scholarly journals Mental Task Recognition by EEG Signals: A Novel Approach with ROC Analysis

2018 ◽  
Author(s):  
Takashi Kuremoto ◽  
Masanao Obayashi ◽  
Shingo Mabu ◽  
Kunikazu Kobayashi
Keyword(s):  
Roc Analysis ◽  
Mental Task ◽  
Eeg Signals ◽  
Novel Approach ◽  
Task Recognition

scholarly journals A Novel Approach For Detection of Neurological Disorders through Electrical Potential Developed in Brain

2019 ◽  
Vol 9 (4) ◽  
pp. 2751
Author(s):  
Mohd Suhaib Kidwai ◽  
S. Hasan Saeed
Keyword(s):  
Neurological Disorders ◽  
Electrical Potential ◽  
Mathematical Concept ◽  
Recurrence Plots ◽  
Eeg Signals ◽  
Novel Approach ◽  
User Friendly

<p>This paper talks about the phenomenon of recurrence and using this concept it proposes a novel and a very simple and user friendly method to diagnose the neurological disorders by using the EEG signals.The mathematical concept of recurrence forms the basis for the detection of neurological disorders,and the tool used is MATLAB.  Using MATLAB, an algorithm is designed which uses EEG signals as the input and uses the synchronizing patterns of EEG signals to determine various neurological disorders through graphs and recurrence plots</p>

Mental task recognition based on SVM classification

2009 ◽  
Author(s):  
G. Costantini ◽  
D. Casali ◽  
M. Carota ◽  
G. Saggio ◽  
L. Bianchi ◽  
...  
Keyword(s):  
Mental Task ◽  
Svm Classification ◽  
Task Recognition

Keywords Recognition from EEG Signals on Smart Devices a Novel Approach

2021 ◽  
pp. 83-94
Author(s):  
Sushil Pandharinath Bedre ◽  
Subodh Kumar Jha ◽  
Prashant Borde ◽  
Chandrakant Patil ◽  
Bharati Gawali ◽  
...  
Keyword(s):  
Smart Devices ◽  
Eeg Signals ◽  
Novel Approach

scholarly journals Enhanced Template Matching Using Dynamic Positional Warping for Identification of Specific Patterns in Electroencephalogram

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Won-Du Chang ◽  
Chang-Hwan Im
Keyword(s):  
Template Matching ◽  
Pattern Analysis ◽  
Detection Accuracy ◽  
Eeg Signals ◽  
Artifact Detection ◽  
One Dimensional ◽  
Novel Approach ◽  
Conventional Methods ◽  
Electroencephalogram Eeg

Template matching is an approach for signal pattern recognition, often used for biomedical signals including electroencephalogram (EEG). Since EEG is often severely contaminated by various physiological or pathological artifacts, identification and rejection of these artifacts with improved template matching algorithms would enhance the overall quality of EEG signals. In this paper, we propose a novel approach to improve the accuracy of conventional template matching methods by adopting the dynamic positional warping (DPW) technique, developed recently for handwriting pattern analysis. To validate the feasibility and superiority of the proposed method, eye-blink artifacts in the EEG signals were detected, and the results were then compared to those from conventional methods. DPW was found to outperform the conventional methods in terms of artifact detection accuracy, demonstrating the power of DPW in identifying specific one-dimensional data patterns.

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