0% Complete
فارسی
Home
/
دوازدهمین کنفرانس بین المللی فناوری اطلاعات و دانش
Classification of mental states of human concentration based on EEG signal
Authors :
Mehran Safari Dehnavi
1
Vahid Safari Dehnavi
2
Masoud Shafiee
3
1- دانشگاه آزاد اسلامی واحد نجف آباد
2- دانشگاه صنعتی امیرکبیر
3- دانشگاه صنعتی امیرکبیر
Keywords :
EEG signal, machine learning methods, classification.
Abstract :
This paper provides a suitable method for classifying the EEG signal. In this article, a number of features are extracted from the EEG signal and by using these different features and networks, these signals are classified into three categories: relaxation, moderate concentration and high concentration. In this case, based on the amount of mental activity that has a direct effect on the EEG signal, the state of attention can be categorized. In this paper, four sensors (electrodes) are used to collect the voltage of the brain signals, then the Large Laplacian Filter is used to localize the signals, and by this method, the signals of the four sensors are converted into one signal, then the frequency of 50 Hz (City frequency) is removed using a Notch passive filter and then a wavelet filter is used to remove noise and artifacts. In this article, the diagnosis of mental states in the time domain is examined. Then, a window is determined on the measured signal and in these windows, various features are extracted and by using these features and machine learning methods, different mental states are categorized. Finally, the method used is tested on the data set and the results of the method is checked. One of the advantages of the proposed method is to reduce the number of network inputs based on PCA feature reduction method, which leads to a reduction in network volume, which is especially important in neural networks. In this article, we have tried to increase the accuracy of classification by using various features.
Papers List
List of archived papers
Presenting an Edge-based Air Quality Management System for Smart City Scenarios
Tina Samizadeh Nikoui - Ali Balador - Amir Masoud Rahmani - Hooman Tabarsaied
A Joint Trajectory and Energy Harvesting Method for an UAV Enabled Disaster Response Network
Hosein Mohammadi Firozjae - Javad Zeraatkar Moghaddam - Mehrdad Ardebilipour
طبقه بندی روش های شناسایی داده های تکراری در جهت تسهیل فرایند پاکسازی داده ها
مهدی جعفری - احمد عبدالله زاده بار فروش
روشی برای تشخیص مرحله پیشرفت آلزایمر در تصاویرFMRI مبتنی بر شبکه های عصبی چگال
فرساد زمانی بروجنی - عباس بهره دار
Short-Term Traffic Flow Prediction Based on a Recurrent Deep Neural Networks: Study in Tehran
Dr Monireh عبدوس - Taha Vajed Samei
Benchmarking Embedding Models for Persian-Language Semantic Information Retrieval
Mahmood Kalantari - Mehdi Feghhi - Nasser Mozayani
Vi-Net: A Deep Violent Flow Network for Violence Detection in Video Sequences
Tahereh Zarrat Ehsan - Seyed Mehdi Mohtavipour
ارائه راهکاری جهت مقابله با حملات DoS در شبکه های نرم افزارمحور
ویدا هاشمی - احمد بختیاری شهری - رضا جاویدان
ساخت پیکره برچسب خورده گزارش های آسیب شناسی
مسلم سمیعی پاقلعه - مهرنوش شمس فرد
Presentation of a New Decoder Based on Quantum Cellular Automata Technology Along with an Analysis of Energy Consumption
- - -
more
Samin Hamayesh - Version 42.0.3