Molavi Behnam, Dumont Guy A
Department of Electrical and Computer Engineering, University of British Columbia, Canada.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:5-8. doi: 10.1109/IEMBS.2010.5626589.
Functional Near Infrared Spectroscopy (fNIRS) enables researchers to conduct studies in situations where use of other functional imaging methods is impossible. An important shortcoming of fNIRS is the sensitivity to motion artifacts. We propose a new wavelet based algorithm for removing movement artifacts from fNIRS signals. We tested the method on simulated and experimental fNIRS data. The results show an average of 18.97 dB and 15.54 dB attenuation in motion artifacts power for our two test subjects without introducing significant distortion in the artifact-free regions of the signal.
功能近红外光谱技术（fNIRS）使研究人员能够在无法使用其他功能成像方法的情况下开展研究。fNIRS的一个重要缺点是对运动伪影敏感。我们提出了一种基于小波的新算法，用于去除fNIRS信号中的运动伪影。我们在模拟和实验fNIRS数据上测试了该方法。结果表明，对于我们的两名测试对象，运动伪影功率平均衰减了18.97 dB和15.54 dB，且在信号无伪影区域未引入明显失真。
