TY - JOUR
T1 - A fatigue state evaluation system based on the band energy of electroencephalography signals
AU - Hsieh, Chin Shun
AU - Tai, Cheng-Chi
PY - 2013/12/1
Y1 - 2013/12/1
N2 - Cranial nerve information can be used to correctly analyze fatigue states. Spectral analysis is the major method of identifying fatigue states. Various frequency bands can be distinguished by digital filters owing to their high accuracy and driftless features. The electroencephalography EEG signal is sent to a personal computer (PC) via a universal serial bus USB interface from a microcontroller and passed through digital filters within 200 taps, and thus, the spectrum of individual signals can be analyzed. This study has investigated the four EEG frequency bands, delta ()δ, theta (θ), alpha (α), and beta (β), using four algorithms to evaluate the fatigue state based on the EEG signals. We compared the four algorithms and determined the best one.
AB - Cranial nerve information can be used to correctly analyze fatigue states. Spectral analysis is the major method of identifying fatigue states. Various frequency bands can be distinguished by digital filters owing to their high accuracy and driftless features. The electroencephalography EEG signal is sent to a personal computer (PC) via a universal serial bus USB interface from a microcontroller and passed through digital filters within 200 taps, and thus, the spectrum of individual signals can be analyzed. This study has investigated the four EEG frequency bands, delta ()δ, theta (θ), alpha (α), and beta (β), using four algorithms to evaluate the fatigue state based on the EEG signals. We compared the four algorithms and determined the best one.
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M3 - Article
AN - SCOPUS:84892188212
SN - 0914-4935
VL - 25
SP - 667
EP - 671
JO - Sensors and Materials
JF - Sensors and Materials
IS - 9
ER -