Govindan Rathinaswamy B, Vairavan Srinivasan, Haddad Naim, Wilson James D, Preissl Hubert, Eswaran Hari
Department of Obstetrics and Gynecology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:6616-9. doi: 10.1109/IEMBS.2009.5332560.
We propose a novel method to characterize the spontaneous brain signals using Hilbert phases. The Hilbert phase of a signal exhibits phase slips when the magnitude of the successive phase difference exceeds pi. To this end we use standard deviation (sigmaDeltatau) of the time (Deltatau) between successive phase slips to characterize the signals. We demonstrate the application of this approach to neonatal and fetal magnetoencephalographic signals recorded using a 151-sensor array to identify the sensors containing the neonatal and fetal brain signals. To this end we propose a spatial filter using sigma(Deltatau) as weights to reconstruct the brain signals.
我们提出了一种使用希尔伯特相位来表征自发脑信号的新方法。当连续相位差的幅度超过π时,信号的希尔伯特相位会出现相位跳变。为此,我们使用连续相位跳变之间的时间(Δτ)的标准差(σΔτ)来表征信号。我们展示了这种方法在使用151传感器阵列记录的新生儿和胎儿脑磁图信号中的应用,以识别包含新生儿和胎儿脑信号的传感器。为此,我们提出了一种以σ(Δτ)作为权重的空间滤波器来重建脑信号。