Textile quality evaluation system based on electroencephalogram

Abstract

The invention provides a textile fabric quality evaluation system based on electroencephalogram, and the system comprises a textile fabric tactile stimulation device which is used for installing a textile fabric sample, and is used for controlling the installed textile fabric sample to slide under the condition of starting; the electroencephalogram signal acquisition equipment is used for recording electroencephalogram data of each region of the brain of the testee when the textile fabric sample slides at the skin contact part of the testee; and the computer equipment is connected with the textile fabric tactile stimulation device and the electroencephalogram signal acquisition equipment, and is used for controlling the textile fabric tactile stimulation device to start or stop and analyzing the electroencephalogram data sent by the electroencephalogram signal acquisition equipment to obtain a quality evaluation result of the textile fabric sample. According to the application, automatic control of textile sample sliding, electroencephalogram data acquisition and electroencephalogram data analysis can be realized at the same time, and the electroencephalogram technology can be effectively applied to textile quality evaluation.

Description

Technical Field

[0001] This application belongs to the technical field of textile quality evaluation, and particularly relates to a textile quality evaluation system based on electroencephalogram (EEG). Background Art

[0002] Textile affective tactile experience is used to comprehensively evaluate the tactile feeling and emotional response of textiles. At present, the evaluation of textile affective tactile experience mainly relies on subjective evaluation, lacking objective quantitative indicators and being difficult to meet the needs of accurate and efficient quality assessment. EEG technology can objectively quantify people's touch feelings by analyzing brain nerve electrical activities, providing a new direction for textile quality evaluation. However, how to effectively apply EEG technology to textile quality evaluation efficiently is a problem to be solved. Summary of the Invention

[0003] In view of the above-mentioned disadvantages of the prior art, the purpose of this application is to provide a textile quality evaluation system based on EEG to solve the above problems.

[0004] This application provides a textile quality evaluation system based on EEG, including:

[0005] A textile tactile stimulation device, used for installing a textile specimen and for controlling the installed textile specimen to slide when started;

[0006] An EEG signal acquisition device, used for recording the EEG data of various regions of the subject's brain when the textile specimen slides on the skin contact part of the subject;

[0007] A computer device, connected to the textile tactile stimulation device and the EEG signal acquisition device, used for controlling the start or stop of the textile tactile stimulation device and for analyzing the EEG data sent by the EEG signal acquisition device to obtain the quality evaluation result of the textile specimen.

[0008] Optionally, the computer device includes:

[0009] A host computer, connected to the EEG signal acquisition device, used for analyzing the EEG data sent by the EEG signal acquisition device;

[0010] A slave computer, connected to the textile tactile stimulation device, used for controlling the start or stop of the textile tactile stimulation device.

[0011] Optionally, the slave computer is also connected to the EEG signal acquisition device, and the slave computer includes:

[0012] A task management module, configured to generate a marking signal and send the marking signal to the electroencephalogram (EEG) signal acquisition device, where the marking signal is used to identify the time stamp of a specific event, and the specific event includes the start event of the EEG stimulation;

[0013] A stimulation device control module, configured to control the start or stop of the textile tactile stimulation device;

[0014] A multi-thread control module, configured to receive the start instruction of the EEG stimulation, and after responding to the start instruction, simultaneously control the task management module to start generating the marking signal and control the stimulation device control module to start the textile tactile stimulation device.

[0015] Optionally, both the task management module and the stimulation device control module are preset with an EEG stimulation duration, an EEG stimulation time interval, and an EEG stimulation frequency;

[0016] The task management module is configured to generate a plurality of the marking signals according to the EEG stimulation duration, the EEG stimulation time interval, and the EEG stimulation frequency starting from the start of generating the marking signal;

[0017] The stimulation device control module is configured to control the start or stop of the textile tactile stimulation device according to the EEG stimulation duration, the EEG stimulation time interval, and the EEG stimulation frequency starting from the start of starting the textile tactile stimulation device.

[0018] Optionally, the EEG signal acquisition device is further configured to perform time stamp alignment processing on the EEG data of each region of the brain according to the marking signal.

[0019] Optionally, the multi-thread control module is further configured to generate an evaluation order of the textile specimens.

[0020] Optionally, the host computer includes:

[0021] An EEG data visualization display module, configured to perform visualization display and adjustment on the aligned EEG data and the marking signal sent by the EEG signal acquisition device;

[0022] An EEG data processing module, configured to import the EEG data to be processed saved in the EEG data visualization display module and perform data preprocessing.

[0023] Optionally, the EEG data processing module is further configured to perform a fast Fourier transform on the EEG data to be processed after data preprocessing to obtain initial data, where the initial data includes the average activity mean values of each region of the brain in a preset high-frequency interval;

[0024] The host computer is further configured to determine target data from the initial data, where the target data includes the average activity mean of each region of the right parietal lobe in a preset high-frequency range.

[0025] The host computer is further configured to determine the quality evaluation result of the textile sample based on the mapping relationship between the target data and the textile quality.

[0026] Optionally, the host computer is connected to the electroencephalogram signal acquisition device through a USB interface, and the slave computer is connected to the textile tactile stimulation device and the electroencephalogram signal acquisition device through a USB interface.

