title: Dominant frequency analysis of EEG reveals brain's response during injury and recovery.
abstract: A new method of monitoring an 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 six was obtained for these data, resulting in three 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 our data is the spectral dispersion, or diverging trends in the three 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 three 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 three 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.
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University, School of Medicine, Baltimore, MD 21205, USA.
authors.forename: V
authors.initials: V
authors.lastname: Goel
authors.forename: A M
authors.initials: AM
authors.lastname: Brambrink
authors.forename: A
authors.initials: A
authors.lastname: Baykal
authors.forename: R C
authors.initials: RC
authors.lastname: Koehler
authors.forename: D F
authors.initials: DF
authors.lastname: Hanley
authors.forename: N V
authors.initials: NV
authors.lastname: Thakor
mesh_terms: D000818:Animals; D000831:Animals, Newborn; D001921:Brain / Q000503:physiopathology*; D003936:Diagnosis, Computer-Assisted; D004569:Electroencephalography; D005583:Fourier Analysis; D002534:Hypoxia, Brain / Q000175:diagnosis / Q000503:physiopathology*; D012151:Resuscitation; D012815:Signal Processing, Computer-Assisted; D013552:Swine