126 results about "Drug addicted" patented technology

The invention provides a method for rapidly identifying monoacetylmorphine and morphine in hair. The method sequentially comprises the following steps: 1, placing hair to be detected, an extract liquid, internal standard morphine-d3 and a billiard ball in a crusher, and carrying out micro-crushing treatment; 2, centrifuging a mixture obtained after the micro-crushing treatment; and 3, taking the supernatant of the centrifuged mixture, and carrying out liquid chromatography-tandem mass spectrometry analysis of the supernatant. The method for rapidly identifying monoacetylmorphine and morphine in hair can realize the simple and rapid separation and purification of monoacetylmorphine and morphine molecules in a complex biological matrix, has the advantages of strong specificity, strong selectivity and high sensitivity, can be used for detecting a practical drug addict hair sample, and can also be used for identifying and detecting heroin addict related cases in the forensic toxicological analysis field.

Disclosed is a detection method for rapidly screening out drug addicts. The method can rapidly screen out drug addicts independently or jointly according to electroencephalogram features and pupil dynamic change features of people to be detected responding to illumination and light offset. The detection method for rapidly screening out the drug addicts is easy and convenient to operate, the obtained result is rapid and accurate, and the method has the good accuracy and practicability.

Methods for screening specific biological endpoints that can be utilized to identify potential therapeutic agents for METH addiction. In one aspect of the invention, the methods involve reversal of behavioral sensitization and / or conditioned place preference in an animal previously treated with METH in the presence of a known amount of a 5-HT2A / 2C antagonist or a selective 5-HT2C antagonist, and reversal of the electrophysiological endpoints in a METH-treated animal in the presence of a known amount of the 5-HT2A / 2C antagonist or the selective 5-HT2C antagonist. Therapeutic treatment methods for reversing the set of biological endpoints that change in the METH drug addict using mirtazapine, SDZ SER 082, and related serotonin antagonists are also provided. The methods of the invention may be utilized in the identification of potential new therapies for multiple drugs of abuse.

The invention relates to a method for quickly screening benzedrine drugs and morphine drugs in hair on the spot. The method sequentially comprises the following steps of step 1, placing the hair to be detected, and grinding media together in a grinding tube of a crusher, and performing grinding and pulverizing treatment for the first time in the grinding tube of the crusher; step 2, after the grinding is performed for the first time, adding a solvent to the grinding tube, dissolving the hair in the grinding tube, and performing grinding and pulverizing treatment for the second time in the grinding tube of the crusher; and step 3, taking liquid in the grinding tube after the grinding and pulverizing treatment is performed for the second time, performing detection on a corresponding colloidal gold plate, and displaying a screening result. Through the adoption of the method disclosed by the invention, the simple, convenient, quick and on-the-spot operation of screening the drugs in the hair can be realized; the method is high in specificity, high in selectivity, and high in sensitivity, and can be applied to screening the hair of actual drug addicts, and can be applied to the field of forensic toxicological analysis, and the screening and solving of relevant cases.

The invention discloses a liquid atomized device and usage as suction toxicant exposure device, which comprises the following parts: accumulator, catheter, liquid adjustment valve, sprayer, air compression pump and air compressor conduit, wherein the big droplet collection cup is set in front of sprayer, whose bottom connects the big droplet reflux pipe to build a specific liquid foggy environment; the spray sensor can be set in the spray chamber, which accomplishes the self-control of liquid foggy quantity through connecting the signal amplifier with adjustment valve controller. The invention can be an experimental device to test animal suction toxicant exposure or other exposures, which collects large droplet in the accumulator to circulate.

The invention discloses a VR closed-loop drug addiction self-control force training system. The system comprises an addiction degree evaluation module, an electroencephalogram motor imagery modeling module and a closed-loop feedback training module, wherein the addiction degree evaluation module collects near-infrared data according to an experimental paradigm, analyzes the near-infrared data, divides addicts into mild addicts, moderate addicts and severe addicts, and selects three difficulty levels according to the addiction degree; the electroencephalogram motor imagery modeling module recognizes motor imagery tasks of the left hand, the right hand and the two feet and controls operation of a mountaineering racing bicycle in a VR model; a VR training scene is designed into a mountaineering racing bicycle, corresponding difficulty levels are selected according to different addiction levels, and people can conduct racing-bicycle mountaineering by means of motor imagery and self-controlforce; and the closed-loop feedback training module collects electroencephalogram information of drug addicts in game control in real time and displays the electroencephalogram information on a PC, and data changes on the PC feeds back whether the game control is correct or not in real time and remind the drug addicts to focus on motor imagery. By means of the system and a method, self-control force and attention of drug addicts are trained.

