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Chuanyan Feng, Shuang Liu, Xiaoru Wanyan, Hao Chen, Yuchen Min and Yilan Ma
In order to discriminate situation awareness (SA) levels on the basis of SA-sensitive electroencephalography (EEG) features, the high-SA (HSA) group and low-SA (LSA) groups, which are representative of two SA levels, were classified according to the situ...
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Hongjian Bo, Haifeng Li, Boying Wu, Hongwei Li and Lin Ma
At present, there are very few analysis methods for long-term electroencephalogram (EEG) components. Temporal information is always ignored by most of the existing techniques in cognitive studies. Therefore, a new analysis method based on time-varying ch...
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Saraswati Sridhar and Vidya Manian
Electroencephalogram signals are used to assess neurodegenerative diseases and develop sophisticated brain machine interfaces for rehabilitation and gaming. Most of the applications use only motor imagery or evoked potentials. Here, a deep learning netwo...
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Hongquan Qu, Zhanli Fan, Shuqin Cao, Liping Pang, Hao Wang and Jie Zhang
Electroencephalogram (EEG) signals contain a lot of human body performance information. With the development of the brain?computer interface (BCI) technology, many researchers have used the feature extraction and classification algorithms in various fiel...
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Wahyu Caesarendra
Pág. 9 - 16
The progress of today's technology is growing very quickly. This becomes the motivation for the community to be able to continue and provide innovations. One technology to be developed is the application of brain signals or called with electroencephalogr...
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