Bci competition dataset in Feature Weighting and Regularization of Common Spatial Patterns in EEG-Based Motor Imagery BCI The goal of the "BCI Competition" is to validate signal processing and classification methods for Brain-Computer Interfaces (BCIs). The BCI competition fosters algorithmic solutions, which allow for a single-trial assessment of mental states. BCI Competition III: Download area Data Set I from Tübingen (description) training data: [ Matlab format (117 MB) ] [ ASCII format (117 MB) ] test data: [ Matlab format (43 MB) ] [ ASCII format (37 MB) ] all inclusive: [ gdf format (139 MB) ] The explanation of the ASCII format is here. Things that are implemented in this repo: Common Spatial Pattern algorithm with One-Versus-Rest version for multiclass; Filter Bank using Chevbychev passband filters; Dataloader for BCI Competition IV 2a dataset; Baseline model (CNN + LSTM) based on this paper This is a python code for extracting EEG signals from dataset 2b from competition iv, then it converts the data to spectrogram images to classify them using a CNN classifier. Contribute to hehichens/BCI development by creating an account on GitHub. Each session is comprised of 6 runs separated by short Sep 27, 2021 · This short video shows how one can import the popular BCI competition IV dataset from Matlab into the MNE-Python environment. BCI competition IV 公共数据集 Data sets 2b，是基于视觉诱发的左右手运动想象的脑电数据集。该数据集采集了9名右利手、视力正常或达到矫正后正常的实验者的 脑电信号 作为数据集。 对受试者要求： Dec 2, 2024 · 目录BCI competition IV Data Set 2b数据集介绍数据采集 本分享为脑机学习者Rose整理发表于公众号：脑机接口社区(微信号：Brain_Computer). BCIs have been extended beyond communication and control over the years. The explanation of the GDF format is here. Each session consists of six runs, and each run consists of 48 trials, 12 for each of the four classes (right-hand, feet, left-hand, tongue). 5k次。论文：EEG-TCNet: An Accurate Temporal Convolutional Network for Embedded Motor-Imagery Brain–Machine Interfaces数据：The BCI Competition IV-2a dataset数据描述请到官网环境win10，pycham2020. The goal of the "BCI Competition III" is to validate signal processing and classification methods for Brain-Computer Interfaces (BCIs). Nov 22, 2016 · BCI Competition Datasets Introduced by Mishuhina et al. mat-A09E. 8647 in datasets 2a and 2b of BCI Competition IV, respectively. Jun 30, 2004 · The performance of the proposed method on the BCI Competition III dataset II and the BCI competition II dataset II, the state-of-the-art dataset, was evaluated and compared with previous studies. Leeb, G. Brunner, R. Brunner , G. 9GB. The goal of the "BCI Competition IV" is to validate signal processing and classification methods for Brain-Computer Interfaces (BCIs). The organizing committee of the competition received many inquiries from the participants through e-mail. Sep 1, 2023 · The experiments results on BCI Competition IV datasets 2a and 2b and the OpenBMI dataset demonstrated the promising effectiveness of the proposed shallow mirror transformer. de/competition/iii / 第四届BCI大赛数据集： https://www. Dec 30, 2024 · The model was provided with a detailed prompt to explore advancements in EEG-based motor imagery classification within the context of Brain-Computer Interfaces (BCIs) using the BCI Competition IV 2a dataset Brunner et al. A Kind Request It would be very helpful for the potential organization of further BCI competitions to get some feedback, criticism and suggestions, about this competition. Pfurtscheller1 1Institute for Knowledge Discovery, Graz University of Technology, Austria 2Institute for Human-Computer Interfaces, Graz University of Technology, Austria Experimental paradigm Feb 6, 2012 · The proposed method was evaluated using the BCI Competition IV Dataset I (Blankertz et al. L. Compared to the past BCI Competitions, new challanging problems are addressed that are highly relevant for practical BCI systems, such as session-to-session transfer Versions of datasets 2-4 in ASCII format will be provided soon. also past) samples