A real-time seizure prediction system. The system includes an implantable electrode configured to transmit an analog neuro-electrophysiological signal from a subject, an analog-to-digital converter configured to convert the analog neuro-electrophysiological signal to a digital neuro-electrophysiological signal based on a predetermined sampling rate, a processor configured to perform following steps during a period defined by the predetermined sampling rate: calculate a plurality of autocorrelation coefficients of the digital neuro-electrophysiological signal for a first predetermined number of samples, calculate a predicted future value of the digital neuro-electrophysiological data based on the plurality of autocorrelation coefficients and the first predetermined number of samples of the digital neuro-electrophysiological data, compare the predicted future value with an actual future value of the digital neuro-electrophysiological data to determine a prediction error, calculate a threshold based on a mean squared value of the prediction error for the first predetermined number of samples and based on a proportionality constant, generate a seizure prediction signal if the prediction error remains above the threshold for a second predetermined number of samples, and a warning device configured to receive the seizure prediction signal and generate an alert.
