@inproceedings{a450c0232bb648999a253ac82f92f5f0,
title = "Digital EEG signal acquiring system based on FPGA",
abstract = "In recent years, with the development of the study of Electroencephalogram (EEG) theory, brain-computer interfaces (BCI) which can control the interrelated devices based on the features extracted from the brain signals have been popular. However, the amplitude of EEG signals are so weak and they are easily affected by external interference. This paper designs one kind of EEG measuring equipment which can acquire 32-channel EEG signal simultaneously based on FPGA. Then we used this system to measure the steady-state visually evoked potential (SSVEP) signals, and analyzed the data of SSVEP signals with the algorithm of Canonical Correlation Analysis (CCA). Experimental results show that this system can measure the voltage of μV level and can be used to measure the EEG signal.",
keywords = "BCI, CCA, FPGA, SSVEP, Weak signal measurement",
author = "Zhang Pengju and Zheng Dezhi and Zhang Shuailei and Huang Kai",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 13th IEEE International Conference on Electronic Measurement and Instruments, ICEMI 2017 ; Conference date: 20-10-2017 Through 22-10-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/ICEMI.2017.8265998",
language = "English",
series = "ICEMI 2017 - Proceedings of IEEE 13th International Conference on Electronic Measurement and Instruments",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "528--533",
editor = "Wu Juan and Yin Jiali and Zhang Qi",
booktitle = "ICEMI 2017 - Proceedings of IEEE 13th International Conference on Electronic Measurement and Instruments",
address = "United States",
}
