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Çaglar Uyulan, David Mayor, Tony Steffert, Tim Watson and Duncan Banks
The field of signal processing using machine and deep learning algorithms has undergone significant growth in the last few years, with a wide scope of practical applications for electroencephalography (EEG). Transcutaneous electroacupuncture stimulation ...
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Sriniketan Sridhar, Anibal Romney and Vidya Manian
Mild Cognitive Impairment (MCI) and Alzheimer?s Disease (AD) are frequently associated with working memory (WM) dysfunction, which is also observed in various neural psychiatric disorders, including depression, schizophrenia, and ADHD. Early detection of...
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Diba Das, Mehdi Hasan Chowdhury, Aditta Chowdhury, Kamrul Hasan, Quazi Delwar Hossain and Ray C. C. Cheung
The electrooculogram (EOG) is one of the most significant signals carrying eye movement information, such as blinks and saccades. There are many human?computer interface (HCI) applications based on eye blinks. For example, the detection of eye blinks can...
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Feng Tian, Yan Zhang and Yingjie Li
Focusing on virtual reality (VR) and film cutting, this study compared and evaluated the effect of visual mode (2D, VR) and cutting rate (fast, medium, slow) on a load, to make an attempt for VR research to enter the cognitive field. This study uses a 2 ...
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Rania Alhalaseh and Suzan Alasasfeh
Many scientific studies have been concerned with building an automatic system to recognize emotions, and building such systems usually relies on brain signals. These studies have shown that brain signals can be used to classify many emotional states. Thi...
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Markus-Oliver Tamm, Yar Muhammad and Naveed Muhammad
Imagined speech is a relatively new electroencephalography (EEG) neuro-paradigm, which has seen little use in Brain-Computer Interface (BCI) applications. Imagined speech can be used to allow physically impaired patients to communicate and to use smart d...
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Firgan Feradov, Iosif Mporas and Todor Ganchev
There is a strong correlation between the like/dislike responses to audio?visual stimuli and the emotional arousal and valence reactions of a person. In the present work, our attention is focused on the automated detection of dislike responses based on E...
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Antonio Quintero-Rincón, Valeria Muro, Carlos D?Giano, Jorge Prendes and Hadj Batatia
Spike-and-wave discharge (SWD) pattern detection in electroencephalography (EEG) is a crucial signal processing problem in epilepsy applications. It is particularly important for overcoming time-consuming, difficult, and error-prone manual analysis of lo...
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Alaa Alqatawneh, Rania Alhalaseh, Ahmad Hassanat and Mohammad Abbadi
In this paper, an efficient, accurate, and nonparametric epilepsy detection and classification approach based on electroencephalogram (EEG) signals is proposed. The proposed approach mainly depends on a feature extraction process that is conducted using ...
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Rania M. Ghoniem, Abeer D. Algarni and Khaled Shaalan
In multi-modal emotion aware frameworks, it is essential to estimate the emotional features then fuse them to different degrees. This basically follows either a feature-level or decision-level strategy. In all likelihood, while features from several moda...
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