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首页> 外文期刊>Medical and Biological Engineering and Computing: Journal of the International Federation for Medical and Biological Engineering >Removal of eye movement artefacts from single channel recordings of retinal evoked potentials using synchronous dynamical embedding and independent component analysis.
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Removal of eye movement artefacts from single channel recordings of retinal evoked potentials using synchronous dynamical embedding and independent component analysis.

机译:使用同步动态嵌入和独立分量分析,从视网膜诱发电位的单通道记录中去除眼动伪影。

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摘要

A system is described for the removal of eye movement and blink artefacts from single channel pattern reversal electroretinogram recordings of very poor signal-to-noise ratios. Artefacts are detected and removed by using a blind source separation technique based on the jadeR independent component analysis algorithm. The single channel data are arranged as a series of overlapping time-delayed vectors forming a dynamical embedding matrix. The structure of this matrix is constrained to the phase of the stimulation epoch: the term synchronous dynamical embedding is coined. A novel method using a marker channel with a non-independent synchronous feature is employed to identify the single most relevant source estimation for reconstruction and signal recovery. This method is non-lossy, all underlying signal being recovered. In synthetic datasets of defined noise content and in standardised real data recordings, the performance of this technique is compared to conventional fixed-threshold hard-limit rejection.The most significant relative improvements are achieved when movement and blink artefacts are greatest: no improvement is demonstrable for the random noise only situation.
机译:描述了一种用于从信噪比非常差的单通道模式反转视网膜电图记录中去除眼球运动和眨眼伪影的系统。通过使用基于jadeR独立成分分析算法的盲源分离技术来检测和去除伪影。将单通道数据安排为一系列重叠的时延矢量,形成动态嵌入矩阵。该矩阵的结构被限制在刺激时期的阶段:创造了术语“同​​步动态嵌入”。一种使用具有非独立同步特征的标记通道的新颖方法被用来识别用于重建和信号恢复的单个最相关的源估计。这种方法是无损的,所有基础信号都可以恢复。在定义噪声含量的合成数据集和标准化的真实数据记录中,将这种技术的性能与常规的固定阈值硬限制拒绝进行了比较。最大的相对改进是在运动和眨眼伪像最大时实现的:没有改进可证明对于仅随机噪声的情况。

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