[0027] Optionally, the textile tactile stimulation device includes a motor and a motor control unit. The motor and the motor control unit are connected based on a common cathode connection method, and the motor control unit is connected to the slave computer through a USB interface.

[0028] Advantages of this technical solution: In this technical solution, by setting up the above-mentioned electroencephalogram-based textile quality evaluation system, it is possible to control the sliding of the textile sample at the skin contact part of the subject, collect the electroencephalogram data of each region of the subject's brain, and analyze the electroencephalogram data to objectively quantify the subject's touch feeling, and then obtain an objective quality evaluation result of the textile sample. It can be seen that this technical solution can simultaneously achieve the automatic control of the sliding of the textile sample, the acquisition of electroencephalogram data, and the analysis of electroencephalogram data, which is conducive to the efficient application of electroencephalogram technology in textile quality evaluation.

[0029] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit this application. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The accompanying drawings here are incorporated into the specification and form a part of this specification, showing embodiments consistent with this application, and are used together with the specification to explain the principles of this application. Obviously, the accompanying drawings in the following description are only some embodiments of this application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts. In the drawings:

[0031] Figure 1 is a structural diagram of an electroencephalogram-based textile quality evaluation system shown in an exemplary embodiment of this application;

[0032] Figure 2 is a structural diagram of the textile tactile stimulation device in an embodiment of this application.

[0033] Figure 3 is one of the partial structural diagrams of the textile tactile stimulation device in an embodiment of this application.

[0034] Figure 4 This is the second partial structure diagram of the textile tactile stimulation device in the embodiment of the present application.

[0035] Figure 5 This is the execution flowchart showing the motor control unit in an exemplary embodiment of the present application. Detailed implementation manners

[0036] The following will describe the implementation manners of the present application with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present application from the content disclosed in this specification. The present application can also be implemented or applied through other different specific implementation manners. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present application. It should be understood that the preferred embodiments are only for illustrating the present application rather than for limiting the protection scope of the present application.

[0037] It should be noted that the diagrams provided in the following embodiments only illustrate the basic concept of the present application in a schematic manner. Therefore, only the components related to the present application are shown in the diagrams, rather than being drawn according to the number, shape, and size of the components in actual implementation. The type, quantity, and ratio of each component in actual implementation can be arbitrarily changed, and the component layout type may also be more complex.

[0038] In the following description, a large number of details are explored to provide a more thorough explanation of the embodiments of the present application. However, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details. In other embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present application difficult to understand.

[0039] Please refer to Figure 1 , Figure 1 This is the structure diagram of the EEG-based textile quality evaluation system shown in an exemplary embodiment of the present application. As Figure 1 shown, in an exemplary embodiment, the EEG-based textile quality evaluation system includes a textile tactile stimulation device 10, an EEG signal acquisition device 30, and a computer device 40, which will be specifically described below.

[0040] The textile tactile stimulation device is used to install a textile specimen and to control the sliding of the installed textile specimen when started.

[0041] The following will describe Figures 2 to 4 the specific structure of the textile tactile stimulation device 10.

[0042] As Figures 2 to 4As shown, the textile tactile stimulation device 10 includes:

[0043] A box body 101, and the box body 101 has a hollow shell structure;

[0044] A motor module, including a motor 102 and a motor control unit connected to the motor 102, and the motor 102 is fixed inside the box body 101;

[0045] A transmission module, including a first transmission unit and a second transmission unit arranged inside the box body 101, the first transmission unit is connected to the output shaft of the motor 102, the second transmission unit is fixed to the box body 101, the first transmission unit and the second transmission unit are used to sleeved with a textile specimen 20, and used to drive the textile specimen 20 to rotate. Wherein, at least one side of the box body 101 is an open structure for extending into the area where the textile specimen 20 is located.

[0046] The above box body 101 has a hollow shell structure and is used to accommodate and fix at least some other structures in the textile tactile stimulation device 10.

[0047] The motor control unit of the above motor module is used to control the motor 102, including controlling the motor 102 to rotate and stop rotating. The motor 102 can be any motor 102 with a rotatable output shaft. For example, the motor 102 can be set as a stepping motor 102.

[0048] In some embodiments, the motor module may further include a driving unit, and the driving unit is respectively connected to the motor control unit and the motor 102, and is used to amplify the control signal output by the motor control unit to drive a high-power motor 102. The above motor control unit and driving unit can be arranged inside the box body 101 or outside the box body 101, and can be specifically set according to requirements.

[0049] The first transmission unit of the above transmission module is connected to the output shaft of the motor 102, that is, the rotation of the output shaft of the motor 102 can drive the first transmission unit to rotate. The second transmission unit is arranged on one side of the first transmission unit. When the textile specimen 20 is sleeved on the first transmission unit and the second transmission unit, if the output shaft of the motor 102 is controlled to rotate, the textile specimen 20 can be driven to rotate by the first transmission unit and the second transmission unit.

