技术领域technical field
本发明涉及一种健康管理设备，特别是涉及一种情绪干预和训练设备，应用于生命与健康设备技术、情绪调控技术和电生理技术领域。The invention relates to a health management device, in particular to an emotional intervention and training device, which is applied in the fields of life and health equipment technology, emotion regulation technology and electrophysiological technology.
背景技术Background technique
情绪是瞬息万变的心理与生理现象，反应了机体对不断变化的环境所采取的适应模式，是对客观事物的态度体验和行为反应。随着情绪的发生，个体的生理、心理体验以及外部行为都会产生相应的改变。根据外在刺激对个体内在体验、生理反应以及行为学表现进行调控的方式就是情绪调控。情绪调控能力是人类适应环境的一种重要的认知功能，良好的情绪调控能力是一个人心理健康的重要标志。如果情绪调控能力出现问题，则容易引发抑郁症、焦虑症等精神疾病。因此，情绪调控的干预和能力的训练显得尤为重要。Emotion is an ever-changing psychological and physiological phenomenon, which reflects the adaptation mode adopted by the body to the constantly changing environment, and is an attitude experience and behavioral response to objective things. With the occurrence of emotions, the individual's physical and psychological experience and external behavior will change accordingly. Emotion regulation is the way to regulate an individual's inner experience, physiological response and behavioral performance according to external stimuli. Emotion regulation ability is an important cognitive function for human beings to adapt to the environment, and good emotion regulation ability is an important symbol of a person's mental health. If there is a problem with the ability to regulate emotions, it is easy to cause mental diseases such as depression and anxiety. Therefore, the intervention of emotion regulation and the training of ability are particularly important.
目前的干预/训练主要基于行为学的方法，可通过心理健康教育，对其情绪和人际方面进行干预。研究发现，情绪调控过程会激发前额叶皮层的活动，降低杏仁核活动，情绪调节和控制过程是可观测、可干预的。随着生物反馈技术的发展，针对情绪调控的训练成为可能。近两年已经有研究利用实时的功能磁共振成像fMRI反馈技术进行情绪调控的训练，被试通过直观的观测到自身的大脑活动情况，来完成调控过程，有效证实了系统的可行性。但是，基于fMRI的反馈实验代价高；同时作为一个动态过程，情绪调控的时变特性是毫秒级的，采用fMRI进行的反馈系统，实时性不高，影响了调控效率。The current intervention/training is mainly based on behavioral methods, which can be used to intervene in emotional and interpersonal aspects through mental health education. Studies have found that the process of emotion regulation will stimulate the activity of the prefrontal cortex and reduce the activity of the amygdala. The process of emotion regulation and control is observable and intervenable. With the development of biofeedback technology, training for emotional regulation has become possible. In the past two years, there have been studies using real-time functional magnetic resonance imaging (fMRI) feedback technology for emotional regulation training. The subjects completed the regulation process by intuitively observing their own brain activity, effectively confirming the feasibility of the system. However, the feedback experiment based on fMRI is costly; at the same time, as a dynamic process, the time-varying characteristics of emotion regulation are at the millisecond level, and the feedback system using fMRI is not real-time, which affects the regulation efficiency.
发明内容Contents of the invention
为了解决现有技术问题，本发明的目的在于克服已有技术存在的不足，提供一种基于脑电反馈的情绪调控系统，系统利用头皮脑电EEG实施反馈一方面大大提高了时间分辨率，有效弥补了fMRI反馈系统的不足，同时能够简易、实时高效地将当前脑电活动反馈给训练者，从而提高反馈的效率、降低了系统的成本。本发明情绪调控系统使用户能便捷地对调控情绪，最终达到能力训练的目的，是一种新型的情绪调控系统。In order to solve the problems of the prior art, the purpose of the present invention is to overcome the deficiencies in the prior art, and provide an emotional control system based on EEG feedback. The system utilizes the scalp EEG to implement feedback. On the one hand, the time resolution is greatly improved, effectively It makes up for the deficiencies of the fMRI feedback system, and at the same time can simply, real-time and efficiently feed back the current brain electrical activity to the trainer, thereby improving the efficiency of feedback and reducing the cost of the system. The emotional regulation system of the present invention enables users to conveniently regulate emotions, and finally achieves the purpose of ability training, and is a new type of emotional regulation system.
为达到上述发明创造目的，本发明采用下述发明构思：In order to achieve the above-mentioned invention creation purpose, the present invention adopts following inventive concept:
本发明基于脑电生物反馈技术，它借助脑电信号分析对被试进行情绪调控的训练。系统首先通过检测负性情绪图片呈现过程中脑电波的相对功率变化情况，来判定被试的情绪调控过程，并将该时刻的相对功率值作为反馈的指标对图片进行加噪处理，完成对被试调控结果的反馈，反复进行以达到情绪调控能力训练的目的，最后以被试完成情绪调控的时间来评价被试当前的情绪调控能力。The invention is based on the electroencephalogram biofeedback technology, which uses the electroencephalogram signal analysis to carry out the emotional control training for the subjects. The system firstly detects the relative power changes of the brain waves during the presentation of negative emotional pictures to determine the emotional regulation process of the subjects, and uses the relative power value at this moment as a feedback indicator to add noise to the pictures to complete the control of the subjects. The feedback of the test regulation results is repeated to achieve the purpose of emotion regulation ability training. Finally, the time for the subjects to complete the emotion regulation is used to evaluate the subjects' current emotion regulation ability.
