test conditions; The data evaluation device is used to obtain a comprehensive evaluation result of the balance control ability of the person to be evaluated according to the balance ability evaluation method according to any one of claims 1 to 7.

9. The balance ability assessment device based on sensory conflict and brain network analysis according to claim 8, characterized in that: In the balance interference device, the virtual reality glasses simulate a real test room environment through three-dimensional simulation software, and the horizontally arranged rotating platform can achieve counterclockwise and clockwise rotation at a set speed. When performing the sensory consistency test condition, the rotating platform drives the person to be evaluated to continuously rotate clockwise around the vertical axis, and the virtual reality glasses simultaneously display a counterclockwise rotating virtual reality visual scene to the person to be evaluated, so that the visual cues perceived by the person to be evaluated are consistent with the body movement. When performing the sensory conflict test condition, the rotating platform drives the person to be evaluated to continuously rotate clockwise around the vertical axis, and the virtual reality glasses simultaneously display a clockwise rotating virtual reality visual scene to the person to be evaluated, so that the visual cues perceived by the person to be evaluated are opposite to the body movement.

10. The balance ability assessment device based on sensory conflict and brain network analysis according to claim 8, characterized in that: One test cycle includes two rounds of testing. Each round of testing includes three stages: baseline period, interference period, and recovery period. A test condition is applied during the interference period of each round of testing. The virtual reality glasses and rotating platform are kept inoperative during the baseline period and recovery period.

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