[0050] At least one side of the above-mentioned box body 101 is an open structure. The open structure refers to a structure that is not completely enclosed, including completely unenclosed and semi-enclosed. The semi-enclosed can be realized by a baffle provided with an opening, or by a structure such as a cover plate and a sliding panel that can be opened and closed. Through the open structure on at least one side, the participant's arm can reach into the box body 101 to touch the textile specimen 20, and after the tactile test of a textile specimen 20 is completed, it can reach in to replace the textile specimen 20.

[0051] In the embodiment of the present application, through the above settings, if the motor 102 rotates, the textile specimen 20 can be driven to rotate around the transmission unit through the first transmission unit and the second transmission unit. If the participant touches the textile specimen 20 through the open structure of the box body 101 at the same time, the textile specimen 20 can slide at the touched part, without the need for the participant to manually slide it, which is beneficial to improving efficiency and reducing interference caused by manual sliding.

[0052] Optionally, the first transmission unit includes a driving wheel 103 and a first driven wheel 104, and the second transmission unit includes a second driven wheel 105;

[0053] The driving wheel 103 is connected to the output shaft of the motor 102 and meshes with the first driven wheel 104. The gear shafts of the first driven wheel 104 and the second driven wheel 105 are both fixed to the box body 101. The driving wheel 103 and the second driven wheel 105 are used to sleeved with the textile specimen 20, and the driving wheel 103 and the first driven wheel 104 are used to squeeze the textile specimen 20 at the meshing position.

[0054] As an example, the above-mentioned driving wheel 103, first driven wheel 104 and second driven wheel 105 can be plastic gears of the same size, with the same number of teeth and module. The driving wheel 103 meshes with the first driven wheel 104. If the textile specimen 20 is squeezed at the meshing position of the driving wheel 103 and the first driven wheel 104, the driving wheel 103 and the first driven wheel 104 can drive the textile specimen 20 to rotate in the radial direction of the driving wheel 103; if the textile specimen 20 is sleeved on the driving wheel 103 and the second driven wheel 105 at the same time, the textile specimen 20 can be driven to rotate around the driving wheel 103 and the second driven wheel 105.

[0055] In the embodiment of the present application, through the above settings, the arm can be stretched downward into the middle area where the belt-shaped textile is located between the driving wheel 103 and the second driven wheel 105, and the inner side of the arm contacts the belt-shaped textile below, so that the belt-shaped textile slides on the inner side of the arm when the motor 102 is started. Compared with using a belt drive to fix the belt-shaped textile on the conveyor belt, the above structure in the embodiment of the present application can avoid interference caused by the conveyor belt material during the tactile test.

[0056] Optionally, first limiting baffles 1031 are respectively arranged on both sides of the rotating part of the driving wheel 103, and the first limiting baffles 1031 protrude from the edges of the rotating part of the driving wheel 103.

[0057] And / or

[0058] Second limiting baffles 1051 are respectively arranged on both sides of the rotating part of the second driven wheel 105, and the second limiting baffles 1051 protrude from the edges of the rotating part of the second driven wheel 105.

[0059] In this embodiment, by arranging the above-mentioned first limiting baffles 1031, it is possible to prevent the textile sample 20 from slipping out from both sides of the rotating part of the driving wheel 103 during rotation; by arranging the above-mentioned second limiting baffles 1051, it is possible to prevent the textile sample 20 from slipping out from both sides of the rotating part of the second driven wheel 105 during rotation.

[0060] Since the textile sample 20 needs to be squeezed between the driving wheel 103 and the first driven wheel 104, when the driving wheel 103 and the first driven wheel 104 are detachable, it is convenient to take out and install the textile sample 20. However, since the driving wheel 103 is connected to the output shaft of the motor 102, in order to reduce the influence on the motor 102, the first driven wheel 104 can be set to be detachable.

[0061] The installation structure of the detachable first driven wheel 104 is described below.

[0062] Optionally, the first driven wheel 104 is arranged between the driving wheel 103 and the top of the box body 101:

[0063] The top of the box body 101 is an open structure. An installation plate 106 is arranged in the area near the top of the box body 101 on the first side of the box body 101. The installation plate 106 is fixed with a first installation bracket 107 and a second installation bracket 108. The first installation bracket 107 and the second installation bracket 108 are respectively provided with a first installation groove and a second installation groove facing the top of the box body 101, and the rotating shaft of the first driven wheel 104 is clamped into the first installation groove and the second installation groove.

[0064] In the embodiment of the present application, through the above arrangement, the first driven wheel 104 can be taken out from the top of the box body 101 and can be clamped in, so as to facilitate the replacement of the textile sample 20.

[0065] Optionally, the first side and the second side of the box body 101 are open structures, and the first side and the second side are the radial two sides of the first transmission unit and the second transmission unit.

[0066] The second side mentioned above is the side opposite to the first side, and the mounting plate 106 can be arranged on the first side. The second side can be directly set as a completely unclosed structure, or a cover plate that can be opened and closed can be arranged.

[0067] With the above settings, it is possible to extend into the area where the transmission module is located from the first side and the second side, which is convenient for replacing the textile sample 20.

[0068] For the convenience of understanding, hereinafter, taking the transmission module including the above-mentioned driving wheel 103, the first driven wheel 104 and the second driven wheel 105 as an example, an exemplary description will be given on how to replace the textile sample 20.