根据上述发明构思，本发明采用下述技术方案：According to above-mentioned inventive concept, the present invention adopts following technical scheme:
一种基于脑电反馈的情绪调控系统，包括信息采集模块、信号处理控制模块、反馈模块、人机界面模块、评价模块和数据管理模块，系统包括管理员与受试者两类用户，他们具有不同的权限，人机界面模块包含通信参数设置功能、利用图片、声音或视频的情绪刺激显示功能和脑电活动特性显示功能，通信参数设置功能实现信息采集模块与服务器之间的连接参数的设置，仅允许管理员进行操作，脑电活动特性显示功能显示受试者的大脑活动的特征，利用图片、声音或视频的情绪刺激呈现给受试者，作为受试者的认知目标，对于脑电活动特性显示功模块，根据信号处理控制模块计算得到脑电特征，将其以柱形图和脑电地形图的方式展现出来，此功能仅限管理员使用，信息采集模块采用服务器-客户端的通信方式，以脑电信号采集系统作为服务器，以PC机作为客户端，来读取脑电信号数据，脑电信号采集系统通过人机界面模块的通信参数设置控制信号连接，来启动实时采集脑电信号，信号处理控制模块接收信息采集模块的输出数据并进行预处理，计算脑电波的特征，以设定反馈阈值和情绪调控的指标，并输出到数据管理模块，通过比较情绪调控指标与阈值来决定控制反馈模块；反馈模块接收到信号处理控制模块的加噪指令后，采用对人机界面模块显示的情绪刺激进行加噪的方式，将加过噪声的情绪刺激反馈输出给人机界面，使受试者接受反馈模块输出的信息，实现情绪调控训练，反馈模块接收到信号处理控制模块的停止加噪指令后，则停止加噪；受试者通过评价模块对情绪调控前后的情绪刺激进行效价评价和唤醒度评价，评价结果输出到数据管理模块；数据管理模块负责程序运行中数据的记录、保存和输出，包括记录信号处理控制模块生成的反馈信号、情绪刺激呈现时刻、情绪刺激加噪时刻以及情绪刺激停止加噪时刻数据的记录和保存，管理人员能将保存后的数据打印输出。An emotion regulation system based on EEG feedback, including an information collection module, a signal processing control module, a feedback module, a human-machine interface module, an evaluation module and a data management module. The system includes two types of users, administrators and subjects, who have Different permissions, the man-machine interface module includes the communication parameter setting function, the emotional stimulation display function using pictures, sounds or videos, and the brain electrical activity characteristic display function, and the communication parameter setting function realizes the setting of the connection parameters between the information collection module and the server , only administrators are allowed to operate. The brain activity characteristic display function displays the characteristics of the brain activity of the subject, and presents the emotional stimulation of the picture, sound or video to the subject as the cognitive goal of the subject. The electrical activity characteristic display function module calculates the EEG characteristics according to the signal processing control module, and displays them in the form of histograms and EEG topographic maps. This function is limited to administrators. The information collection module adopts a server-client The communication method uses the EEG signal acquisition system as the server and the PC as the client to read the EEG signal data. The EEG signal acquisition system starts the real-time acquisition of the EEG signal through the communication parameter setting control signal connection of the man-machine interface module. The electrical signal, the signal processing control module receives the output data of the information acquisition module and performs preprocessing, calculates the characteristics of the brain wave, to set the feedback threshold and the index of emotional regulation, and output to the data management module, by comparing the emotional regulation index with the threshold to determine the control of the feedback module; after the feedback module receives the noise-adding instruction from the signal processing control module, it adopts the method of adding noise to the emotional stimulus displayed by the man-machine interface module, and outputs the emotional stimulus with added noise to the human-machine interface. Make the subject accept the information output by the feedback module to realize emotion regulation training. After the feedback module receives the stop noise instruction from the signal processing control module, it stops adding noise; the subject evaluates the emotional stimulation before and after emotion regulation through the evaluation module. Valence evaluation and arousal evaluation, the evaluation results are output to the data management module; the data management module is responsible for the recording, storage and output of data during program operation, including recording the feedback signal generated by the signal processing control module, the moment when emotional stimulation is presented, and the time when emotional stimulation is added. Record and save the data at the moment of noise and the moment when emotional stimulation stops adding noise, and the management personnel can print out the saved data.
作为优选的技术方案，上述人机界面模块的利用图片、声音或视频的情绪刺激显示功能显示输出的情绪刺激为情绪刺激图片。As a preferred technical solution, the emotional stimulation display function of the man-machine interface module using pictures, sounds or videos displays and outputs emotional stimulation as emotional stimulation pictures.
作为上述方案进一步优选的技术方案，信号处理控制模块首先根据受试者受刺激前的脑电特征来确定其脑电特征的初始阈值，然后在进行情绪调控时将受试者受刺激时情绪调控的脑电特征数据与脑电特征的初始阈值进行比较，以确定是否控制反馈模块进行后续的反馈。As a further preferred technical solution of the above scheme, the signal processing control module first determines the initial threshold of the EEG characteristics according to the EEG characteristics of the subject before being stimulated, and then adjusts the EEG characteristics of the subject when being stimulated. The EEG feature data are compared with the initial threshold of the EEG feature to determine whether to control the feedback module for subsequent feedback.
