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针电极检测运动单位电位序列的自动抖动测量。

Automatic jitter measurement in needle-detected motor unit potential trains.

机构信息

Department of Electrical, Electronics and Communication Engineering, Public University of Navarra, Campus de Arrosadía, 31006, Navarra, Spain.

System Design Engineering Department, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada.

出版信息

Comput Biol Med. 2022 Oct;149:105973. doi: 10.1016/j.compbiomed.2022.105973. Epub 2022 Aug 18.

DOI:10.1016/j.compbiomed.2022.105973
PMID:36099861
Abstract

In an active motor unit (MU), the time intervals between the firings of its muscle fibers vary across successive MU activations. This variability is called jitter and is increased in pathological processes that affect the neuromuscular junctions or terminal axonal segments of MUs. Traditionally, jitter has been measured using single fiber electrodes (SFEs) and a difficult and subjective manual technique. SFEs are expensive and reused, implying a potential risk of patient infection; so, they are being gradually substituted by safer, disposable, concentric needle electrodes (CNEs). As CNEs are larger, voltage contributions from individual fibers of a MU are more difficult to detect, making jitter measurement more difficult. This paper presents an automatic method to estimate jitter from trains of motor unit potentials (MUPs), for both SFE and CNE records. For a MUP train, segments of MUPs generated by single muscle fibers (SF MUP segments) are found and jitter is measured between pairs of these segments. Segments whose estimated jitter values are not reliable, according to several SF MUP segment characteristics, are excluded. The method has been tested in several simulation studies that use mathematical models of muscle fiber potentials. The results are very satisfactory in terms of jitter estimation error (less than 10% in most of the cases studied) and mean number of valid jitter estimates obtained per simulated train (greater than 1.0 in many of the cases and less than 0.5 only in the most complicated). A preliminary study with real signals was also performed, using 19 MUP trains from 3 neuropathic patients. Jitter measurements obtained by the automatic method were compared with those extracted from a commercial system (Keypoint) and the edition and supervision of an expert electromyographer. From these measurements 63% were taken from equivalent interval pair sites within the time span of the MUP trains and, as such, were considered as compatible measurements. Differences in jitter of these compatible measurements were very low (mean value of 1.3 μs, mean of absolute differences of 2.97 μs, 25% and 75% percentile intervals of -0.85 and 3.82 μs, respectively). Although new tests with larger number of real recordings are still required, the method seems promising for clinical practice.

摘要

在活跃的运动单位 (MU) 中,其肌肉纤维的发射时间间隔在连续的 MU 激活中会有所不同。这种可变性称为抖动,并且在影响神经肌肉接头或 MU 末端轴突段的病理过程中会增加。传统上,抖动是使用单纤维电极 (SFE) 和困难且主观的手动技术来测量的。SFE 昂贵且可重复使用,这意味着患者感染的潜在风险;因此,它们正逐渐被更安全、一次性、同心针电极 (CNE) 取代。由于 CNE 更大,单个 MU 纤维的电压贡献更难检测,从而使抖动测量更加困难。本文提出了一种从运动单位电位 (MUP) 中自动估计抖动的方法,适用于 SFE 和 CNE 记录。对于 MUP 序列,找到由单个肌肉纤维产生的 MUP 序列段,并测量这些段之间的抖动。根据几个 SF MUP 段特征,将那些估计的抖动值不可靠的段排除在外。该方法已在使用肌肉纤维电位数学模型的多项模拟研究中进行了测试。在大多数情况下,抖动估计误差小于 10%,许多情况下每个模拟序列获得的有效抖动估计数大于 1.0,只有在最复杂的情况下才小于 0.5,结果非常令人满意。还使用来自 3 名神经病变患者的 19 个 MUP 序列进行了初步的真实信号研究。自动方法获得的抖动测量值与从商业系统 (Keypoint) 提取的值以及专家肌电图医师的编辑和监督进行了比较。从这些测量值中,有 63% 来自 MUP 序列时间范围内的等效间隔对位点,因此被认为是兼容的测量值。这些兼容测量值的抖动差异非常低(平均值为 1.3 μs,平均值绝对差异为 2.97 μs,25% 和 75% 分位数区间分别为-0.85 和 3.82 μs)。尽管仍需要进行更多具有更大数量真实记录的新测试,但该方法似乎很有希望应用于临床实践。

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