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Revealing control mechanism from multifractal analysis on physiological signals

机译:从多重分形分析揭示生理信号的控制机制

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摘要

Multifractal theory has been widely used in various fields of research study. In this paper, methods were proposed to extract the multifractal descriptors of physiological signals from kinematic measurement of cervical spine region during postural sway when static sitting at upright position. The analysis is based on the multifractal detrended fluctuation analysis. The proposed multifractal parameters can be well described by variation space among the experimental subject group through acquisition of trials. Various analytical aspects of experiments have been conducted to verify the robustness and confidence of the proposed motor control mechanism. The exhibition of multifractality structure is hypothesized in describing various discharge of neural activity on motor control in order to balance the static posture through body sway. Variation on the long-range correlated structure can be found among subject groups. This is suggested as the reflection on coordinated behavior in the presence of external variation or pathological conditions. Both impersistent and persistent structures are observed in the multifractal spectrums from experiment. This reveals the relationship to the local and global neural interconnectivity, in which time scales can reflect local and progressively longer neighborhoods of neural interaction, within and outside the given spinal region. Results demonstrate that control mechanism can be revealed and knowledge discovered by means of the multifractal analysis and the extracted descriptors.
机译:多重分形理论已广泛应用于研究的各个领域。本文提出了从静坐直立状态下姿势摆动过程中颈椎运动学测量中提取生理信号的多重分形描述符的方法。该分析基于多重分形趋势波动分析。通过获得试验,实验对象组之间的变化空间可以很好地描述所提出的多重分形参数。已经进行了实验的各种分析方面,以验证所提出的电动机控制机构的鲁棒性和置信度。假设在描述运动控制中各种神经活动放电以平衡通过身体摇摆产生的静态姿势时,假设了多重分形结构的展示。远距离相关结构的变化可以在受试者组之间找到。建议将其反映为在存在外部变异或病理状况的情况下对协调行为的反思。在实验的多重分形光谱中观察到非连续和持久结构。这揭示了与局部和全局神经互连性的关系,其中时间尺度可以反映给定脊柱区域内外的局部和逐渐更长的神经交互作用邻域。结果表明,可以通过多重分形分析和提取的描述符来揭示控制机制并发现知识。

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