肌萎缩侧索硬化患者的腹直肌肌电图检测

目的：探讨腹直肌针极肌电图（EMG）在肌萎缩侧索硬化（ALS）中的诊断价值。方法：对ALS组58例患者进行常规EMG检测,包括上、下肢肌肉、胸锁乳突肌、下胸段脊旁肌及腹直肌,测定自发电位、募集相、运动单位电位（MUP）时限、波幅及多相波,对健康对照组36例健康志愿者进行腹直肌EMG的检测,比较ALS组与对照组腹直肌EMG的差异,以及ALS组中腹直肌EMG与下胸段脊旁肌EMG的差异。结果：健康对照组腹直肌EMG的MUP参数分别为波幅（389±35．7）μV,时限（9．78±1．23）ms,多相波（16．2±5．2）％;ALS组腹直肌EMG的MUP参数分别为波幅（675±135）μV,时限（12．78±1．03）ms,多相波（36．2±7．2）％,ALS组腹直肌EMG各参数与健康对照组比较差异有统计学意义;ALS组腹直肌EMG神经原性改变（43／58,74％）与下胸段脊旁肌EMG（39／58,67％）比较差异无统计学意义。结论：腹直肌EMG各参数均能可靠、稳定地测出,可作为诊断ALS患者胸段下运动神经元病变的辅助手段。     

自动分解肌电图运动单位动作电位各参数的分析和临床意义

目的：探讨运动单位动作电位（ＭＵＡＰ）各参数评价神经肌肉疾病的临床意义。方法：采用肌电图仪,以常规同心圆针电极记录,对７１例健康成人和４３例神经肌肉疾病患者的肱二头肌或／和胫前肌进行自动分解肌电图（ＡＤＥＭＧ）检测,共收集ＭＵＡＰ８３５６个,测定ＭＵＡＰ的５个参数：波幅、时限、转折数、发放率、棘波间隔变异系数（ＣＩＶ）。结果：１５例肌源性疾病患者表现为每一记录部位的ＭＵＡＰ数目增加;肱二头肌ＭＵＡＰ的波幅、时限、转折数减低、发放率增加,ＣＩＶ无改变;胫前肌ＭＵＡＰ的各参数无显著性改变。２８例神经源性疾病患者表现为每一记录部位的ＭＵＡＰ数目减少;ＭＵＡＰ的波幅、转折数及ＣＩＶ增加,时限及发放率无显著性增加。结论：ＡＤＥＭＧ检测的ＭＵＡＰ各参数对于评价神经肌肉疾病有重要的临床意义。     

高频超声观察不同训练动作对产后腹直肌分离间距的即时影响

背景：产后腹直肌分离具有较高的发病率,对产妇的身心健康造成了一定的不良影响。运动疗法是其主要的治疗方法之一,但何种运动方式能更有效地促进其修复,目前尚缺乏共识。目的：通过高频超声检查,观察卷腹运动、腹部中空运动、盆底肌收缩和联合运动4个训练动作对产后腹直肌分离间距的即时影响。方法：招募39例符合条件的腹直肌分离产妇,产后时间2-6个月。在静息状态、卷腹运动、腹式呼吸、盆底收缩、联合运动5个动作模式下,利用高频超声分别在受试者脐上4.5 cm、脐水平和脐下4.5 cm处对腹直肌分离间距进行测量。结果与结论：(1)脐上4.5 cm处,4个训练动作与静息状态相比,对腹直肌分离间距的影响差异均无显著性意义(均P> 0.05);脐水平处,卷腹运动与静息状态相比腹直肌分离间距显著减少(P <0.01),而联合运动与静息状态相比腹直肌分离间距增加(P <0.05);脐下4.5 cm处,卷腹运动与静息状态相比腹直肌分离间距减少(P <0.05),其他3个动作与静息状态相比,腹直肌分离间距虽有增加的趋势,但差异无显著性意义(均P> 0.05);(2)顺产组和剖腹产组相比,静...     

肌营养不良症患者肌电图诊断指标的研究

目的:探讨肌营养不良症的肌电图诊断方法的规范性,以利于临床的诊断和治疗.方法:以沈定国专著中我国正常人骨骼肌运动单位电位(MUP)、神经传导速度(NCV)等的正常值作为依据.收集临床确诊的肌营养不良症患者30例,以及正常对照组30例进行常规肌电图检测.结果:符合肌原性损害的占69.5%,还有少量表现为神经原性损害.在某些肌肉既有肌原性损害的特征,又有神经原性损害的特征.结论:肌营养不良症肌电图表现并非仅仅是肌原性损害,还有神经原性损害、肌原性一神经原性混合性损害,因此肌电图不是肌原性损害者亦不能否定肌营养不良症的诊断.     