作为上述方案进一步优选的技术方案，在信号处理控制模块中，若脑电特征值高于初始阈值的30％，则向反馈模块发送加噪指令，若低于初始阈值的90％，则向反馈模块发送停止加噪指令。As a further preferred technical solution of the above scheme, in the signal processing control module, if the EEG characteristic value is higher than 30% of the initial threshold, then send a noise-adding instruction to the feedback module; The module sends a command to stop adding noise.
作为上述方案进一步优选的技术方案，在反馈模块中，当接收到信号处理控制模块的加噪指令后，则对图片进行加噪，使受试者接受反馈模块输出的信息，实现情绪调控训练，当接收到停止加噪指令后，则停止加噪，反馈结束。反馈模块通过加噪的方式对受试者进行信息反馈，使其感知当前的情绪调控状态，当接收到信号处理控制模块的停止加噪指令时，则停止对情绪加噪，告知受试者情绪调控过程结束。As a further preferred technical solution of the above scheme, in the feedback module, after receiving the noise addition instruction from the signal processing control module, noise is added to the picture, so that the subject accepts the information output by the feedback module to realize emotion regulation training, After receiving the instruction to stop adding noise, stop adding noise, and the feedback ends. The feedback module provides information feedback to the subjects by means of adding noise, so that they can perceive the current state of emotional regulation. When receiving the signal processing control module's stop noise instruction, it stops adding noise to the emotions and informs the subjects of their emotions. The regulation process ends.
本发明与现有技术相比较，具有如下显而易见的突出实质性特点和显著优点：Compared with the prior art, the present invention has the following obvious outstanding substantive features and significant advantages:
1.本发明基于脑电反馈的情绪调控系统，具有成本低、时间分辨率高的特点；1. The emotional control system based on EEG feedback of the present invention has the characteristics of low cost and high time resolution;
2.本发明使用脑电生物反馈技术进行情绪调控，根据实时的脑电反馈的结果，提供情绪状态变化，使用户能便捷地调控情绪，最终达到能力训练的目的，是一种新型的情绪调控系统；2. The present invention uses EEG biofeedback technology to regulate emotions. According to the results of real-time EEG feedback, it provides emotional state changes, so that users can easily regulate emotions, and finally achieve the purpose of ability training. It is a new type of emotion regulation system;
3.本发明采用对刺激进行加噪的方式显示反馈信息，保持受试者注意力的集中，最大程度地减少了刺激之外的干扰；3. The present invention adopts the way of adding noise to the stimulus to display the feedback information, keep the concentration of the subject's attention, and minimize the interference other than the stimulus;
4.本发明涉及情绪调控、电生理领域，使用脑电生物反馈技术进行情绪调控能力的训练；4. The present invention relates to the fields of emotion regulation and electrophysiology, and uses EEG biofeedback technology to train emotion regulation ability;
5.大脑具有可塑性，脑电可以反映大活动的瞬态变化，本发明通过生物反馈技术进行大脑的情绪调节能力的训练，可以实现提高受试者情绪调控能力的目的，使用本脑电生物反馈系统，可以有效提高人们调节负性情绪的能力。5. The brain has plasticity, and EEG can reflect the transient changes of large activities. The present invention uses biofeedback technology to train the brain's emotional regulation ability, which can achieve the purpose of improving the subject's emotional regulation ability. Using this EEG biofeedback The system can effectively improve people's ability to regulate negative emotions.
附图说明Description of drawings
图1为本发明优选实施例基于脑电反馈的情绪调控系统的结构示意图。FIG. 1 is a schematic structural diagram of an emotion regulation system based on EEG feedback in a preferred embodiment of the present invention.
图2为本发明优选实施例的初始评价流程图。Figure 2 is a flowchart of the initial evaluation of the preferred embodiment of the present invention.
图3为本发明优选实施例的情绪调控反馈的操作流程图。Fig. 3 is an operation flow chart of emotion regulation feedback in a preferred embodiment of the present invention.
图4为本发明优选实施例的情绪调控系统进行情绪调控的流程图。Fig. 4 is a flow chart of emotion regulation by the emotion regulation system in a preferred embodiment of the present invention.
