In this paper, the trajectories of the poles (radiuses and frequencies) of the time-varying autoregressive (TV-AR) model of the electroencephalogram (EEG) signal are used for monitoring brain injury and recovery. The TV-AR coefficients are obtained using Burg algorithm applied to a sliding window. The norm of the TV-frequencies is suggested to be a quantitative measure for monitoring the brain injury and recovery. The radiuses-frequencies of the TV-poles are displayed as a scattering plot for monitoring and investigating the brain injury and recovery as well. This scattering plot provides more details about injury-related EEG changes. Analysis and results of real-world EEG data illustrate that the norm of the TV-frequencies and the scattering plot of the radiuses-frequencies provide significant tool for investigating and monitoring the brain injury and recovery from the TV-AR model poles. For intensive analysis various model orders are examined. The second-order model introduces itself as the significant one for monitoring the brain injury. With employing the third-order, asphyxia manifests itself by damping the real pole and by increasing the frequencies of the other two poles. In the resuscitation segment the situation moves back and finally in the recovery segment the scattering plot gets closely similar to the normal EEG scattering plot.