从生物力学角度探讨腹直肌分离

腹直肌分离(diastasis recti abdominis, DRA)是产后并发症之一,常采用腹肌训练的方法促进其康复,但至今没有普遍可接受的训练模式及其相应理论支撑。本文从腹壁生物力学角度对DRA机制和康复效果进行综述,同时也分析了其争议的原因。主要原因包括腹直肌间距(inter-rectus distance, IRD)和腹肌厚度测量方法和测量部位的不统一,以及未能用生物力学方法探讨DRA发生机制等。因此,今后应规范DRA训练方法,研究DRA状态下的腹肌及其腱膜力学特征,为腹肌训练模式提供依据。     

肌营养不良症肌电图合并神经原性损害1例报告

1病例报告患者杨某,男,17岁。因2年前无明显诱因出现双下肢无力进行性加重人院。表现为上楼、爬楼梯及走路久后时感双下肢无力明显;无头昏、头痛,无吞咽困难及饮水呛咳,无肢体麻木、疼痛、双下肢肌肉跳动,无压痛。家族史中患者父母为近亲结婚,患者有2个姐姐,均未发病。否认其他家族成员中有类似疾病患者。门诊以“肌营养不良症”收入我科。     

腹直肌形态与肌内神经分布研究及其临床意义

目的:通过对腹直肌形态学、神经入肌点和肌内神经分支分布的研究,为腹直肌的临床肌移植提供形态学资料.方法:大体解剖法和改良Sihler's肌内神经染色法.结果:(1)腹直肌肌重(47.80±12.89)g,肌长(33.18±3.38)cm,肌宽(4.55±1.87)cm,肌厚(0.55±0.24)cm,腱划长(1.06±0.32)cm.(2)腹白:肌神经入肌点在肌深面肌宽的中、外1/3交界处,自上而下呈线形排列.(3)腹直肌受第7～12胸神终前支和第1腰神经前支支配,呈节段性、重替性分布.神经主干和分支在肌内走行不受腱划分隔的影响.结论:腹直肌由多神经节段性重叠性支配,神经在肌内的行程不受腱划影响.腹直肌的神经入肌点在肌深面肌宽的中、外1/3交界处.     

拮抗肌对运动单位平均发放率的变化关系研究

“共驱动”现象是近年来提出的探索人体随意运动过程中神经系统控制机理的新概念,通过对肘关节恒力收缩时主动肌和拮抗肌两种针电极肌电图（NEMG）信号的分解,估计运动单位（MU）的平均发放率（FR）,研究单块肌肉和拮抗肌对运动单位平均发放率随时间的变化趋势和相关关系,实验结果表明,无论肘关节作屈曲和伸展时,主动肌和拮抗肌两者的运动单位平均发放率均随时间而下降且无相移地高度相关,从而从关节水平上论证了神经肌肉系统“共驱动”现象的存在。     

腹直肌肌皮瓣的应用解剖及其肌内神经分布

目的:研究腹直肌肌皮瓣的血管、神经支配及其肌内神经分布与走行,为临床应用腹直肌肌皮瓣修复重建功能提供详尽的解剖学资料。方法:在新鲜成人尸体标本,完整取下腹直肌,观察测量肌外神经及血管支配,并采用改良Sihler肌内神经染色法观察肌内神经的分支分布。结果:腹直肌血液供应来自腹壁上、下动脉;神经支配来源于第8～12肋间神经,节段性支配腹直肌各个肌腹。结论:应以腹直肌内侧作为切取腹直肌肌皮瓣的手术入路,避免神经损伤;第9～12肋间神经是理想的供肌神经蒂;在利用腹直肌进行亚部游离移植时,宜选择腹直肌的上半部、下半部或者第3、第4肌腹。     

男性单侧腹直肌罕见缺失变异1例

目的 报道1例罕见的右侧腹直肌完全缺失并不伴有其他器官系统变异尸体的腹部解剖过程,腹壁肌群及其供血情况。 方法 解剖并观察尸体腹壁肌、血供、神经支配,对比两侧腹直肌发育和形态差异。 结果 该尸体右侧腹直肌缺失,腹直肌鞘完好,腹壁上动脉和腹壁下动脉仍在腹直肌鞘内走行并相吻合,肋间神经及肋下神经（T7～T12）由鞘内穿出达皮下。左侧腹直肌发育正常并有代偿性增生。男尸腹壁未见疤痕和手术切痕,腹内器官无缺失,腹膜除肝区外无黏连。 结论 该尸体右侧腹直肌缺失可能是胚胎发育第6周之前出现异常所导致。目前腹直肌肌皮瓣常用于多项外科重建手术,全面了解腹直肌的相关变异,对于扩展重建手术的应用范围和作好术前准备,确保手术成功均具有指导意义。     