具体实施方式detailed description
本发明的优选实施例详述如下：Preferred embodiments of the present invention are described in detail as follows:
在本实施例中，参见图1～4，一种基于脑电反馈的情绪调控系统，其特征在于：包括信息采集模块1、信号处理控制模块2、反馈模块3、人机界面模块4、评价模块5和数据管理模块6，系统包括管理员与受试者两类用户，他们具有不同的权限。人机界面模块4包含通信连接参数设置功能、利用图片、声音或视频的情绪刺激显示功能和脑电活动特性显示功能，通信参数设置功能实现信息采集模块与服务器之间的连接参数的设置，仅允许管理员进行操作，利用图片、声音或视频的情绪刺激显示功能将情绪刺激呈现给受试者，作为受试者的认知目标，对于脑电活动特性显示功能模块，根据信号处理控制模块2计算得到脑电特征，将其以柱形图和脑电地形图的方式展现出来，此功能仅限管理员使用。信息采集模块1采用服务器-客户端的通信方式，以脑电信号采集系统作为服务器，以PC机作为客户端，来读取脑电信号数据，脑电信号采集系统通过人机界面模块4的通信参数设置控制信号连接，来启动实时采集脑电信号，信号处理控制模块2接收信息采集模块1输出的数据并进行预处理，通过计算脑电波的特征，以设定反馈阈值和情绪调控的指标，并输出到数据管理模块6，反馈模块3接收到信号处理控制模块2的加噪指令后，采用对人机界面模块4的情绪刺激进行加噪的方式，将加过噪声的情绪刺激反馈输出给人机界面4，使被试者接收反馈模块3输出的信息，实现情绪调控训练，反馈模块接收到信号处理控制模块的停止加噪指令后，则停止加噪，受试者通过评价模块5对情绪调控前后的情绪刺激进行效价评价和唤醒度评价，评价结果输出到数据管理模块6，数据管理模块6负责程序运行中数据的记录、保存和输出，包括记录信号处理控制模块2生成的反馈信号、情绪刺激呈现时刻、情绪刺激加噪时刻以及情绪刺激停止加噪时刻数据的记录和保存，管理人员能将保存后的数据打印输出。In this embodiment, referring to FIGS. 1 to 4 , an emotion regulation system based on EEG feedback is characterized in that it includes an information collection module 1, a signal processing control module 2, a feedback module 3, a man-machine interface module 4, an evaluation Module 5 and data management module 6, the system includes two types of users, administrators and subjects, who have different permissions. The man-machine interface module 4 includes a communication connection parameter setting function, an emotional stimulation display function using pictures, sounds or videos, and an EEG activity characteristic display function. The communication parameter setting function realizes the setting of connection parameters between the information collection module and the server. Allow administrators to operate, use the emotional stimulus display function of pictures, sounds or videos to present emotional stimuli to the subjects, as the cognitive goals of the subjects, for the display function module of brain electrical activity characteristics, according to the signal processing control module 2 Calculate the EEG characteristics and display them in the form of histograms and EEG topographic maps. This function is only available to administrators. The information acquisition module 1 adopts a server-client communication mode, uses the EEG signal acquisition system as the server, and uses the PC as the client to read the EEG signal data, and the EEG signal acquisition system passes the communication parameters of the man-machine interface module 4 Set the control signal connection to start the real-time collection of EEG signals, the signal processing control module 2 receives the data output by the information collection module 1 and performs preprocessing, and calculates the characteristics of the brain waves to set the feedback threshold and emotional regulation indicators, and output to the data management module 6, after the feedback module 3 receives the noise-adding instruction from the signal processing control module 2, it adopts the method of adding noise to the emotional stimulation of the man-machine interface module 4, and outputs the emotional stimulation with noise added to the human The machine interface 4 enables the subject to receive the information output by the feedback module 3 to realize emotional regulation training. After the feedback module receives the signal processing control module's stop noise instruction, it stops adding noise, and the subject evaluates the emotion through the evaluation module 5 Emotional stimuli before and after regulation are evaluated for potency and arousal, and the evaluation results are output to the data management module 6. The data management module 6 is responsible for recording, saving and outputting data during program operation, including recording the feedback signal generated by the signal processing control module 2. , Record and save the data at the time when the emotional stimulus is presented, the time when the emotional stimulus is added to noise, and the time when the emotional stimulus stops adding noise, and the management personnel can print out the saved data.
在本实施例中，参见图1～4，人机界面模块4的利用图片、声音或视频的情绪刺激显示功能显示输出的情绪刺激为情绪刺激图片。图片来自中科院心理健康重点实验室编制的中国情绪图片系统。In this embodiment, referring to FIGS. 1-4 , the emotional stimulation display function of the man-machine interface module 4 using pictures, sounds or videos displays and outputs emotional stimulations as emotional stimulation pictures. The picture comes from the Chinese Emotion Picture System compiled by the Key Laboratory of Mental Health, Chinese Academy of Sciences.
在本实施例中，参见图1～4，信号处理控制模块2首先根据被试者受刺激前的脑电特征来确定其脑电特征的初始阈值，然后在进行情绪调控时将被试者受刺激时的脑电特征数据与脑电特征的初始阈值进行比较，以确定是否控制反馈模块3进行后续的反馈。在信号处理控制模块2中，若脑电特征值高于初始阈值的30％，则向反馈模块3发送加噪指令，若低于初始阈值的90％，则向反馈模块3发送停止加噪指令。In this embodiment, referring to Figs. 1-4, the signal processing control module 2 firstly determines the initial threshold value of the EEG characteristics according to the EEG characteristics of the subject before being stimulated, and then controls the subject's EEG characteristics when regulating emotions. The EEG feature data during stimulation is compared with the initial threshold of the EEG feature to determine whether to control the feedback module 3 for subsequent feedback. In the signal processing control module 2, if the EEG characteristic value is higher than 30% of the initial threshold, a noise-adding instruction is sent to the feedback module 3, and if it is lower than 90% of the initial threshold, a noise-adding instruction is sent to the feedback module 3 .
在本实施例中，参见图1～4，在反馈模块3中，当接收到信号处理控制模块2的加噪指令后，则对图片进行加噪，使受试者接受反馈模块输出的信息，实现情绪调控训练，当接收到停止加噪指令后，则停止加噪，反馈结束。In this embodiment, referring to FIGS. 1-4, in the feedback module 3, after receiving the noise addition instruction from the signal processing control module 2, noise is added to the picture, so that the subject accepts the information output by the feedback module, Realize emotional regulation training, when receiving the stop noise instruction, stop adding noise, and the feedback ends.
