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Keyword: Electroencephalogram
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Open AccessArticle
8 Pages, 898 KB Download PDF

Electroencephalogram Based Medical Biometrics using Machine Learning: Assessment of Different Color Stimuli

Advances in Science, Technology and Engineering Systems Journal, Volume 6, Issue 3, Page # 27–34, 2021; DOI: 10.25046/aj060304
Abstract:

A methodology of medical signal-based biometrics has been proposed in this paper for implementing a human identification system controlled by electroencephalogram in respect of different color stimuli. The advantage of biosignal based biometrics is that they provide more efficient operation in simple experimental condition to ensure accurate identification. Red, Green, Blue (primary colors) and Yellow…

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(This article belongs to the SP10 (Special Issue on Multidisciplinary Sciences and Engineering 2020-21) & Section Biomedical Engineering (EBI))
Open AccessArticle
4 Pages, 717 KB Download PDF

An Electroencephalogram Analysis Method to Detect Preference Patterns Using Gray Association Degrees and Support Vector Machines

Advances in Science, Technology and Engineering Systems Journal, Volume 3, Issue 5, Page # 105–108, 2018; DOI: 10.25046/aj030514
Abstract:

This paper introduces an electroencephalogram (EEG) analysis method to detect preferences for particular sounds. Our study aims to create novel brain–computer interfaces (BMIs) to control human mental (NBMICM), which are used to detect human mental conditions i.e., preferences, thinking, and consciousness, choose stimuli to control these mental conditions, and evaluate these choices. It is important…

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(This article belongs to the SP5 (Special Issue on Multidisciplinary Sciences and Engineering 2018) & Section Artificial Intelligence in Computer Science (CAI))
Open AccessArticle
9 Pages, 962 KB Download PDF

Development of an EEG Controlled Wheelchair Using Color Stimuli: A Machine Learning Based Approach

Advances in Science, Technology and Engineering Systems Journal, Volume 6, Issue 2, Page # 754–762, 2021; DOI: 10.25046/aj060287
Abstract:

Brain-computer interface (BCI) has extensively been used for rehabilitation purposes. Being in the research phase, the brainwave based wheelchair controlled systems suffer from several limitations, e.g., lack of focus on mental activity, complexity in neural behavior in different conditions, and lower accuracy. Being sensitive to the color stimuli, the EEG signal changes promises a better…

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(This article belongs to the SP10 (Special Issue on Multidisciplinary Sciences and Engineering 2020-21) & Section Bioinformatics (BIF))
Open AccessArticle
8 Pages, 985 KB Download PDF

Diagnosis of Tobacco Addiction using Medical Signal: An EEG-based Time-Frequency Domain Analysis Using Machine Learning

Advances in Science, Technology and Engineering Systems Journal, Volume 6, Issue 1, Page # 842–849, 2021; DOI: 10.25046/aj060193
Abstract:

Addiction such as tobacco smoking affects the human brain and thus causes significant changes in the brainwaves. The changes in brain wave due to smoking can be identified by focusing on changes in electroencephalogram pattern, extracting different time-frequency domain features. In this aspect, a laboratory-based study has been presented in this paper, for assessing the…

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(This article belongs to the SP10 (Special Issue on Multidisciplinary Sciences and Engineering 2020-21) & Section Bioinformatics (BIF))
Open AccessArticle
7 Pages, 1,571 KB Download PDF

Human Emotion Recognition Based on EEG Signal Using Fast Fourier Transform and K-Nearest Neighbor

Advances in Science, Technology and Engineering Systems Journal, Volume 5, Issue 6, Page # 1082–1088, 2020; DOI: 10.25046/aj0506131
Abstract:

Human emotional states can transform naturally and are recognizable through facial expressions, voices, or body movements, influenced by received stimuli. However, the articulation of emotions is not practicable by every individual, even when feelings of joy, sadness, or otherwise are experienced. Biomedically, emotions affect brain wave activities, as the continuously functioning brain cells communicate through…

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(This article belongs to the SP9 (Special Issue on Multidisciplinary Innovation in Engineering Science & Technology 2020) & Section Biomedical Engineering (EBI))
Open AccessArticle
11 Pages, 2,323 KB Download PDF

Design of an EEG Acquisition System for Embedded Edge Computing

Advances in Science, Technology and Engineering Systems Journal, Volume 5, Issue 4, Page # 119–129, 2020; DOI: 10.25046/aj050416
Abstract:

The human brain is one of the most complex machines on the planet. Being the only method to get real-time data with high temporal resolution from the brain makes EEG a highly sought upon signal in the neurological and psychiatric domain. However, recent developments in this field have made EEG more than just a tool…

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(This article belongs to the SP9 (Special Issue on Multidisciplinary Innovation in Engineering Science & Technology 2020) & Section Bioinformatics (BIF))
Open AccessArticle
7 Pages, 812 KB Download PDF

Discriminant Analysis of Diminished Attentiveness State Due to Mental Fatigue by Using P300

Advances in Science, Technology and Engineering Systems Journal, Volume 4, Issue 6, Page # 108–114, 2019; DOI: 10.25046/aj040613
Abstract:

Fatigue is broadly divided into two types depending on the content of a task: physical fatigue and mental fatigue. Mental fatigue is associated with human error. It is thus important to search for indicators that can easily evaluate mental fatigue. The aim of this study is to construct a system that can evaluate mental fatigue…

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(This article belongs to the SP8 (Special Issue on Multidisciplinary Sciences and Engineering 2019-20) & Section Psychiatry (PSY))
Open AccessArticle
8 Pages, 908 KB Download PDF

Investigating The Detection of Intention Signal During Different Exercise Protocols in Robot-Assisted Hand Movement of Stroke Patients and Healthy Subjects Using EEG-BCI System

Advances in Science, Technology and Engineering Systems Journal, Volume 4, Issue 4, Page # 300–307, 2019; DOI: 10.25046/aj040438
Abstract:

Improving the hand motor skills in post-stroke patients through rehabilitation based on movement intention derived signals from the brain in conjunction with robot-assistive technologies are explored. The experimental work is conducted using Electroencephalogram based Brain-Computer Interface (EEG-BCI) system and the AMADEO hand rehabilitation robotic device. Two protocols using visual-cues and then using a 2-Dimensional (2D)…

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(This article belongs to the SP7 (Special Issue on Advancement in Engineering and Computer Science 2019) & Section Biomedical Engineering (EBI))
Open AccessArticle
9 Pages, 1,039 KB Download PDF

Dysphoria Detection using EEG Signals

Advances in Science, Technology and Engineering Systems Journal, Volume 4, Issue 4, Page # 197–205, 2019; DOI: 10.25046/aj040424
Abstract:

Dysphoria is a state faced when one experienced disappointment. If it is not handled properly, dysphoria may trigger acute stress, anxiety and depression. Typically, the individual who experienced dysphoria are in-denial because dysphoria is always being associated with negative connotations such as incompetency to handle pressure, weak personality and lack of will power. To date,…

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(This article belongs to the SP7 (Special Issue on Advancement in Engineering and Computer Science 2019) & Section Psychiatry (PSY))

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