Oh Sung Suk, Han Yeji, Lee Jongho, Yun Seong Dae, Kang Joong Koo, Lee Eun Mi, Yoon Hyo Woon, Chung Jun-Young, Park HyunWook
Department of Electrical Engineering, Korean Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.
Department of Electrical Engineering, Korean Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea; Department of Biomedical Engineering, College of Health Science, Gachon University, Incheon, Republic of Korea.
Neurosci Res. 2014 Apr-May;81-82:42-50. doi: 10.1016/j.neures.2014.01.008. Epub 2014 Jan 31.
A simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) can provide high spatiotemporal information of brain activity. However, a proper analysis of the EEG signals is often hindered by various artifacts. In particular, pulse artifact (PA) induced from the heartbeat of a subject interferes with reliable measurements of the EEG signal. A new PA removal method that takes into account the delay variation between the heartbeat and PA and the window size variation in PA is presented in order to improve the detection and suppression of PA in EEG signals. A PA is classified into either a normal PA or a deformed PA. Only normal PAs are averaged to generate a PA template that is used to remove PAs from the measured EEG signals. The performance of the proposed method was evaluated by simulated data and real EEG measurements from epilepsy patients. The results are compared with those from conventional methods.
同步记录脑电图（EEG）和功能磁共振成像（fMRI）可以提供大脑活动的高时空信息。然而，脑电图信号的正确分析常常受到各种伪迹的阻碍。特别是，由受试者心跳引起的脉搏伪迹（PA）会干扰脑电图信号的可靠测量。为了提高脑电图信号中PA的检测和抑制能力，提出了一种新的PA去除方法，该方法考虑了心跳与PA之间的延迟变化以及PA中的窗口大小变化。PA被分为正常PA或变形PA。仅对正常PA进行平均以生成PA模板，该模板用于从测量的脑电图信号中去除PA。通过模拟数据和癫痫患者的实际脑电图测量对所提方法的性能进行了评估。并将结果与传统方法的结果进行了比较。