在本实施例中，参见图1～4，进入正式调控之前，使用者先对所有刺激图片进行“效价评价”和“唤醒度评价”，分为5个等级，评分为1-5，系统记录每项评价得分，如图2。完成所有图片的评价后，使用者进入情绪调控部分，单个图片的调控流程参见图3，首先在人机界面模块4的电脑屏幕中央看到一张带“+”符号的空白图片，显示2秒钟，此时使用者处于静息状态。接着屏幕会显示负性图片，使用者对该图片进行认知重评，以降低其带来的情绪反应。此时系统会根据使用者脑电的变化情况判定是否对使用者进行反馈，若进行反馈，则显示加过噪声的负性图片。反馈结束后，电脑再次弹出“效价评价”和“唤醒度评价”图片，让使用者对之前看到的图片进行唤醒度和效价的评价，评价完毕，图片消失。接着进行下一张图片的调控。In this embodiment, referring to Figures 1-4, before entering the formal control, the user first conducts "potency evaluation" and "arousal evaluation" on all stimulus pictures, which are divided into 5 grades, with scores ranging from 1 to 5, and the system Record each evaluation score, as shown in Figure 2. After completing the evaluation of all pictures, the user enters the emotional control part. The control process of a single picture is shown in Figure 3. First, a blank picture with a "+" symbol is seen in the center of the computer screen of the human-machine interface module 4, and it is displayed for 2 seconds. clock, the user is in a resting state at this time. Then the screen will display a negative picture, and the user will cognitively re-evaluate the picture to reduce the emotional response it brings. At this time, the system will judge whether to give feedback to the user according to the change of the user's EEG. If feedback is given, it will display a negative image with noise added. After the feedback is over, the computer pops up the pictures of "Evaluation of Potency" and "Evaluation of Arousal" again, allowing users to evaluate the degree of arousal and valence of the pictures they saw before. After the evaluation, the pictures disappear. Then proceed to the control of the next picture.
整个系统的主要结构如图1所示，具体的反馈步骤如图4：The main structure of the whole system is shown in Figure 1, and the specific feedback steps are shown in Figure 4:
反馈模块的具体实施如下：The specific implementation of the feedback module is as follows:
步骤0：先由信号处理控制模块计算得出当前时刻的theta相对功率Eθ，以及使用者处于静息状态下基线的theta相对功率Ebase；Step 0: first calculate the relative theta power Eθ at the current moment by the signal processing control module, and the relative theta power Ebase of the baseline when the user is in a resting state;
步骤1：将两者大小进行比较，以决定是否进行反馈操作。若Eθ与Ebase的差高于Ebase的30％T1，转向步骤2；否则转向步骤3；Step 1: Compare the size of the two to decide whether to perform a feedback operation. If the difference between Eθ and Ebase is higher than 30% T1 of Ebase, go to step 2; otherwise go to step 3;
步骤2：对图片进行加噪；Step 2: add noise to the picture;
步骤3：显示当前图片；Step 3: Display the current picture;
步骤4：再次由信号处理控制模块计算当前时刻的Eθ；Step 4: Calculate the Eθ at the current moment by the signal processing control module again;
步骤5：比较Eθ与Ebase，Eθ与Ebase若的差不小于Ebase的10％T2，则返回步骤1；若Eθ与Ebase的差小于Ebase的10％，进入步骤6；Step 5: Compare Eθ and Ebase, if the difference between Eθ and Ebase is not less than 10% T2 of Ebase, return to step 1; if the difference between Eθ and Ebase is less than 10% of Ebase, go to step 6;
步骤6：要求被试对该图片的唤醒度和效价进行评价。Step 6: Ask the subjects to evaluate the arousal and valence of the picture.
在本实施例中，参见图1，整个系统包括信息采集模块1、信号处理控制模块2、反馈模块3、人机界面模块4、评价模块5以及数据管理模块6。使用者通过人机界面模块4观察负性图片，从而产生消极情绪，如悲伤，恐惧等；通过评价模块5对刺激图片进行效价和唤醒度的评价。系统通过信息采集模块1采集使用者实时的EEG信号，再通过信号处理控制模块2对EEG信号进行预处理，同时计算指定频带的功率，作为情绪调控的指标。在反馈模块3中，对信号处理控制模块2中计算的出的指标进行监控，当其超过一定阈值之后，系统判定使用者进行情绪调控，并将结果反馈给使用者，反馈的方式是对负性图片进行加噪，使其减弱对使用者的刺激。各模块设计与功能详情如下：In this embodiment, referring to FIG. 1 , the whole system includes an information collection module 1 , a signal processing control module 2 , a feedback module 3 , a man-machine interface module 4 , an evaluation module 5 and a data management module 6 . The user observes the negative pictures through the man-machine interface module 4, thereby generating negative emotions, such as sadness, fear, etc.; through the evaluation module 5, evaluates the potency and arousal degree of the stimulating pictures. The system collects the user's real-time EEG signal through the information collection module 1, then preprocesses the EEG signal through the signal processing control module 2, and calculates the power of the specified frequency band as an index of emotion regulation. In the feedback module 3, the indicators calculated in the signal processing control module 2 are monitored. When the indicators exceed a certain threshold, the system determines that the user has carried out emotion regulation, and the result is fed back to the user. Add noise to sexual pictures to reduce the stimulation to users. The design and function details of each module are as follows:
信息采集模块1：选用服务器/客户端的通信方式，由脑电信号采集系统作为服务器，采集脑电信号，由PC机作为客户端，读取脑电数据。Information acquisition module 1: choose the server/client communication mode, use the EEG signal acquisition system as the server to collect EEG signals, and use the PC as the client to read the EEG data.