must not be used in order to guarantee a fast response times of the system, although for the competition test data set averaging over more samples could be of benefit. In all three datasets, proposed multi-class approach outperformed common binary-classification-based approach in the same conditions. The dataset is collected in two separate sessions BCI competition iv dataset 2a; Four class problem. To this end, the user usually performs a boring calibration measurement before starting with BCI feedback applications. [ dataset 1 | dataset 2a | dataset 2b | dataset 3 | dataset 4 | The announcement and the data sets of the BCI Competition IV can be found here. 2w次，点赞5次，收藏34次。目录BCI competition IV Data Set 2b数据集介绍数据采集本分享为脑机学习者Rose整理发表于公众号：脑机接口社区(微信号：Brain_Computer). Arguments: BCI Competition IV Dataset 2a Brain-computer interfacing (BCI) is an approach to establish a novel communication channel from men to machines. BCI Competition 2008 – Graz dataset A个人翻译(附MATLAB Jun 21, 2018 · BCI Competition Dataset IV 2a 数据集的经典使用场景主要集中在脑机接口（BCI）领域，特别是在运动想象（Motor Imagery）任务的分类与识别中。 该数据集包含了9名受试者在执行四种不同运动想象任务（左手动、右手动、双脚动、舌头动）时的脑电信号数据。 For the assessment, we used an open-access dataset, BCI competition IV dataset 2a. com/berdakh/mne- Jun 24, 2024 · In our study, we primarily utilized the BCI Competition IV dataset 2a (BCI-2a) for training and evaluating the EEGEncoder model. Fig. de Dowload raw dataset from. zip (1. Contribute to shirindora-old/process_BCI_IV_2b development by creating an account on GitHub. zip_BCI2008竞赛数据_BCI竞赛数据_bci 2008_脑电_ 07-15 总之，2008年 BCI 竞赛 数据集 为研究者提供了宝贵的资源，通过MATLAB进行处理，可以深入探索 脑 电 图信号的奥秘，推动 脑机接口 技术的进步。 Data sets 1 ‹motor imagery, uncued classifier application› Data sets provided by the Berlin BCI group: Berlin Institute of Technology (Machine Learning Laboratory) and Fraunhofer FIRST (Intelligent Data Analysis Group) (Klaus-Robert Müller, Benjamin Blankertz, Carmen Vidaurre, Guido Nolte), and Campus Benjamin Franklin of the Charité - University Medicine Berlin, Department of Neurology Oct 25, 2024 · BCI Competition IV Dataset 2b是由国际脑机接口竞赛（BCI Competition）于2008年发布的数据集，由德国柏林工业大学和瑞士苏黎世联邦理工学院的研究团队共同创建。该数据集的核心研究问题集中在脑机接口（BCI）系统中，特别是针对运动想象任务的脑电图（EEG）信号分类。 Dec 11, 2023 · 前言 本文是在结合了官方的英文介绍以及各大佬的讲解之后，根据我的个人理解整理出的关于BCICIV 2a数据集的简介，如有错误还请指正。相关链接如下：数据集下载链接(. 1-6, 2008. mat文件版本)官方介绍文档(PDF) Feb 5, 2012 · The proposed method was evaluated using the BCI Competition IV Dataset I (Blankertz et al. 2 This competition aimed to find out whether a test was related to the motor imaging of the left hand (Class 1) or the motor imaging of the right hand (Class 2). Contribute to hisunjiang/Public-datasets-of-BCI development by creating an account on GitHub. Introduction. BCI competition III: dataset II- ensemble of SVMs for BCI P300 speller. This data set poses the challenge of getting along with only a little amount of training data. Other (i. Schlögl, and G. Jan 14, 2021 · 文章浏览阅读4. BCI Competition 2008 – Graz dataset A个人翻译(附MATLAB安装BioSig) qq_37378157: 同学你好，我们可以交流一下吗. 74. data_path in main_csp and main_riemannian. Compared to the past BCI Competitions, new challanging problems are addressed that are highly relevant for practical BCI systems, such as classification of continuous EEG without trial structure (data sets 1). 1. In addition, we propose a novel model, called M–ShallowConvNet, which solves the existing problems. Mar 6, 2024 · The proposed model out performs the current state-of-the-art techniques in the BCI Competition IV-2a dataset with an accuracy of 85. 12. Yang, J. QQ交流群：941473018 BCI competition IV Data Set 2b BCI competition IV 公共数据集 Data sets 2b，是基于视觉诱发的左右手运动想象的脑电数据集。 This is a repository for BCI Competition 2008 dataset IV 2a fixed and optimized for python and numpy. BCI technology is used to date primarily for intentional control. This dataset is related with motor imagery. Dec 4, 2020 · BCI Competition 2008 – Graz dataset A个人翻译(附MATLAB安装BioSig) 钟你: 你好，你找到这个数据集了嘛？