[0069] a. Take out the first driven wheel 104 from the top of the box body 101;

[0070] b. Remove the sleeved strip-shaped textile test through the open structure on the first side, the second side or the top of the box body 101;

[0071] c. Sleeve the replaced textile sample 20 on the driving wheel 103 and the second driven wheel 105 through the open structures on the first side and the second side.

[0072] d. Snap the first driven wheel 104 into the above-mentioned first installation groove and the second installation groove from the top of the box body 101.

[0073] The replacement of the textile sample 20 can be completed through the above steps a to d.

[0074] Optionally, baffles are arranged on both the third side and the fourth side of the box body 101, and the baffle on the third side and the baffle on the fourth side are respectively provided with a first opening 109 and / or a second opening 110. The third side and the fourth side are the axial two sides of the first transmission unit and the second transmission unit.

[0075] In this embodiment, by arranging baffles on both the third side and the fourth side, the function of protecting each structure inside the box body 101 can be achieved; by arranging the above-mentioned first opening 109 and / or second opening 110, participants can extend their arms into the area where the strip-shaped textile is located through the first opening 109 and / or the second opening 110, and the first opening 109 and / or the second opening 110 can play a role in supporting the arms, which is beneficial to improving comfort.

[0076] Optionally, the baffle on the third side and the baffle on the fourth side are respectively provided with the first opening 109 and the second opening 110, and a columnar support cylinder 111 communicating the first opening 109 and the second opening 110 is arranged between the third side and the fourth side. Openings 1111 for threading the textile sample 20 are respectively arranged on both sides of the columnar support cylinder 111.

[0077] The above-mentioned columnar support cylinder 111 can play a role in supporting the overall extended arm, which is beneficial to further improve comfort.

[0078] Optionally, a third mounting bracket 112 is provided on the baffle of the third side or the baffle of the fourth side, and the third mounting bracket 112 is fixed to the rotating shaft of the second transmission unit.

[0079] In the embodiment of the present application, by using the existing above-mentioned third baffle and fourth baffle, and setting the third mounting bracket 112 fixed to the rotating shaft of the second transmission unit (such as the second driven wheel 105), it is beneficial to simplify the structure.

[0080] Optionally, a mounting table 113 is provided at the bottom of the box body 101, and the motor 102 is installed on one side of the mounting table 113 facing the top of the box body 101.

[0081] In this embodiment, a bottom plate can be provided at the bottom of the box body 101, and the above-mentioned mounting table 113 is provided on the bottom plate.

[0082] By the above setting, the output shaft of the motor 102 can be kept at a certain distance from the bottom of the box body 101, so as to avoid interference from the bottom of the box body 101 (such as the bottom plate) when the output shaft of the motor 102 rotates.

[0083] Optionally, at least one corner of the mounting side of the motor 102 is provided with a mounting hole, and at least one fourth mounting bracket 114 is provided between the mounting table 113 and the top of the box body 101, and the at least one fourth mounting bracket 114 passes through the mounting hole at the corresponding corner.

[0084] The above-mentioned mounting side can be the side of the motor close to the output shaft, and there are four corners.

[0085] In this embodiment, by the above setting, the fixed installation of the motor 102 can be simply realized, and the risk of the motor 102 sliding during rotation can be reduced.

[0086] In order to further improve the stability of the motor 102, it can be set that all four corners of the mounting side include mounting holes, and there are four fourth mounting brackets 114 between the mounting table 113 and the top of the box body 101. The four fourth mounting brackets 114 respectively pass through the mounting holes at the above four corners to fix the motor 102.

[0087] The electroencephalogram signal acquisition device 30 is used to record the electroencephalogram data of each region of the subject's brain when the textile sample slides on the skin contact part of the subject.

[0088] The above-mentioned electroencephalogram (EEG) signal acquisition device 30 can be an actiCHamp Plus electroencephalogram recording amplifier, which is compatible with active and passive electrode systems and powered by a lithium-ion battery. Its sampling channels start from 32 channels and can be extended to 160 channels according to needs (the more channels, the more detailed the brain regions that can be recorded), so as to meet the experimental requirements of different scales. In addition, it includes 8 auxiliary channels for connecting other physiological sensors, and the sampling rate is as high as 100 kHz.

[0089] The EEG signal acquisition device 30 can be connected to an electrode cap, and the electrodes on the electrode cap are placed on the scalp to capture the weak electrical signals generated by the brain. The electrode cap is distributed with multiple electrodes, which are respectively placed at specific positions on the scalp, and these positions correspond to different regions of the brain. The signals collected by each electrode are amplified and recorded by the EEG signal acquisition device 30 to obtain the EEG data of each region of the above-mentioned brain.

[0090] A computer device 40, connected to the textile tactile stimulation device 10 and the EEG signal acquisition device 30, is used to control the start or stop of the textile tactile stimulation device 10, and to analyze the EEG data sent by the EEG signal acquisition device 30 to obtain the quality evaluation result of the textile sample.

