Reprinted from: Science and Technology Financial Times | 2019-7-12

It is difficult to quit drugs. The difficulty is that drugs can cause disorders of people's brain nerve function. Any information about drugs such as images, words, and even sounds will cause the damaged brain of drug addicts to instantly lose judgment and produce uncontrollable relapses. Impulses. To prevent relapse, we must start by saving the damaged brain. On July 9th, the expert demonstration meeting of the “Anti-Relapse Brain Function Training System” project, guided by the Office of the Zhejiang Provincial Drug Control Commission and developed by Hangzhou Seventh Technology Co., Ltd., was held in Hangzhou. It was well received by the review expert group and recommended for promotion and application in drug rehabilitation work.

Seventh's anti-relapse brain function training system is divided into two parts: hardware equipment and software system. The hardware equipment includes an intelligent all-in-one machine and a Shen Nian EEG helmet. The software system includes an EEG challenge module, a drug addiction assessment system, a brain function training module, an anti-relapse training module, and a training report.

Wu Xuanchen, the technical leader of Seventh Company, introduced that the system is based on the goal management theory in clinical brain science, and uses event-related logic to analyze EEG signals to design detoxification courses.

The system uses cutting-edge brain-computer interface equipment to record the electrophysiological signals generated during brain operation and apply the signals to a variety of drug rehabilitation training. The purpose is to enhance the self-regulation ability of drug rehabilitation personnel, thereby effectively reducing the relapse caused by impaired cognitive function, and opening a new type of motivation for drug rehabilitation personnel to take the initiative to detoxify.Scientific and effective means of detoxification and rehabilitation.

After the drug rehabilitation students wear the EEG helmet, they log in on the smart all-in-one machine, obtain customized courses and conduct training through the cloud server. The EEG helmet records and feeds back the brainwave signals of drug rehabilitation personnel in training in real time, generates a report and prints it on the smart all-in-one machine after the course is completed, and uploads the course record to the cloud server. The training data of drug rehabilitation personnel is statistically and analyzed on the cloud server, and the results are used to iterate the content of the training course.

The anti-drug department of Yueqing City is one of the pilot application units of the project. There, 31 drug addicts have used the system, of which 29 have not relapsed for more than a year. The practical effect surprised the managers of the anti-drug department. At the same time, the system can help anti-drug personnel to have an intuitive judgment on the depth of drug addiction of drug users, and can be managed separately according to the other party's situation, which is conducive to the development of anti-drug work. Feedback from the relevant departments of Lishui City, after the training of the system, the management personnel found that after seeing and hearing information about drugs, drug addicts will not have the uncontrollable desire to take drugs as before, but will have a short pause, giving the brain the possibility of analysis and judgment, so as to exercise self-control. “Now there are people who have taken drugs and their families have offered to use this system. ”

The clinical test results show that the system can effectively improve the level of attention function of drug rehabilitation personnel, reduce the possibility of their urge to find drugs, enhance self-control, and improve the cognitive level of drug rehabilitation personnel.

After demonstration, the review expert group believes that the anti-relapse brain function training system includes the main functions of management, training, evaluation, and multiple interactive feedback. Based on the multi-interactive feedback model, it provides a standardized anti-relapse plan for drug rehabilitation personnel, and provides targeted training and management data for community drug rehabilitation managers.It is used for community drug rehabilitation and community rehabilitation.