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    • 3. 发明申请
    • MOTION AND NOISE ARTIFACT DETECTION FOR ECG DATA
    • 心电数据运动和噪声检测
    • WO2012051320A3
    • 2012-06-07
    • PCT/US2011055989
    • 2011-10-12
    • WORCESTER POLYTECH INSTCHON KI HLEE JINSEOK
    • CHON KI HLEE JINSEOK
    • A61B5/0402A61B5/0432
    • A61B5/7207A61B5/04012A61B5/0404A61B5/0432A61B5/0456
    • Technologies are provided herein for real-time detection of motion and noise (MN) artifacts in electrocardiogram signals recorded by electrocardiography devices. Specifically, the present disclosure provides techniques for increasing the accuracy of identifying paroxysmal atrial fibrillation (AF) rhythms, which are often measured via such devices. According to aspects of the present disclosure, a method for detecting MN artifacts in an electrocardiogram (ECG) recording includes receiving an ECG segment and decomposing the received ECG segment into a sum of intrinsic mode functions. The intrinsic mode functions associated with MN artifacts present within the ECG segment are then isolated. The method further includes determining randomness and variability characteristic values associated with the isolated intrinsic mode functions and comparing the randomness and variability characteristic values to threshold randomness and variability characteristic values. If the randomness and variability characteristic values exceed the threshold characteristic values, the ECG signal is determined to include MN artifacts.
    • 本文提供的技术用于实时检测由心电图仪器记录的心电图信号中的运动和噪声(MN)伪影。 具体地,本公开提供了用于增加识别阵发性心房颤动(AF)节律的准确性的技术,其经常通过这样的装置测量。 根据本公开的方面,用于检测心电图(ECG)记录中的MN伪像的方法包括接收ECG片段并将接收到的ECG片段分解为固有模式功能的总和。 然后隔离与ECG段内存在的MN伪影相关联的固有模式功能。 该方法还包括确定与分离的固有模式函数相关联的随机性和可变性特征值,并将随机性和可变性特征值与阈值随机性和可变性特征值进行比较。 如果随机性和变异性特征值超过阈值特征值,则确定ECG信号包括MN伪像。