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In this process, we using the EEG signal processing method of detection and classification to provide a unique signature for an individual as a biometric. Neural representations of hand synergies were encoded in spectral coherence of optimal EEG electrodes in the motor and parietal areas. The signal is stored in the dataset and then process in the MATLAB simulation itself. Also, it was observed that the best performance was obtained when movement specific EEG signals by using the physionet datasets were used as features of the signal. The implications of these first results, improvements, and their applications in the near future are discussed.
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