DocumentCode :
1417466
Title :
Dominant frequency analysis of EEG reveals brain´s response during injury and recovery
Author :
Goel, Vaibhava ; Brambrink, Ansgar M. ; Baykal, Ahmet ; Koehler, Raymond C. ; Hanley, Daniel F. ; Thakor, Nitish V.
Author_Institution :
Dept. of Biomed. Eng., Johns Hopkins Univ., Baltimore, MD, USA
Volume :
43
Issue :
11
fYear :
1996
Firstpage :
1083
Lastpage :
1092
Abstract :
A new method of monitoring and analyzing electroencephalogram (EEG) signals during brain injury is presented, EEG signals are modeled using the autoregressive (AR) technique to obtain the frequencies where there are peaks in the spectrum. The powers at these dominant frequencies are analyzed to reveal the state of brain injury during an experimental study involving progressive hypoxia, asphyxia, and recovery. Neonatal piglets (n=8) were exposed to a sequence of 30 min of hypoxia (10% oxygen), 5 min of room air, and 7 min of asphyxia. They then received cardiopulmonary resuscitation and were subsequently monitored for 4 h. An optimal AR model order of 6 was obtained for these data, resulting in 3 dominant frequencies. These dominant frequencies, referred to as the low, medium, and high frequency components, fell in the bands 1.0-5.5 Hz, 9.0-14.0 Hz, and 18.0-21.0 Hz, respectively. A remarkable feature of the authors´ data is the spectral dispersion, or diverging trends in the 3 frequency bands. During hypoxia, the relative powers of the medium and high-frequency components of EEG increased up to 160% and 176%, from their respective baseline values. During the first minute of asphyxia the medium- and high-frequency powers (relative to baseline) increased by 280-400%. The power in all 3 frequency components went down to nearly zero within 40-80 s of asphyxia. During recovery, the phenomenon of burst-suppression was clearly exhibited in the low-frequency component. A new index, called mean normalized separation, representing the degree of disproportionality in the recovery of powers of the 3 dominant components relative to their mean recovered power, is presented as a possible single indicator of electrical function recovery. In conclusion, dominant frequency analysis helps reveal the brain´s graded electrical response to injury and recovery.
Keywords :
electroencephalography; medical signal processing; patient monitoring; 1.0 to 5.5 Hz; 18.0 to 21.0 Hz; 30 min; 4 hr; 5 min; 7 min; 9.0 to 14.0 Hz; EEG dominant frequency analysis; O/sub 2/; asphyxia; brain injury; brain recovery; burst-suppression; cardiopulmonary resuscitation; frequency bands; graded electrical response; hypoxia; mean normalized separation; monitoring method; optimal autoregressive model order; progressive hypoxia; spectral dispersion; Asphyxia; Biomedical engineering; Brain injuries; Brain modeling; Electroencephalography; Frequency; Medical diagnostic imaging; Monitoring; Pediatrics; Spectral analysis; Animals; Animals, Newborn; Brain; Diagnosis, Computer-Assisted; Electroencephalography; Fourier Analysis; Hypoxia, Brain; Resuscitation; Signal Processing, Computer-Assisted; Swine;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/10.541250
Filename :
541250
Link To Document :
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