[0091] In the embodiment of the present application, the subject wears the above-mentioned electrode cap and contacts the textile sample installed on the textile tactile stimulation device 10. The computer device 40 can control the start of the above-mentioned textile tactile stimulation device 10 when the EEG stimulation task starts. The textile sample slides at the skin contact part to stimulate the generation of weak electrical signals in each region of the subject's brain; the EEG signal acquisition device 30 collects the EEG data of each region of the brain and uploads it to the computer device 40 for analysis, so as to obtain an objective quality evaluation result of the textile sample.

[0092] By using the EEG-based textile quality evaluation system of the present application, it is possible to simultaneously realize the automatic control of the sliding of the textile sample, the acquisition of EEG data, and the analysis of EEG data, which is beneficial to the efficient application of EEG technology in textile quality evaluation.

[0093] Optionally, the computer device 40 includes:

[0094] A host computer, connected to the EEG signal acquisition device 30, for analyzing the EEG data sent by the EEG signal acquisition device 30;

[0095] A slave computer, connected to the textile tactile stimulation device 10, for controlling the start or stop of the textile tactile stimulation device 10.

[0096] In this embodiment, the electroencephalogram (EEG) data analysis and the control of the textile tactile stimulation device 10 are respectively implemented by a host computer and a slave computer. In this way, the slave computer can quickly respond to control signals, and the host computer can focus on data processing, which is beneficial to improving the system efficiency.

[0097] Optionally, the slave computer is further connected to the EEG signal acquisition device 30, and the slave computer includes:

[0098] A task management module, configured to generate a marker signal and send the marker signal to the EEG signal acquisition device 30. The marker signal is used to identify the timestamp of a specific event, and the specific event includes the start event of the EEG stimulation;

[0099] A stimulation device control module, configured to control the start or stop of the textile tactile stimulation device 10;

[0100] A multi-thread control module, configured to receive the start instruction of the EEG stimulation, and after responding to the start instruction, simultaneously control the task management module to start generating the marker signal and control the stimulation device control module to start the textile tactile stimulation device 10.

[0101] The above task management module can be implemented by installing E-PRIME software. The above marker signal is used to identify the timestamp of a specific event. There may be multiple marker signals, and each marker signal contains a timestamp, indicating the specific time point when the specific event occurs. The specific event includes the start event of the EEG stimulation. In some embodiments, the specific event further includes the end event of the EEG stimulation, etc.

[0102] Optionally, the above slave computer is connected to the EEG signal acquisition device 30, specifically through a USB interface. The slave computer communicates with the EEG signal acquisition device 30 through a serial port, so as to send the marker signal to the EEG signal acquisition device 30.

[0103] The above marker signal is mainly used for EEG data alignment. Specifically, in some embodiments, after the task management module sends the above marker signal to the EEG signal acquisition device 30, the EEG signal acquisition device 30 performs timestamp alignment processing on the EEG data of each brain region according to the marker signal. Thus, based on the timestamp of the marker signal and the timestamp of the EEG data, it is possible to determine the EEG data corresponding to the current marker signal.

[0104] The above-mentioned stimulation device control module can control the above-mentioned motor 102 by controlling the above-mentioned motor control unit, that is, control the textile tactile stimulation device 10. As an example, the motor control unit can be an Arduino control unit, and the stimulation device control module installs Arduino IDE, which is a control tool for the Arduino control unit. Control parameters of the motor can be preset in the Arduino control unit to accurately control the rotation speed of the motor (for example, 1-10 cm / s).

[0105] Optionally, the above-mentioned lower computer is connected to the textile tactile stimulation device 10, and specifically can be connected to the motor drive unit through a USB interface. The lower computer communicates with the motor drive unit through a serial port.

[0106] In some embodiments, the above-mentioned motor control unit and the motor 102 can be connected based on the common cathode connection method. When the textile tactile stimulation device 10 includes a drive circuit, the drive circuit is connected to the motor control unit and the motor 102 respectively through the common cathode connection method.

[0107] The above-mentioned multi-thread control module functions to control the task management module and the stimulation device control module simultaneously, so that when a start instruction for electroencephalogram (EEG) stimulation is received, a marker signal can be generated in a timely manner and the textile tactile stimulation device 10 can be controlled to start in a timely manner. Among them, the above-mentioned multi-thread control module can be implemented based on the Python multi-thread code pre-designed in Visual Studio Code. As an example, the multi-thread control module can obtain the start instruction for EEG stimulation through keyboard monitoring. For example, it can be set that when the multi-thread control module monitors that the space bar is pressed, that is, the start instruction for EEG stimulation is received.

[0108] In some embodiments, the above-mentioned multi-thread control module can also generate the evaluation order of textile specimens. For example, the random function in Python can be used to generate the evaluation order of textile specimens, and the experimenter installs the textile specimens on the textile tactile stimulation device 10 in batches based on the above-mentioned evaluation order.

[0109] In the embodiments of the present application, by setting the above-mentioned lower computer to include a task management module, a stimulation device control module, and a multi-thread control module respectively, it is beneficial to receive the start instruction for EEG stimulation in a timely manner, and to simultaneously control the generation of the above-mentioned marker signal and the control of the textile tactile stimulation device 10, thereby improving the system reliability.

