Broniec A
Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Science and Technology, al. A. Mickiewicza 30, Kraków, Poland.
Med Biol Eng Comput. 2016 Dec;54(12):1935-1947. doi: 10.1007/s11517-016-1491-z. Epub 2016 Apr 8.
Flicker-noise spectroscopy (FNS) is a general phenomenological approach to analyzing dynamics of complex nonlinear systems by extracting information contained in chaotic signals. The main idea of FNS is to describe an information hidden in correlation links, which are present in the chaotic component of the signal, by a set of parameters. In the paper, FNS is used for the analysis of electroencephalography signal related to the hand movement imagination. The signal has been parametrized in accordance with the FNS method, and significant changes in the FNS parameters have been observed, at the time when the subject imagines the movement. For the right-hand movement imagination, abrupt changes (visible as a peak) of the parameters, calculated for the data recorded from the left hemisphere, appear at the time corresponding to the initial moment of the imagination. In contrary, for the left-hand movement imagination, the meaningful changes in the parameters are observed for the data recorded from the right hemisphere. As the motor cortex is activated mainly contralaterally to the hand, the analysis of the FNS parameters allows to distinguish between the imagination of the right- and left-hand movement. This opens its potential application in the brain-computer interface.
闪烁噪声光谱法（FNS）是一种通过提取混沌信号中包含的信息来分析复杂非线性系统动力学的通用现象学方法。FNS的主要思想是用一组参数来描述隐藏在信号混沌分量中相关链接里的信息。在本文中，FNS用于分析与手部运动想象相关的脑电图信号。该信号已根据FNS方法进行参数化，并且在受试者想象运动时观察到FNS参数有显著变化。对于右手运动想象，从左半球记录的数据计算出的参数会出现突然变化（表现为一个峰值），出现在与想象初始时刻对应的时间。相反，对于左手运动想象，从右半球记录的数据观察到参数有有意义的变化。由于运动皮层主要是对侧于手部被激活，对FNS参数的分析能够区分右手和左手运动的想象。这开启了其在脑机接口中的潜在应用。