信号处理控制模块2：主要负责对客户端接收到的数据进行处理，以提取反馈指标。具体包括信号的预处理和指定频带功率的计算，然后将提取的参数作为基线的阈值或者反馈阶段的实时数据对反馈模块进行驱动。Signal processing control module 2: mainly responsible for processing the data received by the client to extract feedback indicators. It specifically includes signal preprocessing and calculation of specified frequency band power, and then uses the extracted parameters as the baseline threshold or real-time data in the feedback stage to drive the feedback module.
反馈模块3：根据信号处理控制模块得到的实时数据和设定的反馈阈值，将结果反馈给被试。在本系统中，反馈的方式是根据反馈阈值对刺激图片进行加噪处理。Feedback module 3: Feedback the results to the subjects according to the real-time data obtained by the signal processing control module and the set feedback threshold. In this system, the way of feedback is to add noise to the stimulus picture according to the feedback threshold.
人机界面模块4：包含通信参数、按钮，刺激图片显示以及脑电频谱显示。Man-machine interface module 4: including communication parameters, buttons, stimulation picture display and EEG spectrum display.
评价模块5：包含调控前和调控后对刺激图片的效价评价和唤醒度评价，评价结果保存到数据管理模块。Evaluation module 5: Including the evaluation of the potency and arousal degree of the stimulation pictures before and after the regulation, and the evaluation results are saved to the data management module.
数据管理模块6：负责程序运行中数据的记录、保存和输出，这里包括反馈指标、图片呈现时刻，图片加噪时刻以及图片停止加噪时刻等数据的保存，管理人员可将保存后的数据打印输出。Data management module 6: Responsible for the recording, saving and output of data during program operation, including the storage of feedback indicators, picture presentation time, picture noise addition time, and picture stop noise addition time, etc. The management personnel can print the saved data output.
本实施例应用于情绪调控、电生理领域，使用脑电生物反馈技术进行情绪调控能力的训练。大脑具有可塑性，脑电可以反映大活动的瞬态变化，本实施例通过生物反馈方法进行大脑的情绪调节能力的训练，能实现提高受试者情绪调控能力的目的，使用本实施例脑电生物反馈系统，可以有效提高人们调节负性情绪的能力。This embodiment is applied to the fields of emotion regulation and electrophysiology, and uses EEG biofeedback technology to train emotion regulation ability. The brain has plasticity, and EEG can reflect the transient changes of large activities. This embodiment uses the biofeedback method to train the brain's emotion regulation ability, which can achieve the purpose of improving the subject's emotion regulation ability. The feedback system can effectively improve people's ability to regulate negative emotions.
上面结合附图对本发明实施例进行了说明，但本发明不限于上述实施例，还可以根据本发明的发明创造的目的做出多种变化，凡依据本发明技术方案的精神实质和原理下做的改变、修饰、替代、组合或简化，均应为等效的置换方式，只要符合本发明的发明目的，只要不背离本发明基于脑电反馈的情绪调控系统的技术原理和发明构思，都属于本发明的保护范围。The embodiments of the present invention have been described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned embodiments, and various changes can also be made according to the purpose of the invention of the present invention. The changes, modifications, substitutions, combinations or simplifications should be equivalent replacement methods, as long as they meet the purpose of the invention, as long as they do not deviate from the technical principle and inventive concept of the EEG feedback-based emotion regulation system of the present invention, they all belong to protection scope of the present invention.
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| CN201610909148.6ACN106267514B (en) | 2016-10-19 | 2016-10-19 | Feeling control system based on brain electricity feedback |
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| CN201610909148.6ACN106267514B (en) | 2016-10-19 | 2016-10-19 | Feeling control system based on brain electricity feedback |
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| CN201610909148.6AActiveCN106267514B (en) | 2016-10-19 | 2016-10-19 | Feeling control system based on brain electricity feedback |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107080546A (en)* | 2017-04-18 | 2017-08-22 | 安徽大学 | Electroencephalogram-based emotion perception system and method for environmental psychology of teenagers and stimulation sample selection method |
| CN108392201A (en)* | 2018-02-26 | 2018-08-14 | 广东欧珀移动通信有限公司 | Brain training method and relevant device |
| CN108494952A (en)* | 2018-03-05 | 2018-09-04 | 广东欧珀移动通信有限公司 | Voice communication processing method and relevant device |
| CN108648806A (en)* | 2018-07-06 | 2018-10-12 | 杭州赛翁思科技有限公司 | A kind of method and system of training user's Feeling control ability |
| CN108784692A (en)* | 2018-05-11 | 2018-11-13 | 上海大学 | A kind of Feeling control training system and method based on individual brain electricity difference |
| CN108806771A (en)* | 2018-05-25 | 2018-11-13 | 上海果效智能科技有限公司 | mental parameter processing method and system |
| CN109350051A (en)* | 2018-11-28 | 2019-02-19 | 华南理工大学 | Head wearable device for mental state assessment and adjustment and its working method |
| CN109589493A (en)* | 2018-09-30 | 2019-04-09 | 天津大学 | It is a kind of based on the attentional regulation method through cranium galvanic current stimulation |
