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Patient-specific seizure onset detection system

机译:特定于患者的癫痫发作检测系统

摘要

The present invention provides methods and systems for patient-specific seizure onset detection. In one embodiment, at least one EEG waveform of the patient is recorded, and at least one epoch (sample) of the waveform is extracted. The waveform sample is decomposed into one or more subband signals via a wavelet decomposition of the waveform sample, and one or more feature vectors are computed based on the subband signals. A seizure onset can then be identified based on classification of the feature vectors to a seizure or a non-seizure class by comparing the feature vectors with a decision measure previously computed for that patient. The decision measure can be derived based on reference seizure and non-seizure EEG waveforms of the patient. In another aspect, similar methodology is employed for automatic detection of alpha waves. In other aspects, the invention provides diagnostic and imaging systems that incorporate the above seizure-onset and alpha-wave detection methodology.
机译:本发明提供了用于患者特异性癫痫发作检测的方法和系统。在一实施例中,记录患者的至少一个EEG波形,并提取该波形的至少一个历元(样本)。经由波形样本的小波分解将波形样本分解为一个或多个子带信号,并且基于子带信号来计算一个或多个特征向量。然后,可以通过将特征向量与先前针对该患者计算的决策量度进行比较,基于特征向量对癫痫发作或非癫痫发作类别的分类来识别癫痫发作。可以基于患者的参考癫痫发作和非癫痫发作EEG波形得出决策措施。在另一方面,采用类似的方法来自动检测α波。在其他方面,本发明提供了结合上述癫痫发作和α波检测方法的诊断和成像系统。

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