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Titlebook: EEG Signal Processing and Feature Extraction; Li Hu,Zhiguo Zhang Book 2019 Springer Nature Singapore Pte Ltd. 2019 Electroencephalography

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Mental Health Assessment of Juveniles,tation can be used to identify the underlying ERP components and their latencies from the multichannel ERP waveforms. In this chapter, we illustrated the basic concepts of microstate analysis, the commonly used clustering algorithms, the metrics derived from microstate analysis, and how to perform microstate analysis using open-access tools.
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Spirituality, Belief, and Relationship convolutional neural network and recurrent neural network. Then, we provide the applications of these two DL models to focus on the eye state detection task, which both achieve excellent recognition effects and are expected to be useful for broader applications in BCI systems.
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Deep Learning, convolutional neural network and recurrent neural network. Then, we provide the applications of these two DL models to focus on the eye state detection task, which both achieve excellent recognition effects and are expected to be useful for broader applications in BCI systems.
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EEG/ERP Data Analysis Toolboxes,lboxes in EEG/ERP analysis, such as EEGLab, FieldTrip, BrainVision Analyzer, etc., and then focus on the introduction of Letswave, which is an intuitive and streamlined tool to process and visualize EEG data, with a shallow learning curve. Examples are provided for a better understanding of Letswave7 in EEG/ERP data analysis.
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https://doi.org/10.1007/978-981-13-9113-2Electroencephalography (EEG); Signal processing; Feature extraction; Time series analysis; Software
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978-981-13-9115-6Springer Nature Singapore Pte Ltd. 2019
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