The present invention relates to a system for combating the psychological craving for drugs of new drug addicts. The system is characterized in that it includes a viewing device based on panoramic technology and an electrocardiometer, and the addict wears the viewing device and the electrocardiometer to monitor the HRV value of the addict; Panoramic technology watches drug use scenes and hears the sound effects of drug use props; the addict uses virtual reality technology to watch drug-related disgust scenes and hear complication-related sound effects through virtual reality technology, using its enhanced The immersive experience presents audio-visual content that induces addicts' memory of drug use, and achieves the purpose of extracting drug-related memory.

The invention provides a non-contact rapid detection system and method for drug addicts. The detection system comprises a camera device and a processing apparatus connected with the camera device, wherein the camera device is arranged on a security inspection machine or in front of the security inspection machine and an access control system, and the detection system can also be used as a portablehandheld device. The human face can be identified and detected according to image information acquired by the camera device, the eye positions of a detected person can be located, pupil dynamic imagedata is collected for a period of time (1-2 seconds) to obtain various data such as the pupil P value, the R value, the T value and the Q value to be compared with data of normal people and drug addicts, and whether or not the detected person is a non-drug user is judged. According to the system and the method, identification and detection can be completed efficiently without contact, networkingreporting can be achieved, and a comprehensive technical support is provided for supervising, controlling and screening drug-related person of relevant departments. The detection rate is high, the detection can be completed within 2-3 seconds, the equipment cost is low, the equipment structure is small and exquisite, and detection and identification results are precise and reliable.

The invention relates to a self-service station for drug maintenance therapy of drug addicts under control to give up their habits. Terminal equipment is arranged in an equipment room. The equipment room is provided with a door lock. An entrance guard controller is connected with the door lock. A room entering identity detecting device is connected with a monitoring center. The monitoring center compares stored identity identification information with the identity identification information which is acquired by the room entering identity detecting device. If the stored identity identification information is same with the acquired identity identification information, the monitoring center controls a first entrance guard controller for unlocking the door lock. A witness database homogeneity verifying system of the terminal equipment verifies the identity of the drug addict under control to give up the habit. An IC card reader reads an IC card. A drug supplying device supplies the drug to the drug addict. The drug supplying device comprises a drug drinking cup dispensing assembly, a conveying assembly for conveying drug drinking cups, a drug liquid storage container, and a drug liquid peristaltic pump which pumps the drug liquid into the drug drinking cups for drinking by the drug addict. The self-service station can realize change from original face-to-face treatment to self-service backend centralized treatment service, thereby facilitating drug maintenance therapy of the drug addict, reducing treatment cost, realizing time saving and labor saving in treatment, and reducing operation cost reduction of a treatment station.

The invention discloses a drug retaking prognosis method of a drug addict. The method comprises the steps that a plurality of pictures related to drugs and pictures unrelated to the drugs are collected; a plurality of addicts under drug treatment are selected to conduct grading on the selected pictures, so that the pictures related to the drugs and the pictures unrelated to the drugs are selected;the attentional bias and implicit association of an addict to be prognosed are tested by means of the pictures; based on the test results, the drug retaking probability of the addict to be prognosedis predicted. According to the method, the attentional bias and implicit association of the addict to be prognosed are tested, so that the drug retaking probability of the addict to be prognosed is predicted and prognosed based on the test results; therefore, the drug retaking probability of the addict can be prognosed, moreover, prognosis is scientific and accurate, and the theoretical property is high.

