BrainKilter: A Real-Time EEG Analysis Platform for Neurofeedback Design and Training. Pei, G., Guo, G., Chen, D., Yang, R., Shi, Z., Wang, S., Zhang, J., Wu, J., & Yan, T. IEEE Access, 8:57661–57673, 2020. ZSCC: 0000002 Conference Name: IEEE Accessdoi abstract bibtex Neurofeedback targets self-regularized brain activity to normalized brain function based on brain-computer interface (BCI) technology. Although BCI software or platforms have continued to mature in other fields, little effort has been expended on neurofeedback applications. Hence, we present BrainKilter, a real-time electroencephalogram (EEG) analysis platform based on a “4-tier layered model”. The purposes of BrainKilter are to improve portability and accessibility, allowing different users to choose various options to perform EEG processing, target stimulation-induction through a pipeline, and analyze data online, essentially, to design a protocol paradigm and applicable BCI technology for neurofeedback experiments. The data processing effectiveness and application value of BrainKilter were tested using multiple-parameter neurofeedback training, in which BrainKilter regulated the amplitude of mismatch negative (MMN) signals for healthy individuals. The proposed platform consists of a set of software modules for online protocol design and signal decoding that can be conveniently and efficiently integrated for neurofeedback design and training. The BrainKilter platform provides a truly easy-to-use environment for customizing the experimental paradigm and for optimizing the parameters of neurofeedback experiments for research and clinical neurofeedback applications using BCI technology.
@article{pei_brainkilter_2020,
title = {{BrainKilter}: {A} {Real}-{Time} {EEG} {Analysis} {Platform} for {Neurofeedback} {Design} and {Training}},
volume = {8},
issn = {2169-3536},
shorttitle = {{BrainKilter}},
doi = {10.1109/ACCESS.2020.2967903},
abstract = {Neurofeedback targets self-regularized brain activity to normalized brain function based on brain-computer interface (BCI) technology. Although BCI software or platforms have continued to mature in other fields, little effort has been expended on neurofeedback applications. Hence, we present BrainKilter, a real-time electroencephalogram (EEG) analysis platform based on a “4-tier layered model”. The purposes of BrainKilter are to improve portability and accessibility, allowing different users to choose various options to perform EEG processing, target stimulation-induction through a pipeline, and analyze data online, essentially, to design a protocol paradigm and applicable BCI technology for neurofeedback experiments. The data processing effectiveness and application value of BrainKilter were tested using multiple-parameter neurofeedback training, in which BrainKilter regulated the amplitude of mismatch negative (MMN) signals for healthy individuals. The proposed platform consists of a set of software modules for online protocol design and signal decoding that can be conveniently and efficiently integrated for neurofeedback design and training. The BrainKilter platform provides a truly easy-to-use environment for customizing the experimental paradigm and for optimizing the parameters of neurofeedback experiments for research and clinical neurofeedback applications using BCI technology.},
journal = {IEEE Access},
author = {Pei, Guangying and Guo, Guoxin and Chen, Duanduan and Yang, Ruoshui and Shi, Zhongyan and Wang, Shujie and Zhang, Jinpu and Wu, Jinglong and Yan, Tianyi},
year = {2020},
note = {ZSCC: 0000002
Conference Name: IEEE Access},
keywords = {4-tier layered model, BCI, BCI software, BCI technology, BrainKilter, BrainKilter platform, Data processing, EEG processing, Electroencephalography, MMN, Neurofeedback, Protocols, Real-time systems, Software, Training, brain-computer interface technology, brain-computer interfaces, clinical neurofeedback applications, data processing effectiveness, electroencephalography, medical signal processing, mismatch negative signals, multiple-parameter neurofeedback training, neurofeedback, neurofeedback design, neurofeedback experiments, neurophysiology, normalized brain function, online protocol design, platform, real-time, real-time EEG analysis platform, real-time electroencephalogram analysis platform, self-regularized brain activity, signal decoding, software modules, target stimulation-induction},
pages = {57661--57673},
}
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The purposes of BrainKilter are to improve portability and accessibility, allowing different users to choose various options to perform EEG processing, target stimulation-induction through a pipeline, and analyze data online, essentially, to design a protocol paradigm and applicable BCI technology for neurofeedback experiments. The data processing effectiveness and application value of BrainKilter were tested using multiple-parameter neurofeedback training, in which BrainKilter regulated the amplitude of mismatch negative (MMN) signals for healthy individuals. The proposed platform consists of a set of software modules for online protocol design and signal decoding that can be conveniently and efficiently integrated for neurofeedback design and training. 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