可以发我一份嘛. Python toolbox for Brain-Computer Interfacing (BCI) - wyrm/examples/BCI Competition 3, Data Set 2 (P300 Speller). Li, Y. Leeb 1, C. 7. de/competition/ii/ 第三届BCI大赛数据集： https://www. The proposed model achieves the accuracies of 0. [A P300 detection algorithm based on F-score feature selection and support vector machines]. Sheng Wu Yi Xue Gong Cheng Xue Za Zhi, 25:23-26, Feb 2008. gdf文件版本)数据集下载链接(. Includes movements of the left hand,the right hand, the feet and the tongue. A few computer-generated artificial data were also present in the dataset, though they are not considered both in this study and in the competition. 友情链接： 加州大学圣迭戈分校认知神经科学实验室 中国科学院半导体研究所 BCI Society 中国生物医学工程学会 地址：清华大学医学院C253 邮箱：wuhaolin@tsinghua. Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Oct 25, 2024 · 脑机接口（BCI）技术在神经科学和康复医学领域具有重要应用。BCI Competition III Dataset III由2004年举办的第三届国际脑机接口竞赛中发布，由柏林工业大学和柏林夏里特医学院共同贡献。该数据集旨在推动脑机接口技术的发展，特别是针对运动想象任务的分类问题。 Jun 8, 2020 · 文章浏览阅读1. All data sets in this database are open access. This study employs the BCI Competition IV 2a dataset from Graz University of Technology . de/competition/iv/ 2、2020年国际BCI First, download the source code. IEEE Trans Biomed Eng, 55:1147-1154, Mar 2008. Data were acquired from nine subjects, and two sessions were recorded for each subject. The 2020 international BCI competition aimed to provide high-quality neuroscientific data for open access that could be used to evaluate the current degree of technical advances in BCI. 2020 International BCI Competition Mar 28, 2012 · The performances of the algorithms were evaluated on BCI Competition IV (Tangermann et al. Associated to this BCI paradigm, there is the problem of classifying electroencephalogram signals related to responses to some visual stimuli. Jan 3, 2025 · BCI-Competition-IVa-dataset-2数据集广泛应用于脑机接口（BCI）领域的研究，特别是在基于脑电信号（EEG）的运动想象分类任务中。 该数据集通过提供多通道EEG信号及其对应的标签，为研究者提供了一个标准化的测试平台，用于开发和验证新的信号处理和机器学习算法。 BCI Competition IV-2a: 22-electrode EEG motor-imagery dataset, with 9 subjects and 2 sessions, each with 288 four-second trials of imagined movements per subject. Performances of our algorithm have been evaluated on dataset II of the BCI Competition III and has yielded the best performance of the competition. That is only a "port" of the original dataset, I used the original GDF files and extract the signals and events. Yao, and X. The trials were recorded using 22 EEG electrodes at a sampling rate of 250 Hz. ipynb on the filtered datasets Sep 20, 2023 · 目录BCI competition IV Data Set 2b数据集介绍数据采集 本分享为脑机学习者Rose整理发表于公众号：脑机接口社区(微信号：Brain_Computer). See a full comparison of 3 papers with code. **Understand the Dataset**: Familiarize yourself with the structure and contents of the dataset. Schl ogl2, and G. 9k次，点赞20次，收藏58次。BCI竞赛数据集下载及其测试集标签的方法基于EEG信号P300 speller模式识别项目，在BCI竞赛iii官网下载数据集&测试集的方法_手机bci数据在哪里查 Dataset IIa from BCI Competition 4 . https://github. . Although Jun 30, 2020 · BCI competition IV Data Set 2b BCI competition IV 公共数据集 Data sets 2b，是基于视觉诱发的左右手运动想象的脑电数据集。 该数据集采集了9名右利手、视力正常或达到矫正后正常的实验者的脑电信号作为数据集。 Aug 1, 2023 · Proposed approach is evaluated with three public datasets, BCI competition II, BCI competition III and the BNCI Horizon. 8164 and 0. bbci. BCI Competition III. _bci iv 2b Aug 24, 2022 · BCI competition IV Data Set 2b. This paper presents a review of new frontiers regarding brain-computer interface (BCI) technology and discusses the current BCI technology levels based on the challenges presented in the 2020 international BCI competition. txt. As experienced already in prior competitions not only scientists from the The well-known BCI Competition IV 2a dataset is used to train and evaluate models. BCI Competition IV Dataset 2a数据集的构建基于脑机接口（BCI）领域的国际竞赛IV，旨在提供一个标准化的数据集以评估和比较不同的BCI算法。 该数据集收集了来自9名受试者的脑电图（EEG）数据，每位受试者在四种不同的实验条件下执行任务。 