[0110] Optionally, both the task management module and the stimulation device control module are preset with the EEG stimulation duration, the EEG stimulation time interval, and the number of EEG stimulation times;

[0111] The task management module is used to generate a plurality of the marker signals starting from the start of generating the marker signal, according to the EEG stimulation duration, the EEG stimulation time interval, and the number of EEG stimulation times.

[0112] The stimulation device control module is used to control the textile tactile stimulation device 10 to be turned off or started starting from the start of activating the textile tactile stimulation device 10, according to the EEG stimulation duration, the EEG stimulation time interval, and the number of EEG stimulation times.

[0113] The above-mentioned task management module can generate a marker signal at the start of each stimulation to identify the corresponding EEG data. For example, assuming that the number of EEG stimulations for each textile sample is 3 times, a marker signal is generated at the start of each stimulation.

[0114] In this embodiment, by presetting the above-mentioned EEG stimulation duration, EEG stimulation time interval, and number of EEG stimulation times, regular multiple stimulations can be realized without repeatedly inputting the start instruction of EEG stimulation. Since multiple stimulations can reduce the random error of single stimulation, the present application can improve the stability and repeatability of data through the above settings.

[0115] Optionally, the host computer includes:

[0116] The EEG data visualization and display module is used to visually display and adjust the aligned and processed EEG data and the marker signal sent by the EEG signal acquisition device 30.

[0117] The EEG data processing module is used to import the EEG data to be processed saved in the EEG data visualization and display module and perform data preprocessing.

[0118] The above-mentioned EEG data visualization and display module can install BrainVision Recorder. Through the EEG data visualization and display module, the aligned and processed EEG data and the marker signal sent by the EEG signal acquisition device 30 can be displayed in real time, and the experimenter can adjust them in real time.

[0119] The above-mentioned EEG data processing module can install MATLAB to implement the above data preprocessing function. The above data preprocessing can include interpolation of bad channels (Topographic Interpolation), rereferencing, filtering, removal of electrooculogram, removal of artifacts, segmentation according to the marker signal, baseline calibration, and segment mean processing.

[0120] In the embodiments of the present application, setting the above-mentioned EEG data visualization and display module is beneficial for experimenters to view and adjust EEG data in a timely manner; setting the above-mentioned EEG data processing module is beneficial for obtaining standardized EEG data.

[0121] Optionally, the EEG data processing module is further configured to perform a fast Fourier transform on the to-be-processed EEG data after data preprocessing to obtain initial data, where the initial data includes the average activity mean values of each region of the brain in a preset high-frequency interval;

[0122] The host computer is further configured to determine target data from the initial data, where the target data includes the average activity mean values of each region of the right parietal lobe in a preset high-frequency interval;

[0123] The host computer is further configured to determine the quality evaluation result of the textile sample based on the mapping relationship between the target data and the textile quality.

[0124] Through experiments, it is determined that higher beta-band oscillations are related to more pleasant stimuli, and the frequency range of the beta band is usually 12 - 30 Hz. Based on this, a preset high-frequency interval (such as 26 - 28 Hz) is set in the present application. After performing the above-mentioned fast Fourier transform, the average activity mean values (which can be average activity amplitudes, unit: μV) of each region of the brain in the preset high-frequency interval are extracted, that is, the above-mentioned initial data is extracted, and further analysis is performed to obtain the quality evaluation result.

[0125] The above-mentioned regions of each part of the brain include regions of each part of the right parietal lobe and regions of each part of the right frontal lobe, etc. Through experiments, it is determined that there is a strong positive correlation between the oscillations of each region of the right parietal lobe and the quality of the textile. Based on this, in the embodiments of the present application, target data is extracted from the above-mentioned initial data, that is, the average activity mean values of each region of the right parietal lobe in the above-mentioned preset high-frequency interval are extracted. Regions of each part of the right parietal lobe include regions (P8, CP6, TP10). Among them, P8 is located at the rear of the right parietal lobe; CP6 is located in the middle of the right parietal lobe; TP10: is located on the outside of the right parietal lobe, close to the temporal lobe.

[0126] After obtaining the average activity mean values (i.e., target data) of each region in the right parietal lobe in the above-mentioned preset high-frequency interval, based on the mapping relationship between the target data and the fabric quality, the quality evaluation result of the fabric sample can be determined. As an example, the average activity mean values of (P8, CP6, TP10) can be set to correspond to different weights respectively, and weighted to obtain the final data; or the average activity mean values of (P8, CP6, TP10) can be directly averaged again to obtain the final data. Based on the mapping relationship between the above-mentioned final data and the fabric quality, the quality evaluation result of the fabric sample is determined. Among them, the mapping relationship can be determined in advance based on experiments. For example, the fabric sample is scored for softness using a professional instrument to obtain a softness grade, and based on the above-mentioned final data corresponding to the softness grade, the above-mentioned mapping relationship is determined.

[0127] In the embodiments of the present application, through the above settings, the tactile sensations of the subjects can be objectively quantified, and the quality evaluation results of the fabric samples can be accurately obtained.

[0128] To more clearly understand the technical solutions of the embodiments of the present application, a specific embodiment is provided below for illustration.