The invention discloses a method for detecting GABA, Glu, DA, 5-HT and amphetamine type stimulants from serum. The method comprises steps as follows: S1: preparation of a standard liquid: GABA, Glu, DA, 5-HT and amphetamine type stock solutions, standard curve working solutions and quality control working solutions are prepared, and an internal standard compound stock solution and a working solution are prepared; S2: treatment of blank serum samples and a drug addict serum sample: the standard curve working solutions or the quality control working solutions of GABA, Glu, DA, 5-HT and amphetamine type compounds are added to the blank serum samples respectively, then a trichloroacetic acid containing Glu-d5 and a acetonitrile solution containing DA-d4 and Amp-d6 are added sequentially, vortex shocking and centrifugation are performed, and supernatants are sucked for testing; except addition of the standard curve working solutions or quality control working solutions, an unknown biological sample is subjected to the treatment manners the same as above; S3: liquid chromatograph-mass spectrometer detection: the supernatants prepared in the S2 are detected; S4: drawing of standard curves. The method has the characteristics of convenience in operation, high efficiency and practicability.

The invention discloses a drug addict screening method based on IPPG. The method comprises the steps of collecting or recognizing a face video image, extracting an effective frame image containing faces, extracting a face ROI from the frame image, extracting an IPPG signal from the face ROI, and performing enhancement and noise reduction combined treatment on the IPPG signal to obtain a clean pulse wave signal. Pulse wave characteristic parameters and physiological index data are obtained by analyzing and processing the pulse wave signal, then the pulse wave characteristic parameters and the physiological index data are compared with a model constructed by an existing sample database, the drug taking condition of a detected person is judged, and besides, detection data is automatically stored in the database to supplement and perfect the model. According to the drug addict screening method based on IPPG disclosed by the invention, the drug addict screening period can be effectively prolonged, the influence of the metabolic period is reduced, the detection efficiency and convenience are improved, the economic benefit is increased, and the problems of personnel mismatch, sampling infection hidden danger, biological sample pollution and the like possibly existing in a traditional screening manner are solved.

The invention relates to medicine maintenance treatment equipment for drug addicts under drug rehabilitation. A control mainframe of the equipment is connected with a cloud server, and a human, identity card and database identity verification system, an IC card reader and a medicine supply device are connected with the control mainframe. The human, identity card and database identity verification system is used for verifying identities of the drug addicts under drug rehabilitation; the IC card reader is used for reading IC cards of the drug addicts under drug rehabilitation; the medicine supply device is used for supplying medicines to the drug addicts under drug rehabilitation and comprises a medicine taking cup distribution component, a conveying component, a liquid medicine storage container and a liquid medicine peristaltic pump. The medicine taking cup distribution component is used for distributing medicine taking cups; the conveying component is capable of conveying the medicine taking cups; the liquid medicine storage container is used for storing liquid medicine; the liquid medicine peristaltic pump is used for pumping the liquid medicine from the liquid medicine storage container into the medicine taking cups to allow the drug addicts under drug rehabilitation to acquire the liquid medicine from a liquid medicine supply port. The medicine maintenance treatment equipment for drug addicts under drug rehabilitation has advantages that original face-to-face treatment is changed into self-service backend centralized treatment service, convenience is provided for medicine maintenance treatment of the drug addicts under drug rehabilitation, treatment cost is reduced, time saving and labor saving in treatment are realized, and operating cost of treatment sites can be reduced.

The invention discloses a big data-based abnormal behavior prediction system for forcibly isolating drug rehabilitation personnel. The system comprises a data acquisition unit, a data storage unit, adata analysis unit and a data application unit, The data acquisition unit is used for acquiring data information of the compulsory isolation drug rehabilitation personnel from a business system and asecurity system of the compulsory isolation drug rehabilitation station; The data analysis unit performs model learning according to the data information of the known personnel to obtain a learning model, and utilizes the learning model to predict the abnormal behavior of the to-be-predicted personnel to obtain a prediction result; And the data application unit is used as a related response according to the prediction result. According to the method, the behavior feature integrated learning model is constructed based on the big data, so that accurate prediction and alarming are carried out onabnormal behaviors of the forced isolation drug rehabilitation personnel, occurrence of the abnormal behaviors of the forced isolation drug rehabilitation personnel is effectively prevented, and the safety protection and personnel supervision level of the forced isolation drug rehabilitation personnel are improved.