2020 International BCI competition dataset Hosted on the Open Science Framework OSF HOME. Additionally, if there is an associated publication, please make sure to cite it. State-of-the-art performance was achieved on a publicly available BCI competition IV dataset 4 with a correlation coefficient between true and predicted trajectories up to 0. The task in this competition is to use Oct 25, 2024 · BCI Competition IV Dataset 1 数据集的构建基于脑机接口（BCI）领域的国际竞赛IV，旨在提供一个标准化的数据平台，以评估和比较不同BCI算法的性能。 该数据集收集了来自多名受试者的脑电图（EEG）信号，这些信号在受试者执行特定任务时记录。 文章浏览阅读6. You need to read the original paper here Popular public datasets of BCI. Each classifier is composed of a linear support vector machine trained on a small part of the available data and for which a channel selection procedure has been performed. The existing open-access datasets from past competitions mostly deal with healthy individuals' data, while the major application area of BCI is in the clinical domain. , 2012) Dataset 2a and Dataset 2b. - Ahmed-Habashy/Datase All the data used in the codes was earlier bandpassed filtered in MATLAB with a 2nd order Butterworth Filter from 0. This means that you can freely download and use the data according to their licenses. 4 MB) If you used the dataset in your work, please cite the original paper of it: C. Prediction of Finger Flexion IV Brain-Computer Interface Data Competition The goal of this dataset is to predict the flexion of individual fingers from signals recorded from the surface of the brain (electrocorticography The task in this competition is to use the provided flexion information in order to predict finger flexion for a provided test set. Brain-computer interface P300 speller aims at helping patients unable to activate muscles to spell words by means of their brain signal activities. It will remain private for the next competition. SMR_BCI: SMR-BCI dataset- Two class motor imagery (002-2014), BCIC2a: BCI Competition IV 2a dataset- Four class motor imagery (001-2014), OpenBMI: OpenBMI dataset. This data set consists of EEG data from 9 subjects. cn Special attention has been given to the state-of-the-art studies on deep learning for EEG-based BCI research in terms of algorithms. The presented method provides the opportunity for developing fully-functional high-precision cortical motor brain-computer interfaces. Dataset Description This data set consists of EEG data from 9 subjects. . Jan 25, 2023 · 文章浏览阅读1. m filtering file on the dataset obtained from the link for the BCI COmpetition Dataset Run the file BCI_III_DS_2_TestSet_PreProcessing. 1-30 Hz Run the . Includes movements of the left hand, the right hand, the feet and the tongue. 9安装包：C:\Users\Administrator>pip listPackage . Electroencephalogram data from four datasets (BCI Competition IV dataset 2a, 2b and two self-acquired datasets) were segmented into four types of the time window and had features extracted by In the field of brain-computer interface (BCI) research, the availability of high-quality open-access datasets is essential to benchmark the performance of emerging algorithms. Oct 25, 2024 · BCI Competition IV Dataset 4由国际脑机接口竞赛（BCI Competition）组织于2008年发布，由柏林工业大学和图宾根大学的研究团队共同开发。 该数据集收集了来自健康受试者和脑卒中患者的脑电图（EEG）数据，旨在评估和比较不同BCI系统的性能。 Feb 15, 2008 · Brain-computer interface P300 speller aims at helping patients unable to activate muscles to spell words by means of their brain signal activities. 48% and 76. Next, we will provide a comprehensive explanation of the DL techniques employed for the classification of MI tasks. Then provide the average of 8 consecutive samples (so that to get a BCI Competition 2008 { Graz data set B R. Dataset Description. , 2012). Specically, we introduces a number of advanced deep learning algorithms and frameworks aimed at several major issues in BCI including robust brain signal representation learning, cross-scenario classification, and semi-supervised classification. Aug 31, 2019 · BCI competition 2008 dataII. edu. e. OSFHOME; 2020 International BCI Competition. Public. ipynb at master · bbci/wyrm Aug 2, 2023 · 前言： 好的，这篇开始，我们首先以08年bci国际大赛4分类运动想象的数据作为入门项目，本篇讲的是该数据集的预处理工程，bci领域有很多研究方向的数据，比如运动想象，睡眠，癫痫，眼动，肌电等等，而我是比较推荐把该数据作为入门的数据，官方介绍简单易懂，并且做的是分类。 