A discrimination between the two different types of acute stroke (ischemic and hemorrhagic) is accomplished by the implementation of both the Inverse problem of electroencephalography (EEG) technique and the method of principal components analysis (PCA). The study was based on electroencephalograms (EEGs) recorded from patients that had suffered from stokes. The brain activity was simulated with a realistic head model excited by electric dipoles, which in the present work were allowed only to rotate about a fixed origin. Combining the calculated surface potentials of the head model and the EEG recordings, the inverse problem algorithm converged to a solution giving an equivalent dipole that included all the information needed to distinguish each type of stroke. Alternatively, PCA technique was implemented directly on the EEG recordings in order to reveal potentially hidden patterns underlying the recordings. For this purpose, the corresponding techniques developed within our previous work, are exploited herein for the processing of patients' EEGs. It is observed that indeed both equivalent dipole and PCA or its alternative proper orthogonal decomposition approaches were able to discriminate the two types of stroke.

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