The present invention is quick identification method of the addiction and dependence of opium drug addict, and belongs to the field of medicine and biotechnology. Naloxone eye drop in 2 or 3 drops is dripped into the eye of drug addict, and after 10-40 min, the pupil diameter is measured and compared with that before naloxone is dripped. The addiction and dependence on opium drug is judged based on the diameter difference, and the difference over 5 pixels shows the existing addiction, and the difference of 5-10, 11-20 and over 21 shows the slight, middle and serious dependence separately. The said method is efficient, accurate and reliable.

The invention discloses a police conversation speech recognition method and system based on big data. The method comprises the steps of completing identity provisioning of a talker and a person to betalked and parameter setting of audio collecting equipment, completing control of the audio collecting equipment, and automatically generating a talking file catalogue; showing the recognition text contents of talking speech displayed in real time by a talking interface display window, and saving talking speech files and text files; analyzing the talking speech through big data, designing a mentalstate evaluation list, analyzing the mental state index of a talking target, and generating a big data analysis report; and enabling the talking speech files and the text files to be related to the inner part of a judicial system, and completing sharing of the talking speech files and the text files. According to the police conversation speech recognition method and system, the working strength of working police is alleviated, the working efficiency is improved, through the big data analysis method, the mental state of drug addicts under control to give up their habits is analyzed, and support can be provided for increment of the education level of the drug addicts under control to give up their habits.

The invention discloses a device and a method for nervous system data acquisition of drug addicts. The device comprises a flexible pressure sensor module, a gait information acquisition module, a display module, a voice module, a drug addiction induction module, a drug abstinence person information management system, a gait test system and a gait analysis system; the output of a flexible pressuresensor and the output of the gait information acquisition module are connected with the gait test system, the gait test system, the control voice module, the display module and the drug addiction induction module are used for executing corresponding instructions, collecting relevant data for preprocessing, and acquired data is obtained.

The invention discloses a drug addict screening method based on pulse waves. The screening method comprises the steps that 1, a pulse wave collection device is adopted for collecting pulse waves of anaddict to be detected first; 2, pulse wave parameters are obtained by processing the pulse waves, and a characteristic variability pattern of the addict to be detected is obtained, and the characteristic variability pattern of the pulse waves is calculated, wherein the pulse wave parameters comprise total pulse wave pulse period time and pulse wave conduction time parameters; 3, judgment is conducted by using a big data model based on the parameters. The drug addict screening method based on the pulse waves lowers the detection cost, simplifies the detection process of drug addicts, shortensthe detection time of the drug addicts and improves the detection successful rate of the drug addicts.

The invention discloses a Chinese medicament capable of giving up drug addiction. The Chinese medicament is prepared from the following raw materials by weight: 1 to 15 grams of amber, 0.5 to 2 grams of tuckahoe, 5 to 20 grams of cinnabar, 2.5 to 30 grams of platycladi seed, 8 to 18 grams of milkwort, 1 to 3 grams of poppy and 1 to 5 grams of hawthorn; and the Chinese medicament is prepared by adding 3 to 8 jin of water, decocting for 20 minutes and filtering to obtain liquor. The medicaments in the formula are common medicaments and are low in price, so economic burden is not brought to families of drug addicts; the Chinese medicament is convenient and easy to prepare, and is prepared by adding the water and decocting for a moment; the drug addiction can be thoroughly given up; and the drug addicts do not feel pain when the drug addiction is given up.

