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公開日:2022/06/22 / 最終更新日:2022/06/22
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Thewolfofwallstreetfullmovieinhindihd25
thewolfofwallstreetfullmovieinhindihd25
The Wolf of Wall Street, Full.
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.An adaptive three-step decision algorithm for detecting seizures using a single cortical electrode.
Monitoring patients with chronic epileptic patients is a difficult and costly task. In this work, we present an algorithm to detect seizures in patients with focal epilepsy by using a single cortical electrode to acquire a two-dimensional electroencephalogram (EEG) and analyzing this data stream using a combination of signal processing, machine learning, and feature analysis to detect seizure onsets. The algorithm is based on a novel data acquisition and processing algorithm to provide a dense two-dimensional continuous recording of the EEG while minimizing the cost. The seizure detection algorithm consists of three processing steps: 1) preprocessing the raw EEG data to increase the signal-to-noise ratio, 2) acquiring a brain activity map using a threshold-based machine learning algorithm that aims to detect the true onset of a seizure, and 3) combining the two maps for a final decision. For this work we used the publicly available data sets of the public Media Seizure Detection Competition 2004 as a benchmark to evaluate the proposed algorithm. The obtained results yielded a sensitivity of 99.41% and a positive predictivity of 98.46% for the detection of the seizures by using six channels. This method allows the detection of ictal and interictal events with a single cortical electrode providing a means to lower the cost of monitoring a patient. The proposed method consists of three processing steps: 1) preprocessing the raw EEG data to increase the signal-to-noise ratio, 2) acquiring a brain activity map using a threshold-based machine learning algorithm that aims to detect the true onset of a seizure, and 3) combining the two maps for a final decision. For this work we used the publicly available data sets of the public Media Seizure Detection Competition 2004 as a benchmark to evaluate the proposed algorithm. The obtained results yielded a sensitivity of 99.41% and a positive predictivity of 98.46% for the detection of the seizures by using six channels. This method allows the detection of ictal and interictal events with a single cortical
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