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Tadashi Yamamoto and Toyohiro Hamaguchi
In this study, we aimed to evaluate the effectiveness of a brain robot in rehabilitation that combines motor imagery (MI), robotic motor assistance, and electrical stimulation. Thirteen in-patients with severe post-stroke hemiplegia underwent electroence...
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Foteini Gramouseni, Katerina D. Tzimourta, Pantelis Angelidis, Nikolaos Giannakeas and Markos G. Tsipouras
The objective of this systematic review centers on cognitive assessment based on electroencephalography (EEG) analysis in Virtual Reality (VR), Augmented Reality (AR) and Mixed Reality (MR) environments, projected on Head Mounted Displays (HMD), in healt...
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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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Zhiwei Li, Jun Li, Yousheng Xia, Pingfa Feng and Feng Feng
Epileptic diseases take EEG as an important basis for clinical judgment, and fractal algorithms were often used to analyze electroencephalography (EEG) signals. However, the variation trends of fractal dimension (D) were opposite in the literature, i.e.,...
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Shang Feng, Haifeng Li, Lin Ma and Zhongliang Xu
In the application of the brain-computer interface, feature extraction is an important part of Electroencephalography (EEG) signal classification. Using sparse modeling to extract EEG signal features is a common approach. However, the features extracted ...
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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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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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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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Steven Galindo-Noreña, David Cárdenas-Peña and Álvaro Orozco-Gutierrez
Brain?computer interface (BCI) systems communicate the human brain and computers by converting electrical activity into commands to use external devices. Such kind of system has become an alternative for interaction with the environment for people suffer...
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Jackeline Granados-Ruiz,David Asael Gutierrez-Hernandez,Carlos Lino-Ramírez,Víctor M. Zamudio,Manuel Ornelas-Rodríguez,Miguel Gómez-Díaz,Diego Mendoza-Gámez,Pilar Pérez-Mata
Generally, signal processing is applied to a set of data that is derived from the sampling of an acquired signal. This treatment is carried out with the help of a computer that in turn executes a series of logical and mathematical operations. The treatme...
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