The invention relates to a medicine supplying device of medicine maintenance therapy equipment for drug addicts under control to give up drug habits. A first driving motor of a medicine drinking cup providing assembly can drive cup separating wheels to rotate through a first transmission mechanism; the cup separating wheels are used for supporting a medicine drinking cup pile to be provided; during rotating, the cup separating wheels are separated from a medicine drinking cup at the bottommost layer and are used for bearing the medicine drinking cup at an upper layer, so that the medicine drinking cup at the bottommost layer is driven to fall from a cup providing hole; a second driving motor of a transmission assembly is used for driving a manipulator to move through a second transmission mechanism; after the medicine drinking cup falling down from the medicine providing hole is taken by the manipulator at a cup receiving position, the manipulator can move to a medicine drinking position and transmit the medicine drinking cup to the medicine drinking position; and a liquid medicine peristalsis pump can inject liquid medicines stored in a liquid medicine storage container to the medicine drinking cup transmitted to the medicine drinking position to allow the drug addicts under control to give up drug habits to drink. Through the adoption of the medicine supplying device disclosed by the invention, the medicine maintenance therapy equipment for drug addicts under control to give up drug habits can conveniently, quickly and automatically feed medicines for the drug addicts under control to give up drug habits.

The invention provides a drug addict pupil detector with high-precision detection rate. The pupil detector includes a detection device housing, a camera lens cone and a stimulating lens cone. The camera lens cone includes an eye lens, a camera and a control circuit, wherein the camera is installed on the tail portion, and the control circuit is connected with the camera. A weak light emitting device is installed behind the eye lens in the camera lens cone and connected with the control circuit. A light emitting device with a weak light source is installed on the rear portion of the eye lens, weak light appears in a dark detection environment, the instinct of the human eyes is to look at what can be seen, the weak light emitting device makes the eyeballs not move in the dark environment, the steady state of watching is kept, and it is thus ensured that the pupil detection process can be smoothly performed. Weak light does not interfere collection of the pupil characteristics, the special brightness and wavelength of the weak light can not stimulate the mood of a person to be detected and makes the person keep quiet and peaceful, the collection of pupil characteristics is facilitated, and finally the accuracy and reliability of the detection are improved.

The invention provides a drug taking propagation prediction method and device and electronic equipment, and relates to the technical field of data processing. The method comprises the following stepsof: obtaining parameter values, wherein the parameter values comprise conversion parameters of pre-divided different types of crowds, a number of relatives and friends corresponding to a single drug addict and number initial values of the different types of crowds, and the conversion parameters comprise conversion speeds or conversion probabilities between the different types of crowds; and calculating numbers of the different types of crowds in a preset time on the basis of a pre-established drug taking propagation model according to the parameter values, wherein the different types of crowdscomprise a relative and friend crowd, a drug addict crowd, an isolated crowd and a rehabilitation crowd. According to the method and device and the electronic equipment, drug taking propagation conditions are reasonably predicted, so that data reference and decision making basis are provided for drug control actions, benefit is brought to seek effective blocking strategies, resources are reasonably utilized, the strategies are reasonably adjusted, and social behavior intervention actions can be developed more effectively.

The invention provides a prediction method and device for information of a drug addict and computing equipment. The method comprises the steps of obtaining an original data set about a target crowd; wherein the original data set comprises a personnel basic information table and a personnel behavior record table; constructing a prediction sample set comprising at least one prediction sample based on the original data set; wherein one prediction sample is determined according to the personnel identity and a first preset time period, and each prediction sample comprises characteristics extractedbased on basic information of corresponding personnel and behavior information of the corresponding personnel in the corresponding first preset time period; and inputting the prediction sample set into a trained drug addict prediction model, obtaining a target probability of drug taking of the corresponding person after the first preset time period predicted by the model, and outputting the targetprobability. According to the technical scheme, the defects in the prior art can be overcome, prediction of the drug addict is achieved on the basis of big data, the whole process saves time and labor, and the prediction efficiency is very high.

The invention discloses a morphine detection method based on a SPR technique. The method comprises the following steps: coupling a SPR chip with an amino group on BSA through a EDC / NHS activated carboxyl group and then taking the SPR chip as a sensing chip, and when a to-be-detected sample passes by the surface of the sensing chip, utilizing a surface plasma resonance detector to detect the change in light intensity of the total reflected light at an interface of to-be-detected saliva and a molecular recognition sensitive chip so as to directly determine the morphine content in saliva. The method provided by the invention is high in detection sensitivity, is capable of greatly reducing the loss rate of drug addict detection and increasing the working efficiency and has an important application value.