[0129] a. In an event-related potentials (ERPs) laboratory with an indoor temperature of 26°C and relatively constant humidity. The subjects wear an electrode cap of the internationally common 10-20 system and sit on a chair in a closed-eye and static state. The above-mentioned subjects all meet the requirements of the experiment, have no history of neurological diseases, and have not taken drugs that may affect brain electrical activities, etc.

[0130] b. Selection of experimental materials. Four fabric samples are selected, and all are scored for softness using a professional instrument, and are classified into A, B, C, and D according to the softness score difference (rounded off).

[0131] c. The task host will prompt that it is the nth emotional tactile stimulus fabric sample for cyclic stroking stimulation. The right arm of the subject is placed into the above-mentioned first opening 109 or the second opening 110, and the exposed right forearm skin just contacts the driven fabric sample. After the subject is ready, press the space bar to enter the experiment. The multi-thread control module of the lower computer controls the task management module and the stimulus device control module respectively. The task management module and the stimulus device control module generate corresponding marker signals according to a brain electrical stimulation duration of 20 s, a time interval of 40 s for each brain electrical stimulation, and 3 stroking stimulations for each fabric sample. The stimulus device control module controls the motor control unit according to a brain electrical stimulation duration of 20 s, a time interval of 40 s for each brain electrical stimulation, and 3 stroking stimulations for each fabric sample, and then controls the motor to start and stop correspondingly. In this way, it is no longer necessary to use the space bar and manual timing in the experimental stage of the same fabric sample.

[0132] Among them, parameters such as the rotational speed of the above-mentioned motor 102 are controlled by a motor control unit (such as an Arduino control unit). As Figure 5 , as shown in the execution flow chart of the motor control unit, the contact sequence between the specimen and the skin is generated by a random function in Python. After testing one textile specimen, the next sequential textile specimen will be reinstalled and the motor position will be reset, and the corresponding program will be executed.

[0133] d. The lower computer marks the time points of the occurrence of electroencephalogram (EEG) stimulation on the EEG graph of the EEG signal acquisition device 30 through the USB interface. When the stimulation of one textile ends, the subject can press the keyboard to start the next experiment; during EEG data analysis, these marked time points will be used as the starting points for the occurrence of event-related potentials, and the EEG waves will be segmented and superimposed.

[0134] e. The EEG data visualization display module visualizes and adjusts the EEG data and marker signals sent by the EEG signal acquisition device 30 through BrainVision Recorder.

[0135] f. The EEG data processing module preprocesses the EEG data saved by the EEG data visualization display module through MATLAB. The following is a specific description of it.

[0136] f1. Interpolation of bad leads. In the interpolation of bad leads, spherical spline interpolation (SSI) is used. For subject one, the bad leads of the Fz electrode and the TP9 electrode are interpolated, and for subject two, the bad leads of the Fz electrode and the TP9 electrode are interpolated.

[0137] f2. Re-reference processing. During the experimental acquisition stage, the lead is used as the reference electrode; during the data preprocessing stage, the bilateral mastoid average (TP9, TP10) reference is reselected. The bilateral mastoid average reference can effectively reduce artifacts caused by muscle activity, eye movement, etc., thereby improving the quality of EEG signals and the accuracy of analysis.

[0138] f3. Filtering processing. In the filtering process, the infinite impulse response filtering method is selected, and a zero-phase shift Butterworth filter is used. The characteristic of the Butterworth filter is that the frequency response curve in the passband is maximally flat without fluctuations, and it gradually decreases to zero in the stopband.

[0139] f4. Ocular artifact removal. During the process of ocular correction, independent component analysis (ICA) is used for ocular artifact correction. This method is a class of algorithms that recover statistically independent components from linear mixtures based on higher-order statistics.

[0140] f5. Artifact removal. In the process of removing artifacts (Raw Data Inspection, removing artifact signals caused by equipment or subject movement), the entire EEG dataset is systematically screened through an automatic detection algorithm to identify regions with abnormal voltage changes.

[0141] f6. Segmentation according to marker signals. The continuous EEG data (specifically, electroencephalogram EEG) records are segmented into specific time periods according to the marker signals.

[0142] f7. Baseline calibration. The Segmentation Wizard tool can be used for baseline correction (BaselineCorrection). Each specific time period starts 200 milliseconds before the marker and lasts until 8000 milliseconds after the marker, with a total duration of 8200 milliseconds. This segmentation strategy allows for detailed analysis of each event-related potential. To maintain data integrity, the "Skip Bad Intervals" function is enabled to automatically exclude time periods containing artifacts.

[0143] f8. Epoch mean processing. Multiple single trials are averaged together through epoch averaging to create an average EEG waveform.

[0144] g1. Experimental data analysis. The above average EEG waveform (i.e., the EEG data saved after preprocessing in MATLAB) is subjected to a fast Fourier transform, and the mean value (μV) of the high-frequency β average activity in the range of 26 - 28 Hz is exported for analysis (initial data). Among them, during the above fast Fourier transform process, the Hanning Window is selected to optimize the spectral estimation and reduce spectral leakage. By setting a specific resolution of 0.5 Hz, the accuracy of frequency analysis is ensured.