| CN110464344A (en)* | 2019-08-16 | 2019-11-19 | 兰州大学 | The method for collecting the device of eeg signal acquisition and music and its playing music |
| CN111026265A (en)* | 2019-11-29 | 2020-04-17 | 华南理工大学 | A continuous labeling system and method for emotion labels based on VR scene video |
| WO2020100144A1 (en)* | 2018-11-15 | 2020-05-22 | The Medical Research, Infrastructure and Health Services Fund of the Tel Aviv Medical Center | Resilience training |
| CN111858696A (en)* | 2019-04-29 | 2020-10-30 | 哈曼国际工业有限公司 | Assess cognitive responses to over-the-air updates |
| CN113180669A (en)* | 2021-05-12 | 2021-07-30 | 中国人民解放军中部战区总医院 | Emotional regulation training system and method based on nerve feedback technology |
| CN115736954A (en)* | 2022-12-02 | 2023-03-07 | 深圳大学 | Emotion regulation and control training method based on electroencephalogram signals and related equipment |
| CN116077070A (en)* | 2023-01-17 | 2023-05-09 | 天之成科技(上海)有限公司 | Application system, method and electronic device based on brain-computer interface |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4928704A (en)* | 1989-01-31 | 1990-05-29 | Mindcenter Corporation | EEG biofeedback method and system for training voluntary control of human EEG activity |
| CN1581149A (en)* | 2004-03-25 | 2005-02-16 | 东南大学 | Method for constituting man-machine interface using humen's sentiment and sentiment variation information |
| CN201227465Y (en)* | 2008-06-03 | 2009-04-29 | 吴剑波 | Multi-path portable mental emotion adjustment and intelligence potential excitation device |
| CN101569778A (en)* | 2009-03-10 | 2009-11-04 | 深圳先进技术研究院 | Biofeedback simulation system and biofeedback simulation method |
| CN101822863A (en)* | 2010-01-28 | 2010-09-08 | 深圳先进技术研究院 | Emotion regulating device and method thereof |
| CN202236782U (en)* | 2011-08-30 | 2012-05-30 | 忽以阳 | Attention training instrument based on brain waves |
| CN102499677A (en)* | 2011-12-16 | 2012-06-20 | 天津大学 | Emotional state identification method based on electroencephalogram nonlinear features |
| CN102715911A (en)* | 2012-06-15 | 2012-10-10 | 天津大学 | Brain electric features based emotional state recognition method |
| CN102715902A (en)* | 2012-06-15 | 2012-10-10 | 天津大学 | Emotion monitoring method for special people |
| CN202505349U (en)* | 2012-03-02 | 2012-10-31 | 株式会社东芝 | Device for monitoring mood of patient in real time, X-ray computed tomography (CT) device and magnetic resonance imaging (MRI) device |
| CN203342164U (en)* | 2013-03-19 | 2013-12-18 | 北京思源佳创技术开发有限公司 | Intelligent feeding-back type relaxation training system |
| CN104434056A (en)* | 2013-09-17 | 2015-03-25 | 吕品 | Biological feedback system based on pulse waves |
| CN104983414A (en)* | 2015-07-13 | 2015-10-21 | 瑞声声学科技(深圳)有限公司 | Wearable device and user emotion sensing and regulating method thereof |
| CN105147282A (en)* | 2015-08-25 | 2015-12-16 | 上海医疗器械高等专科学校 | Cognitive disorder electroencephalogram recognition system |
| CN105395192A (en)* | 2015-12-09 | 2016-03-16 | 恒爱高科(北京)科技有限公司 | Wearable emotion recognition method and system based on electroencephalogram |
| CN105536118A (en)* | 2016-02-19 | 2016-05-04 | 京东方光科技有限公司 | Emotion regulation device, wearable equipment and cap with function of relieving emotion |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4928704A (en)* | 1989-01-31 | 1990-05-29 | Mindcenter Corporation | EEG biofeedback method and system for training voluntary control of human EEG activity |
| CN1581149A (en)* | 2004-03-25 | 2005-02-16 | 东南大学 | Method for constituting man-machine interface using humen's sentiment and sentiment variation information |
| CN201227465Y (en)* | 2008-06-03 | 2009-04-29 | 吴剑波 | Multi-path portable mental emotion adjustment and intelligence potential excitation device |
| CN101569778A (en)* | 2009-03-10 | 2009-11-04 | 深圳先进技术研究院 | Biofeedback simulation system and biofeedback simulation method |
| CN101822863A (en)* | 2010-01-28 | 2010-09-08 | 深圳先进技术研究院 | Emotion regulating device and method thereof |
| CN202236782U (en)* | 2011-08-30 | 2012-05-30 | 忽以阳 | Attention training instrument based on brain waves |
| CN102499677A (en)* | 2011-12-16 | 2012-06-20 | 天津大学 | Emotional state identification method based on electroencephalogram nonlinear features |
| CN202505349U (en)* | 2012-03-02 | 2012-10-31 | 株式会社东芝 | Device for monitoring mood of patient in real time, X-ray computed tomography (CT) device and magnetic resonance imaging (MRI) device |
| CN102715902A (en)* | 2012-06-15 | 2012-10-10 | 天津大学 | Emotion monitoring method for special people |
| CN102715911A (en)* | 2012-06-15 | 2012-10-10 | 天津大学 | Brain electric features based emotional state recognition method |
| CN203342164U (en)* | 2013-03-19 | 2013-12-18 | 北京思源佳创技术开发有限公司 | Intelligent feeding-back type relaxation training system |
