设计基于随机发射模式的肌电信号发生器

Gabriela León, Emely López, Hans López, Cesar Hernández
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引用次数: 0

摘要

肌电图(EMG)信号表现出复杂的干扰模式,由多个单运动单元动作电位(SMUAP)组成。目前还缺乏能生成 EMG 信号并考虑长程依赖性 (LRD) 或短程依赖性 (SRD) 等内在特征的模型,或支持病理相关信号研究的模型。因此,本研究旨在开发一种基于发射模式衍生的 SRD 或 LRD 的肌电信号发生器。我们使用动态模型对从数据库中提取的真实肌电信号的多达 15 个 SMUAP 波形进行参数化。然后,我们使用基于 SMUAP 数量的某些信号的相对出现率来随机生成后者。此外,我们还通过生成随机点火模式来补充我们的模型。信号的合成重建结果表明,与各自的点火模式相比,信号出现了位移,最高误差率为 4.1%。目前状态下的肌电信号发生器模型对于有意研究信号行为的专家来说非常有用,他们可以从合成信号的探索开始,然后再研究真实信号。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of an EMG Signal Generator Based on Random Firing Patterns
Electromyographic (EMG) signals exhibit complex interference patterns that comprise several single motor unit action potentials (SMUAPs). Evidence of a model that can generate EMG signals and considers intrinsic characteristics, such as long-range dependence (LRD) or shortrange dependence (SRD), or that supports the study of pathology-related signals is lacking. Therefore, the present study aimed to develop an EMG signal generator based on SRD or LRD derived from firing patterns. We used a dynamic model to parameterize up to 15 SMUAP waveforms of real EMG signals extracted from a database. Then, we used relative appearance rates for some signals based on the number of SMUAPs to generate the latter randomly. Furthermore, we complemented our model by generating a random firing pattern. The synthetic reconstruction of the signals indicated a displacement compared with their respective firing patterns, with the highest error rate being 4.1%. The model of the EMG signal generator in its current state could be useful for a specialist who intends to study the behavior of the signals, starting with the exploration of synthetic signals and then proceeding to the real signals.
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