Model for decomposition of the motor unit action potential 2 Analysis of simulated motor unit action potentials

A model for decomposition of the motor unit action potential (MUAP) which finds an optimal fit of a set of simulated single-fibre action potentials (SSFAPs) to the original MUAP is tested. The composition of SSFAPs which best produces the MUAP is assumed to carry information about the actual distribution of single-fibre action potentials generating the MUAP. Two methods are derived from the model. The first makes use of a fixed set of SSFAPs. In the second method, a gradually expanding set of SSFAPs is built, using a sequence of crosscorrelation, optimal reconstruction and subtraction. In the paper MUAPs are constructed under various well defined conditions. The MUAPs are decomposed by the two methods, and the results are compared with traditional MUAP parameters. Under these conditions, the model obtains parameters with closer biological connections compared with traditional measures.     

Resolving superimposed motor unit action potentials

A new algorithm to resolve superimposed motor unit action potentials (MUAPs) is described, which uses a reduced search space and is based on the peel off approach. Knowledge specific to the problem domain, such as temporal relationships between and within motor unit action potential trains and MUAP energy information, is used to reduce the search space of motor units, possibly contributing to a superposition. The algorithm is tested using real electromyographic signals, and it demonstrates robust performance across the signals tested. For the signals tested, the average total resolution rate is 94%, the average correct resolution rate is 99.2% and the average error rate is 0.85%.     

Motor unit action potential rate and motor unit action potential shape properties in subjects with work-related chronic pain

The objective of this study was to investigate differences in motor control of the trapezius muscle in cases with work-related chronic pain, compared to healthy controls. Ten cases with chronic pain and 13 controls participated in the study. Electromyographic (EMG) signals were recorded from the upper trapezius during five computer work-related tasks. Motor control was assessed using global root-mean-square value (RMS_G), motor unit action potential (MUAP) rate (number of MUAPs per second, MR) and two MUAP shape parameters, i.e. root-mean-square (RMS_MUAP) and median frequency (FMED_MUAP). MR and FMED_MUAP were higher for the cases than for the controls (P<0.05). RMS_MUAP showed a trend for higher values in the chronic pain group (P<0.13), whereas RMS_G did not show a significant difference between the groups. The higher MR, FMED_MUAP and the trend for higher RMS_MUAP suggest that more high-threshold MUs contribute to low-level computer work-related tasks in chronic pain cases. Additionally, the results suggest that the input of the central nervous system to the muscle is higher in the cases with chronic pain.     

Median averaging of electromyographic motor unit action potentials: comparison with other techniques

A technique of extracting individual motor unit action potentials (MUAPs) from EMG signals by median averaging, a modification of an existing method, is presented. To compare different techniques of MUAP extraction, 89 MUAPs were recorded with a concentric needle electrode in the brachial biceps muscle of normal subjects and patients with nerve and muscle diseases. MUAPs were also extracted by another method, called split-sweep median averaging, in which alternate MUAP discharges are averaged independently in two computer buffers until the two averaged signals appear equal on visual inspection by the operator. The amplitude, area, area: amplitude ratio, duration and number of phases and turns of each extracted MUAP were determined by each technique. Overall, there was a strong correlation between all features of the MUAPs extracted by median and splitsweep averaging, although the latter method required, on average, twice as many MUAP discharges to produce acceptable signals. We thus conclude that median averaging is a fast and accurate method that requires relatively few MU discharges to extract MUAP signals from spurious background signals.     

Robust supervised classification of motor unit action potentials

A certainty-based classification algorithm is described, which comprises part of a clinically used EMG signal decomposition system. This algorithm classifies a candidate motor unit action potential (MUAP) to the motor unit action potential train (MUAPT) that produces the greatest estimated certainty, provided this maximal certainty is above a given threshold. The algorithm is iterative, such that the certainty with which assignments are made increases with each pass through the data, and it has specific stopping criteria. The performance and sensitivity (to the assignment threshold) of the Certainty algorithm and an iterative minimum Euclidean distance (MED) algorithm are compared by classifying sets of MUAPs detected in real concentric needle-detected EMG signals, using a range of assignment thresholds for each algorithm. With regard to MUAP assignment and error rates, the Certainty algorithm consistently provides better mean results and, more importantly, less variable results than the MED algorithm. The Certainty algorithm can provide mean assignment and error rates of 80.8 and 1.5%, respectively, with a maximum error rate of 3.2%; the MED algorithm can provide mean assignment and error rates of 80.3 and 3.3%, respectively, with a maximum error rate of 6.5%. The Certainty algorithm is relatively insensitive to the certainty threshold used, can consistently differentiate between similarly shaped MUAPs from different MUAPTs, and can make correct classifications despite biological shape variability, background noise and signal shape non-stationarity.     

