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NEURAL OSCILLATION MONITORING SYSTEM
专利权人:
Newton Howard
发明人:
Newton Howard
申请号:
US15257019
公开号:
US20170065229A1
申请日:
2016.09.06
申请国别(地区):
US
年份:
2017
代理人:
摘要:
Embodiments of the present invention may provide automated techniques for signal analysis that may continuously provide up-to-date results that link EEG and behaviors that are important for daily activities. Such techniques may provide automation, objectivity, real-time monitoring and portability. In an embodiment of the present invention, a computer-implemented method for monitoring neural activity may comprise receiving data representing at least one signal representing neural activity of a test subject, pre-processing the received data by performing at least one of band-pass filtering, artifact removal, identifying common spatial patterns, and temporally segmentation, processing the pre-processed data by performing at least one of time domain processing, frequency domain processing, and time-frequency domain processing, generating a machine learning model using the processed data as a training dataset, and outputting a characterization of the neural activity based on the machine learning model.
来源网站:
中国工程科技知识中心
来源网址:
http://www.ckcest.cn/home/

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