Dataset Description This data set consists of EEG data from 9 subjects. Prediction of Finger Flexion IV Brain-Computer Interface Data Competition The goal of this dataset is to predict the flexion of individual fingers from signals recorded from the surface of the brain (electrocorticography (ECoG)). The organizers are aware of the fact that by such a competition it is impossible to validate BCI systems as a whole. The BCI competition IV stands in the tradition of prior BCI competitions that aim to provide high quality neuroscientific data for open access to the scientific community. Thus the newly proposed algorithms to enhance the BCI Competition II: Download area Data from Tübingen: data set Ia: a34lkt/Traindata_0. Artifact removal from EEG data is done through preprocessing, followed by feature extraction for recognizing discriminative information in the recorded brain signals. 1% for new subjects and existing subjects, respectively, which were highest among the compared Oct 10, 2024 · 运动想象二分类(left hand, right hand)，源自2008 BCI Competition IV dataset 2b，含 gdf 数据和 mat 数据两种格式 数据官网：http://bbci. This is a repository for BCI Competition 2008 dataset IV 2a fixed and optimized for python and numpy. Two sessions on different days were recorded for each subject. , 2007), which was recorded from 4 human subjects performing motor imagery tasks. Please send e-mail to access the data before using our codes. Feb 26, 2025 · This would download runs 6, 10, and 14 (hand/foot motor imagery) runs from subjects 1 and 2 in the EEGBCI dataset to “~/datasets” and prompt the user to store this path in the config (if it does not already exist). 97% for the subject-dependent and subject-independent modes, respectively. This paper addresses the problem of signal responses variability within a single subject in such brain Jul 8, 2022 · The BCI competition datasets have been used commonly to evaluate proposed model performance 12,13; however, recently, datasets with a large number of participants have growing attention as In this paper, we highlight potential problems that might arise in ShallowConvNet and investigate the potential solutions. 2python版本：Python 3. <Code> Process dataset 2b from BCI competition IV. Jan 15, 2022 · The proposed method incorporates the XGBO algorithm for feature selection and the random forest for the classification of EEG signals. Muller-Putz , A. The cue-based BCI paradigm consisted of four different motor imagery tasks, namely the imagination of movement of the left hand (class 1), right hand (class 2), both feet (class 3), and tongue (class 4). BCI competition IV Data Set 2b. Müller-Putz, A. QQ交流群：941473018 BCI competition IV Data Set 2b BCI competition IV 公共数据集 Data sets 2b，是基于视觉诱发的左右手运动想象的脑电数据集。 Oct 30, 2024 · BCI Competition IV Dataset 3a，作为脑机接口（BCI）领域的重要数据集，由2008年举办的第四届BCI竞赛中发布。 该数据集由柏林工业大学和柏林夏里特医学院的研究团队共同创建，旨在推动脑电图（EEG）信号处理和分类技术的发展。 The goal of the "BCI Competition IV" is to validate signal processing and classification methods for Brain-Computer Interfaces (BCIs). However, this type of comparison can identify the level and direction of the development of BCIs by study groups using common comparators. Jul 21, 2024 · The BCI competition IV is a benchmark dataset in the field of brain and human computer interfaces. The cue-based BCI paradigm consisted of four different motor imagery tasks, namely the imag- ination of movement of the left hand (class 1), right hand (class 2), both feet (class 3), and tongue (class 4). 以上是BCI Competition IV 2a数据集项目的目录结构、启动文件和配置文件的介绍。希望这份文档能帮助你更好地理解和使用该项目。 bcidatasetIV2a This is a repository for BCI Competition 2008 dataset IV 2a fixed May 1, 2024 · The BCI Competition IV dataset 2a (BCI IV 2a) is a publicly available multi-class MI dataset containing EEG recordings of 9 participants during imagination movements of left hand, right hand, both feet, and tongue (Tangermann et al. Four class motor imagery (001-2014) Jan 17, 2024 · To utilize the BCI Competition 2008–Graz dataset A for your research or analysis, you can follow these general steps: 1. QQ交流群：941473018BCI competition IV Data Set 2bBCI competition IV 公共数据集 Data sets 2b，是基于视觉诱发的左右手运动想象的脑电数据集。 