The invention provides a drug addict rehabilitation evaluation system and method based on a portrait label. The system comprises an evaluation demand selection module, a scale extraction module, a rehabilitation scheme recommendation module, an evaluation information collection module, an evaluation result processing module, an evaluation scale database used for storing multiple evaluation scales,a rehabilitation scheme database used for storing multiple care schemes, and a portrait label system comprising a scale label system based on evaluation scale database labeling and a care scheme label system based on rehabilitation scheme database labeling and realizing association of a scale label and a rehabilitation scheme label. The system is advantaged in that labeling of the evaluation process is realized, periodic evaluation of a drug addict in the evaluation process is performed, an evaluation record analysis report can be generated, and quantification and rehabilitation of the long-term care effect of the drug addict are facilitated.

The invention provides a method and a device for evaluating drug addiction degree of drug addict on the basis of built-in test. The evaluation method comprises the following steps that a display areais arranged, and is divided into two sub-display areas; (2) a first sighting mark is displayed in the display area, and a drug addict watches the first sighting mark; (3) scenes containing drugs and scenes without drugs are displayed in the two sub-display regions respectively, at random, and simultaneously; (4) a sight tracking module is used for respectively recording the time of the drug addictwatching the sub-display area having drug scenes and the time of the drug addict watching the sub-display area without drug scenes; (5) single-factor variance analysis is carried out on the time of the drug addict watching the two sub-display areas, and the drug addiction degree of the drug addict can be judged. The invention further provides a device applying the method. The evaluation method and device can effectively evaluate the drug addiction degree of drug addicts.

The invention discloses a drug addiction degree detection method, a computer system is used for drug addiction degree detection, and an adopted detection system is composed of a behavioristics module,a drug addiction stimulation module, a data acquisition module, a CNN model establishment module, a CNN classification module and a result evaluation module. The method comprises the following operation steps: 1) collecting behavioral indexes; 2) stimulating the response of drug addicts to drugs; 3) collecting near-infrared data; and 4) establishing a CNN model. 5) performing CNN classification;and 6) evaluating a result. The method solves the problem that the addiction degree of the drug addiction personnel can only be defined according to artificial subjective factors. According to the method, the artificial intelligence method is used for classifying physiological data of mild, moderate and severe drug addiction personnel, and the average accuracy is 75%. According to the method, drugaddiction degree definition is more objective and standardized, and drug rehabilitation and rehabilitation trend is more scientific, reasonable and humanized.

The invention relates to the technical field of big data analysis, in particular to a risk assessment method and a system for forcibly isolating drug addicts. The method comprises the steps of forminga forced isolation drug addiction treatment personnel risk assessment label by drug addiction treatment management personnel for the sample data of the forced isolation drug addiction treatment personnel and the risk assessment data screened by the user portrait label; inputting the user portrait label of each forced isolation drug abstinence person in the training set and the user portrait labelof each forced isolation drug abstinence person in the test set into a LightGBM classification model; and when the classification accuracy and the recall rate meet set values, obtaining a standard LightGBM classification model, and obtaining a risk assessment result of the to-be-assessed forced isolation drug abstinence person through the standard LightGBM classification model. The method can effectively predict and prevent the occurrence of abnormal behaviors of forced isolation drug addicts, and provides decision support for the implementation of supervision in the later period.

The invention provides a method for identifying suspected drug addicts, a device for identifying suspected drug addicts and a storage medium. The method comprises an acquisition step and a detection step. According to the acquisition step, a to-be-processed face image img is acquired. According to the detection step, a trained deep neural network model is adopted to identify the to-be-processed face image img; and if a probability value output by the neural network is greater than a threshold value, it is determined that a person corresponding to the face image is a suspected drug addict. According to the method of the invention, drug addicts are identified through facial features. According to the method, the device and the storage medium of the invention, a deep learning technology is utilized; a special deep neural network algorithm is designed; a large number of face pictures of drug addicts and non-drug addicts are used to train the neural network algorithm, so that the algorithmcan learn the difference between the facial features of the drug addicts and non-drug addicts; and the weight of the neural network algorithm is solidified, so that the algorithm can extract the facial features of people in a targeted mode and can classify the facial features so as to identify whether one person is suspected to addict drugs or not, and identification is convenient and fast.