Erickson Jonathan C, Putney Joy, Hilbert Douglas, Paskaranandavadivel Niranchan, Cheng Leo K, O'Grady Greg, Angeli Timothy R
Department of Physics and Engineering, Washington and Lee University, Lexington, VA, USA.
Department of Physics and Engineering, Washington and Lee University.
IEEE Trans Biomed Eng. 2016 Nov;63(11):2262-2272. doi: 10.1109/TBME.2016.2521764. Epub 2016 Jan 26.
The aim of this study was to develop, validate, and apply a fully automated method for reducing large temporally synchronous artifacts present in electrical recordings made from the gastrointestinal (GI) serosa, which are problematic for properly assessing slow wave dynamics. Such artifacts routinely arise in experimental and clinical settings from motion, switching behavior of medical instruments, or electrode array manipulation.
A novel iterative Covariance-Based Reduction of Artifacts (COBRA) algorithm sequentially reduced artifact waveforms using an updating across-channel median as a noise template, scaled and subtracted from each channel based on their covariance.
Application of COBRA substantially increased the signal-to-artifact ratio (12.8 ± 2.5 dB), while minimally attenuating the energy of the underlying source signal by 7.9% on average ( -11.1 ± 3.9 dB).
COBRA was shown to be highly effective for aiding recovery and accurate marking of slow wave events (sensitivity = 0.90 ± 0.04; positive-predictive value = 0.74 ± 0.08) from large segments of in vivo porcine GI electrical mapping data that would otherwise be lost due to a broad range of contaminating artifact waveforms.
Strongly reducing artifacts with COBRA ultimately allowed for rapid production of accurate isochronal activation maps detailing the dynamics of slow wave propagation in the porcine intestine. Such mapping studies can help characterize differences between normal and dysrhythmic events, which have been associated with GI abnormalities, such as intestinal ischemia and gastroparesis. The COBRA method may be generally applicable for removing temporally synchronous artifacts in other biosignal processing domains.
本研究的目的是开发、验证并应用一种全自动方法，以减少胃肠道（GI）浆膜电记录中出现的大量时间同步伪迹，这些伪迹对正确评估慢波动力学存在问题。此类伪迹通常在实验和临床环境中因运动、医疗器械的切换行为或电极阵列操作而产生。
一种新颖的基于协方差的伪迹迭代减少（COBRA）算法，使用跨通道更新中位数作为噪声模板，依次减少伪迹波形，并根据各通道的协方差进行缩放和减法运算。
应用COBRA显著提高了信伪比（12.8±2.5 dB），同时使基础源信号的能量平均最小衰减7.9%（-11.1±3.9 dB）。
对于体内猪胃肠道电图数据的大片段，COBRA被证明在辅助慢波事件的恢复和准确标记方面非常有效（灵敏度=0.90±0.04；阳性预测值=0.74±0.08），否则这些数据会因广泛的污染伪迹波形而丢失。
使用COBRA大幅减少伪迹最终能够快速生成准确的等时激活图，详细描述猪肠道中慢波传播的动力学。此类映射研究有助于表征正常和心律失常事件之间的差异，这些差异与胃肠道异常有关，如肠道缺血和胃轻瘫。COBRA方法可能普遍适用于去除其他生物信号处理领域中的时间同步伪迹。