Model for decomposition of the motor unit action potential 1 The algorithm

A model for decomposition of the motor unit action potential (MUAP) into its constituent single-fibre action potentials is presented. It finds an optimal fit of a set of simulated single-fibre action potentials (SSFAPs) to the MUAP. The SSFAPs are assumed to originate from muscle fibres at different distances from the electrode, having various delays in time. Two methods for decomposition of the MUAP are derived from this model: first, that the MUAP is decomposed into a fixed set of SSFAPs; and secondly that the MUAP is decomposed into an adaptive, expanding set of SSFAPs. In the second method three steps are used repeatedly. First, the MUAP is cross-correlated with a collection of four SSFAPs. Then the most similar SSFAPs are used to reconstruct the original MUAP. The reconstruction thus obtained is subtracted from the original MUAP to detect activity not yet imitated. This difference (‘residual’) is again used for cross-correlation, restarting in step 1. After a suitable number of iterations, the MUAP is optimally imitated by a set of SSFAPs. The set of SSFAPs, obtained as described, is assumed to give information about underlying anatomical and physiological data (such as fibre number, fibre density, impulse dispersion) of the motor unit under study.     

Anatomical basis of rectus abdominis myo-cutaneous flaps

Summary The recent development of myo-cutaneous flaps and their use in plastic and reconstructive surgery prompted the authors to have a particular interest in musculo-cutaneous flaps of the rectus abdominis. From their personal studies and from a review of the literature, they consider the anatomical bases for these flaps and the different methods proposed for their construction. Finally they indicate their vast area of application which is essentially related to the wide range over which they can act.

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Bases anatomiques des lambeaux myo-cutanés de grand droit de l'abdomen

Résumé Le développement récent des lambeaux myocutanés et de leurs indications en chirurgie plastique et reconstructive, a amené les auteurs à s'intéresser plus particulièrement aux lambeaux musculo-cutanés de grand droit. A partir d'un travail personnel et d'une revue de la littérature, ils en rappellent les bases anatomiques et les différentes modalités proposées. Ils précisent enfin leur vaste domaine d'utilisation lié essentiellement à l'ampleur de leur rayon d'action.

     

运动单位电位多参数分析在肌原性损害中的诊断价值

目的 :探讨运动单位电位 (MUP)多项参数对肌原性损害的诊断价值。方法 :对 10例肌原性病变患者 ,采用棘波触发平均技术 ,得到股四头肌MUP 2 30个 ,肱二头肌MUP 190个 ,胫骨前肌MUP172个 ,对MUP多项参数进行定量分析 ,并与正常对照进行对比。结果 :各项参数与正常对照相比均有显著意义 (P <0 0 0 1～ 0 0 0 0 1) ,经 5 %可信限和均数 - 2 0标准差界值水平的显著性检验和相关性分析 ,证明时限与面积 /波幅比较大小指数、宽度高度指数和面积具有较高的诊断敏感性。结论 :时限与面积 /波幅比对肌原性损害的诊断作用最敏感 ,大小指数、宽高度指数与面积的诊断作用次之 ,波幅的诊断作用最小     

Adaptive motor unit action potential clustering using shape and temporal information

An adaptive algorithm is described that groups motor unit action potentials (MUAPs), detected in a composite EMG signal during signal decomposition, and creates partial motor unit action potential trains (MUAPTs). Data-driven MUAP shape and motor unit firing-pattern based criteria are used to form the clusters. An algorithm for estimating MUAPT temporal parameter, which provides accurate estimates even for partially defined trains, is used to obtain firing-pattern information. No a priori knowledge is required regarding the number of clusters or the distribution of their template shapes. The clustering algorithm when applied to real concentric-needle detected MUAP data provides accurate and useful clustering results. Compared to a classical leader-based algorithm, it provides more robust performance, is better able to estimate the true number of motor units represented in a set of detected MUAPs, and obtains more complete and accurate MUAPTs.