Jan 1, 2022 · We used BCI Competition IV 2b dataset available on the BCI competition website. Put all files of the dataset (A01T. The potency of the proposed system was investigated using two public EEG datasets (BCI Competition III dataset IIIa and dataset IVa). But nevertheless we envision interesting contributions to ultimately improve the full BCI. R. 目前网络上公开的数据集有三个，分别为第二、三和四届BCI数据集，具体获取方式如下： 第二届BCI大赛数据集： https://www. 38% and 70. 5 MB) data set Ia: a34lkt/Traindata_1. The brain-computer interface (BCI) has been investigated as a form of communication tool between the brain and external devices. After discussion by committee members, we decided not to open the label for the test dataset to the public. BNCI 2014-001 Motor Imagery dataset Dataset IIa from BCI Competition 4 [1]. 2 Keywords: brain-computer interface (BCI), electroencephalogram, competition, open datasets, neural decoding. The BCI-2a dataset comprises recordings from nine subjects across two sessions, with each subject performing 288 motor imagery trials. Pfurtscheller, "BCI Competition 2008–Graz data set A," Institute for Knowledge Discovery (Laboratory of Brain-Computer Interfaces), Graz University of Technology, vol. 4 shows the time schedule of BCI IV 2a dataset. The crucial idea is to directly tap the communication at its very origin: the human brain. This data set contains brain signals from three subjects, as well as the time courses of the flexion of each of five fingers. Data Set II The current state-of-the-art on BCI Competition IV 2a is ATCNet: Atention temporal convolutional network. mat) into a subfolder within the project called 'dataset' or change self. May 1, 2020 · BCI Competition IV-2a: 22-electrode EEG motor-imagery dataset, with 9 subjects and 2 sessions, each with 288 four-second trials of imagined movements per subject. Then, download the dataset "Four class motor imagery (001-2014)" of the BCI competition IV-2a. Raw signals: Compute vectors 16 times per second using the last second of data. 16, pp. BCI competition IV 公共数据集 Data sets 2b，是基于视觉诱发的左右手运动想象的脑电数据集。该数据集采集了9名右利手、视力正常或达到矫正后正常的实验者的脑电信号作为数据集。 对受试者要求： Apr 18, 2024 · In this section, we will begin with an overview of the dataset used in this study. Sep 8, 2023 · The proposed framework is tested on BCI Competition IV dataset 1 and BCI Competition III dataset 4a. Wu. This paper addresses the problem of signal responses variability within a single subject in such brain Jul 22, 2022 · Using competition datasets to compare and evaluate various researchers' BCI decoding performance has not been easily achieved in BCI studies. The experimental paradigm involved Beginner friendly EEG dataset. The shallow mirror transformer obtained average accuracies of 74. One important objective in BCI research is to reduce the time needed for the initial measurement. During the competition, only the class labels for the training data were provided while the class labels for the evaluation data were disclosed only after the competition results have been announced. The goal of the "BCI Competition IV" is to validate signal processing and classification methods for Brain-Computer Interfaces (BCIs). For the neurosciences, such developments in signal processing and machine learning are clearly relevant as these single-trial data analysis methods provide a possibility to monitor the acting and behaving brain. EEG data were collected from nine people using three bipolar electrodes at a sampling rate of 250 Hz. 9w次，点赞51次，收藏161次。本文结合官方英文介绍及大佬讲解，整理了bciciv 2a数据集简介。该数据集由9名受试者的eeg数据组成，用于四种运动想象任务分类。 The goal of the "BCI Competition II" is to validate signal processing and classification methods for Brain Computer Interfaces (BCIs). kkt lqqev cxy ksxcvb ovtt ijlz zsi ghxrjvc bzz cebttej armev lhulo gctkna gukr sbykg