| CN104434056A (en)* | 2013-09-17 | 2015-03-25 | 吕品 | Biological feedback system based on pulse waves |
| CN104983414A (en)* | 2015-07-13 | 2015-10-21 | 瑞声声学科技(深圳)有限公司 | Wearable device and user emotion sensing and regulating method thereof |
| CN105147282A (en)* | 2015-08-25 | 2015-12-16 | 上海医疗器械高等专科学校 | Cognitive disorder electroencephalogram recognition system |
| CN105395192A (en)* | 2015-12-09 | 2016-03-16 | 恒爱高科(北京)科技有限公司 | Wearable emotion recognition method and system based on electroencephalogram |
| CN105536118A (en)* | 2016-02-19 | 2016-05-04 | 京东方光科技有限公司 | Emotion regulation device, wearable equipment and cap with function of relieving emotion |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107080546A (en)* | 2017-04-18 | 2017-08-22 | 安徽大学 | Electroencephalogram-based emotion perception system and method for environmental psychology of teenagers and stimulation sample selection method |
| CN108392201A (en)* | 2018-02-26 | 2018-08-14 | 广东欧珀移动通信有限公司 | Brain training method and relevant device |
| CN108494952A (en)* | 2018-03-05 | 2018-09-04 | 广东欧珀移动通信有限公司 | Voice communication processing method and relevant device |
| CN108494952B (en)* | 2018-03-05 | 2021-07-09 | Oppo广东移动通信有限公司 | Voice call processing method and related equipment |
| CN108784692A (en)* | 2018-05-11 | 2018-11-13 | 上海大学 | A kind of Feeling control training system and method based on individual brain electricity difference |
| CN108806771A (en)* | 2018-05-25 | 2018-11-13 | 上海果效智能科技有限公司 | mental parameter processing method and system |
| CN108648806A (en)* | 2018-07-06 | 2018-10-12 | 杭州赛翁思科技有限公司 | A kind of method and system of training user's Feeling control ability |
| CN109589493A (en)* | 2018-09-30 | 2019-04-09 | 天津大学 | It is a kind of based on the attentional regulation method through cranium galvanic current stimulation |
| WO2020100144A1 (en)* | 2018-11-15 | 2020-05-22 | The Medical Research, Infrastructure and Health Services Fund of the Tel Aviv Medical Center | Resilience training |
| CN109350051A (en)* | 2018-11-28 | 2019-02-19 | 华南理工大学 | Head wearable device for mental state assessment and adjustment and its working method |
| CN109350051B (en)* | 2018-11-28 | 2023-12-29 | 华南理工大学 | Head wearable device for mental state assessment and adjustment and working method thereof |
| CN111858696A (en)* | 2019-04-29 | 2020-10-30 | 哈曼国际工业有限公司 | Assess cognitive responses to over-the-air updates |
| CN110464344A (en)* | 2019-08-16 | 2019-11-19 | 兰州大学 | The method for collecting the device of eeg signal acquisition and music and its playing music |
| CN111026265A (en)* | 2019-11-29 | 2020-04-17 | 华南理工大学 | A continuous labeling system and method for emotion labels based on VR scene video |
| CN113180669A (en)* | 2021-05-12 | 2021-07-30 | 中国人民解放军中部战区总医院 | Emotional regulation training system and method based on nerve feedback technology |
| CN113180669B (en)* | 2021-05-12 | 2024-04-26 | 中国人民解放军中部战区总医院 | Emotion adjustment training system and method based on nerve feedback technology |
| CN115736954A (en)* | 2022-12-02 | 2023-03-07 | 深圳大学 | Emotion regulation and control training method based on electroencephalogram signals and related equipment |
| CN116077070A (en)* | 2023-01-17 | 2023-05-09 | 天之成科技(上海)有限公司 | Application system, method and electronic device based on brain-computer interface |
| Publication number | Publication date |
|---|---|
| CN106267514B (en) | 2019-07-23 |
| Publication | Publication Date | Title |
|---|---|---|
| CN106267514A (en) | Feeling control system based on brain electricity feedback | |
| Li et al. | Emotion recognition using physiological signals | |
| CN105451801B (en) | Sound-induced sleep method and system therefor | |
| CN110947076B (en) | An intelligent brainwave music wearable device that can adjust mental state | |
| CN106725462A (en) | Acousto-optic Sleep intervention system and method based on EEG signals | |
| CN106407733A (en) | Depression risk screening system and method based on virtual reality scene electroencephalogram signal | |
| CN112163518B (en) | Emotion modeling method for emotion monitoring and emotion monitoring and adjustment system | |
| CN108784692A (en) | A kind of Feeling control training system and method based on individual brain electricity difference | |
| CN108721048B (en) | Computer-readable storage medium and terminal | |
| CN107402635B (en) | Mental health adjusting method and system combining brain waves and virtual reality | |
| CN102715902A (en) | Emotion monitoring method for special people | |
| CN109893093A (en) | A kind of state of consciousness detection system for implicitly watching brain-computer interface attentively | |
| CN110037696A (en) | EEG feedback system based on eye electric switch | |
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