通过基于复杂性的肌电图(EMG)信号分析,解码眼外肌的激活状态

Fractals Pub Date : 2024-04-03 DOI:10.1142/s0218348x24500671
SRIDEVI SRIRAM, KARTHIKEYAN RAJAGOPAL, ONDREJ KREJCAR, HAMIDREZA NAMAZI
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引用次数: 0

摘要

分析眼外肌的激活情况对于了解眼球运动模式、洞察眼球运动控制以及促进视觉研究、神经学和生物医学工程等领域的进步至关重要。十名受试者在记录肌电图(EMG)信号的同时进行了实验,包括正常注视、眨眼、眼球向上和向下运动以及眼球向左和向右运动。我们利用分形理论、样本熵和近似熵(ApEn)分析了记录的肌电信号的复杂性。结果表明,这些技术能够解码不同眼球运动之间肌电信号复杂性的变化。换句话说,我们可以利用这些方法来研究不同条件下的眼外肌激活情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DECODING OF THE EXTRAOCULAR MUSCLES ACTIVATIONS BY COMPLEXITY-BASED ANALYSIS OF ELECTROMYOGRAM (EMG) SIGNALS

The analysis of extraocular muscles’ activation is crucial for understanding eye movement patterns, providing insights into oculomotor control, and contributing to advancements in fields such as vision research, neurology, and biomedical engineering. Ten subjects went through the experiments, including normal watching, blinking, upward and downward movements of eyes, and eye movements to the left and right while their electromyogram (EMG) signals were recorded. We analyzed the complexity of recorded EMG signals using fractal theory, sample entropy, and approximate entropy (ApEn). The results showed that the techniques are able to decode the changes in the complexity of EMG signals between different eye movements. In other words, we can use these methods to study extraocular muscle activations in different conditions.

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