Research Papers: General

Empirical mode decomposition-based motion artifact correction method for functional near-infrared spectroscopy

[+] Author Affiliations
Yue Gu, Zhenhu Liang, Jiaqing Yan

Yanshan University, Institute of Electrical Engineering, No. 438, Hebei Street, Haigang District, Qinhuangdao 066004, China

Junxia Han, Zheng Li, Xiaoli Li

Beijing Normal University, State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, No. 19, Xinjiekou Wai Street, Haidian District, Beijing 100875, China

Beijing Normal University, Center for Collaboration and Innovation in Brain and Learning Sciences, No. 19, Xinjiekou Wai Street, Haidian District, Beijing 100875, China

J. Biomed. Opt. 21(1), 015002 (Jan 06, 2016). doi:10.1117/1.JBO.21.1.015002
History: Received August 9, 2015; Accepted November 30, 2015
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Abstract.  Functional near-infrared spectroscopy (fNIRS) is a promising technique for monitoring brain activity. However, it is sensitive to motion artifacts. Many methods have been developed for motion correction, such as spline interpolation, wavelet filtering, and kurtosis-based wavelet filtering. We propose a motion correction method based on empirical mode decomposition (EMD), which is applied to segments of data identified as having motion artifacts. The EMD method is adaptive, data-driven, and well suited for nonstationary data. To test the performance of the proposed EMD method and to compare it with other motion correction methods, we used simulated hemodynamic responses added to real resting-state fNIRS data. The EMD method reduced mean squared error in 79% of channels and increased signal-to-noise ratio in 78% of channels. Moreover, it produced the highest Pearson’s correlation coefficient between the recovered signal and the original signal, significantly better than the comparison methods (p<0.01, paired t-test). These results indicate that the proposed EMD method is a first choice method for motion artifact correction in fNIRS.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Yue Gu ; Junxia Han ; Zhenhu Liang ; Jiaqing Yan ; Zheng Li, et al.
"Empirical mode decomposition-based motion artifact correction method for functional near-infrared spectroscopy", J. Biomed. Opt. 21(1), 015002 (Jan 06, 2016). ; http://dx.doi.org/10.1117/1.JBO.21.1.015002


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