[0145] g2. Export the functional values of the right parietal lobe (P8, CP6, TP10) of the subject in the initial data, and calculate the mean value (μV) of the activity of the right parietal lobe of the subject under the four emotional tactile stimulus textile samples of A, B, C, and D. Through experiments, it is found that as the softness of the textile sample changes, the functional values of the human body in the right parietal lobe (P8, CP6, TP10) will change accordingly, so the pleasant emotion changes accordingly, and usually shows a positive correlation.

[0146] Based on the above steps, it can be seen that in the embodiments of the present application, the quality of the fabric is determined by the functional values of the above right parietal lobe (P8, CP6, TP10), and the reliability is relatively high. In the subsequent process of fabric quality evaluation, based on the fabric quality evaluation system of the present application, it can simulate a real emotional tactile stimulation scenario, and combined with the electroencephalogram signal acquisition and analysis technology, it can realize an objective quantitative evaluation of the emotional tactile experience quality of the fabric, so as to obtain an objective and reliable fabric quality evaluation result.

[0147] The above embodiments are only used to exemplarily illustrate the principle and efficacy of the present application, rather than to limit the present application. Any person familiar with this technology can modify or change the above embodiments without departing from the spirit and scope of the present application. Therefore, all equivalent modifications or changes completed by those with ordinary knowledge in the technical field without departing from the spirit and technical idea disclosed by the present application should still be covered by the claims of the present application.

Claims

1. A textile quality evaluation system based on electroencephalogram, characterized in that, Comprising: A textile tactile stimulation device for mounting a textile specimen and for controlling the sliding of the mounted textile specimen in the case of activation; An electroencephalogram (EEG) signal acquisition device for recording EEG data of various regions of the subject's brain when the textile specimen slides on the skin contact area of the subject; A computer device connected to the textile tactile stimulation device and the EEG signal acquisition device for controlling the activation or deactivation of the textile tactile stimulation device and for analyzing the EEG data sent by the EEG signal acquisition device to obtain a quality evaluation result of the textile specimen.

2. The EEG-based textile quality evaluation system according to claim 1, wherein The computer device includes: A host computer connected to the EEG signal acquisition device for analyzing the EEG data sent by the EEG signal acquisition device; A slave computer connected to the textile tactile stimulation device for controlling the activation or deactivation of the textile tactile stimulation device.

3. The EEG-based textile quality evaluation system according to claim 2, wherein The slave computer is also connected to the EEG signal acquisition device, and the slave computer includes: A task management module for generating a marker signal and sending the marker signal to the EEG signal acquisition device, the marker signal being used to identify the time stamp of a specific event, the specific event including the start event of EEG stimulation; A stimulation device control module for controlling the activation or deactivation of the textile tactile stimulation device; A multi-thread control module for receiving the start instruction of the EEG stimulation and for, after responding to the start instruction, simultaneously controlling the task management module to start generating the marker signal and controlling the stimulation device control module to start activating the textile tactile stimulation device.

4. The EEG-based textile quality evaluation system according to claim 3, wherein, Both the task management module and the stimulation device control module are preset with an EEG stimulation duration, an EEG stimulation time interval, and an EEG stimulation number; The task management module is used for generating a plurality of the marker signals according to the EEG stimulation duration, the EEG stimulation time interval, and the EEG stimulation number starting from the start of generating the marker signal; The stimulation device control module is used for controlling the closing or activation of the textile tactile stimulation device according to the EEG stimulation duration, the EEG stimulation time interval, and the EEG stimulation number starting from the start of activating the textile tactile stimulation device.

5. The EEG-based fabric quality evaluation system according to claim 3 or 4, characterized in that, The EEG signal acquisition device is also used for performing time stamp alignment processing on the EEG data of various regions of the brain according to the marker signal.

6. The EEG-based textile quality evaluation system according to claim 3, characterized in that The multi-thread control module is also used for generating the evaluation order of the textile specimen.

7. The EEG-based textile quality evaluation system according to claim 5, wherein The host computer includes: An EEG data visualization display module for visually displaying and adjusting the aligned EEG data and the marker signal sent by the EEG signal acquisition device; An EEG data processing module for importing the to-be-processed EEG data saved in the EEG data visualization display module and performing data preprocessing.

8. The EEG-based fabric quality evaluation system according to claim 7, characterized in that, The EEG data processing module is also used for performing a fast Fourier transform on the to-be-processed EEG data after data preprocessing to obtain initial data, the initial data including the average activity mean values of various regions of the brain in a preset high-frequency interval. The host computer is further configured to determine target data from the initial data, where the target data includes the average activity mean of each region of the right parietal lobe in a preset high-frequency interval; The host computer is further configured to determine a quality evaluation result of the textile sample based on the mapping relationship between the target data and the quality of the textile.

9. The electroencephalogram-based textile quality evaluation system according to claim 3, wherein The host computer is connected to the electroencephalogram signal acquisition device through a USB interface, and the slave computer is connected to the textile tactile stimulation device and the electroencephalogram signal acquisition device through a USB interface.

10. The EEG-based textile quality evaluation system according to claim 2 or 9, characterized in that, The textile tactile stimulation device includes a motor and a motor control unit. The motor and the motor control unit are connected based on a common cathode connection method, and the motor control unit is connected to the slave computer through a USB interface.

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