Motion tracking and electromyography-assisted identification of mirror hand contributions to functional near-infrared spectroscopy images acquired during a finger-tapping task performed by children with cerebral palsy.
Motion tracking and electromyography-assisted identification of mirror hand contributions to functional near-infrared spectroscopy images acquired during a finger-tapping task performed by children with cerebral palsy.
复制标题
运动跟踪和肌电图辅助识别镜像手对脑瘫儿童执行手指敲击任务时获取的功能性近红外光谱图像的贡献。
DOI：
10.1117/1.nph.1.2.025009
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发表时间：
2014
期刊：
影响因子：
5.3
通讯作者：
Alexandrakis,George
中科院分区：
文献类型：
--
作者：
Hervey,Nathan;Khan,Bilal;Shagman,Laura;Tian,Fenghua;Delgado,MauricioR;Tulchin-Francis,Kirsten;Shierk,Angela;Roberts,Heather;Smith,Linsley;Reid,Dahlia;Clegg,NancyJ;Liu,Hanli;MacFarlane,Duncan;Alexandrakis,George
最近的研究表明，功能近红外光谱（fNIRS）是一种可行的和敏感的方法来成像大脑性瘫痪（CP）儿童的感觉运动皮层活动。然而，在单侧手指轻敲期间，CP儿童经常在非轻敲的手中表现出意想不到的运动，称为镜像运动，这混淆了对所产生的fNIRS图像的解释。这项工作提出了一种方法分离的一些镜像运动的贡献fNIRS图像，并演示了其应用程序的fNIRS数据从四个孩子CP执行手指敲击任务与镜像运动。分别使用运动跟踪和肌电图（EMG）与fNIRS信号同时测量手指运动和手臂肌肉活动。随后，从运动捕捉或EMG数据创建受试者特异性回归量，并将独立成分分析与一般线性模型相结合，以创建表示由于敲击手而激活的fNIRS图像和表示由于镜像手而激活的一个图像。所提出的方法可以提供关于镜面运动如何对fNIRS图像做出贡献的信息，并且在某些情况下，它有助于从敲击手激活图像中去除镜面运动污染。
Recent studies have demonstrated functional near-infrared spectroscopy (fNIRS) to be a viable and sensitive method for imaging sensorimotor cortex activity in children with cerebral palsy (CP). However, during unilateral finger tapping, children with CP often exhibit unintended motions in the nontapping hand, known as mirror motions, which confuse the interpretation of resulting fNIRS images. This work presents a method for separating some of the mirror motion contributions to fNIRS images and demonstrates its application to fNIRS data from four children with CP performing a finger-tapping task with mirror motions. Finger motion and arm muscle activity were measured simultaneously with fNIRS signals using motion tracking and electromyography (EMG), respectively. Subsequently, subject-specific regressors were created from the motion capture or EMG data and independent component analysis was combined with a general linear model to create an fNIRS image representing activation due to the tapping hand and one image representing activation due to the mirror hand. The proposed method can provide information on how mirror motions contribute to fNIRS images, and in some cases, it helps remove mirror motion contamination from the tapping hand activation images.