Aloui N, Planat-Chretien A, Bonnet S
Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:208-211. doi: 10.1109/EMBC46164.2021.9629641.
Combining electroencephalography (EEG) to functional near-infrared spectroscopy (fNIRS) is a promising technique that has gained momentum thanks to their complementarity. While EEG measures the electrical activity of the brain, fNIRS records the variations in cerebral blood flow and related hemoglobin concentrations. However, both modalities are typically contaminated with artefacts. Muscle and eye artefacts, affect the EEG signals, while hemodynamic and oxygenation changes in the extracerebral compartment due to systemic changes (superficial layer) corrupt the fNIRS signals. Moreover, both signals are sensitive to sensor motion artefacts characterized by large amplitude. There are several well-established methods for removing artefacts for both modalities. The objective of this paper is to apply a common approach to denoise both EEG and fNIRS signals. Indeed Artifact Subspace Reconstruction (ASR) method, which is an automatic, online-capable and efficient method for deleting transient or large-amplitude EEG artefacts, can be a good alternative to also denoise fNIRS signals. In this paper, we first propose, a new more comprehensive formulation of ASR. Then, we study the effectiveness of the method in denoising both the EEG and fNIRS signals.
将脑电图（EEG）与功能性近红外光谱（fNIRS）相结合是一项很有前景的技术，由于它们的互补性，该技术已获得发展动力。脑电图测量大脑的电活动，而功能性近红外光谱记录脑血流量和相关血红蛋白浓度的变化。然而，这两种模式通常都受到伪迹的污染。肌肉和眼部伪迹会影响脑电图信号，而由于全身变化（表层）导致的脑外腔室血流动力学和氧合变化会破坏功能性近红外光谱信号。此外，这两种信号都对以大幅度为特征的传感器运动伪迹敏感。有几种成熟的方法可用于去除这两种模式的伪迹。本文的目的是应用一种通用方法对脑电图和功能性近红外光谱信号进行去噪。事实上，伪迹子空间重构（ASR）方法是一种用于删除瞬态或大幅度脑电图伪迹的自动、在线且高效的方法，它也可以作为对功能性近红外光谱信号进行去噪的一个很好的替代方法。在本文中，我们首先提出一种新的、更全面的伪迹子空间重构公式。然后，我们研究该方法对脑电图和功能性近红外光谱信号进行去噪的有效性。
