An Automatic Spike Detection System Based on Elimination of False Positives Using the Large-Area Context in the Scalp EEG

@article{Ji2011AnAS,
  title={An Automatic Spike Detection System Based on Elimination of False Positives Using the Large-Area Context in the Scalp EEG},
  author={Zhanfeng Ji and Takenao Sugi and Satoru Goto and Xingyu Wang and Akio Ikeda and Takashi Nagamine and Hiroshi Shibasaki and Masatoshi Nakamura},
  journal={IEEE Transactions on Biomedical Engineering},
  year={2011},
  volume={58},
  pages={2478-2488}
}
Most automatic spike detection systems in the scalp electroencephalogram (EEG) focused on the characteristics of “spike.” However, the characteristics of “false positives” (FPs) have not been fully studied. In this paper, we proposed a system that contains a series of algorithms to eliminate FPs and a template method to confirm spikes. The system used large area context available on 49 channels from two common montages. The impact of slow-waves after spikes was taken into consideration, as well… CONTINUE READING
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