表面肌电信号的时变AR模型参数评估肌疲劳程度的研究

目的 本研究针对表面肌电信号的非平稳特性,采用时变参数AR模型的方法对表面肌电信号进行分析,实现对短时表面肌电信号的肌肉疲劳快速评估.方法 应用时变参数模型对10名受试者疲劳前、后的肌电信号进行特征提取,建立时变参数AR模型,并采用递推最小二乘算法求解模型的时变参数,将线性非平稳问题转化为线性时不变问题.结果 以时变参数AR模型的第一个时变参数的均值作为肌肉疲劳的快速指针.实验证明时变参数比传统的中值频率对疲劳反应的灵敏度高（提高范围为37.80%到324.46%）.结论 该方法可以实现对短时表面肌电信号的肌肉疲劳快速评估,为腰肌劳损的诊断和康复治疗,以及人体工效学的研究提供一个可靠的工具.     

表面肌电信号的时变AR模型参数估计及其在下腰痛评估中的应用研究

本文针对表面肌电信号的非平稳特性,采用时变参数AR模型对表面肌电信号进行分析,将线性非平稳问题转化为线性时不变问题,并采用递推最小二乘算法求解模型的时变参数.在此基础上,提出了结合奇异值分解进行参数优化,进而进行模式分类的方法.能够成功地区分下腰痛患者治疗前后的状态,为下腰痛的诊断、治疗与康复判定奠定了一定的基础.     

基于幅频联合分析法对肌肉疲劳状态下表面肌电信号时、频域变化规律的研究

目的:通过对肌肉疲劳状态下表面肌电信号(sEMG)的提取,利用幅频联合分析的方法探讨sEMG作为肌肉生理特征信号在疲劳发生过程中的变化规律。方法:5名健康男性左右手臂分别进行一次实验,实验过程中,手臂自然下垂,前臂抬起至水平,与上臂成90°角,前臂上悬挂重量为5 Kg的重物,使肌肉等长收缩8 min,采用英国BIOPAC公司生产的MP150及其肌电采集模块同步记录肌肉的表面肌电信号,使用The MathWorks公司的MATLAB7.0软件,在信号3min、5 min、7 min后各取20 s进行幅频联合分析。结果:sEMG随着肌肉疲劳状态的加剧,信号幅值平均值明显增大,功率谱密度发生变化,平均功率频率(MPF)、中位频率(MF)明显减小。结论:表面肌电信号的幅频联合分析法为进一步深入研究肌肉疲劳状态下表面肌电信号的变化提供了方法支撑和理论依据。     

基于小波变换的肌肉疲劳表面肌电信号特征提取的研究

当前肌肉疲劳表面肌电信号(surface electromgography,sEMG)特征提取方法,忽略了非线性跳错信号的影响,且不能在非平稳状态下进行特征提取,存在特征提取准确度差的问题。提出基于小波变换的肌肉疲劳sEMG特征提取研究,采用小波变换对所采集的样本去噪,结合时域、频域特征分析法,融合傅里叶变换方法对肌电信号中的线性特征进行提取,根据带谱近似熵理论对非线性挑错信号进行特征回归分析,并利用拟态分解函数和希尔伯特变换法对肌电信号进行时频特征的整合提取,最终完成基于小波变换的肌肉疲劳sEMG特征提取研究。实验验证,所提方法具有可行性,且将1000个肌电信号样本分成5组,对其中的跳错信号进行特征提取,所提方法准确度较文献方法高出75%,在非平稳状态下将200个肌电信号样本分成5组进行特征提取,所提方法准确度较文献方法高出33%。由此得出,所提方法优于当前特征提取方法。     

利用表面肌电信号评价肌肉疲劳的方法

表面肌电信号分析是评价局部肌肉疲劳有效的工具。过去由于受信号处理技术的限制,对肌肉疲劳的评价仅局限于等长、恒力收缩。由于适合于非平稳信号分析的频谱估计技术的发展,使得动态收缩条件下的肌肉疲劳评价得以实现,在工效学、康复医学和运动医学等方面开启了新的应用领域。本文论述了利用表面肌电信号评价肌肉疲劳,特别是在肌肉动态收缩期间评价肌肉疲劳的方法,为进一步探讨肌肉疲劳的发生机制提供理论依据。     

长时间颈部后仰相关局部肌肉表面肌电特征分析

目的 为降低长时间颈部后仰对航空机务人员身心健康造成影响,探讨航空机务人员在托举作业过程中长时间保持颈部后仰姿势对颈部肌肉表面肌电的影响。方法 择12名在校大学生作为研究对象,受试者站立在飞机机翼下方保持颈部后仰固定姿势模拟机务人员进行托举作业,记录受试者主观疲劳感觉评分(rating of perceived exertion, RPE),同时采集斜方肌、胸锁乳头肌和颈部夹肌的表面肌电信号,分析并计算肌电信号均方根(root mean square, RMS)、积分肌电(integral electromyography, iEMG)、中值频率(median frequency, MF)和平均功率频率(mean power frequency, MPF),并结合主观疲劳感觉评分进行相关性和回归分析。结果 胸锁乳突肌、斜方肌和颈部夹肌的iEMG和RMS变化与托举时间呈正相关关系,其中颈部夹肌的iEMG和胸锁乳突肌RMS相关程度最高,其相关系数分别为0.48和0.84,拟合程度分别为0.69和0.71,差异具有统计学意义(P<0.05);胸锁乳突肌、斜方肌和颈部夹肌的MPF和MF变...     

基于低频电刺激诱发表面肌电信号的肌肉疲劳度研究

目的 通过对肌肉疲劳过程中非诱发表面肌电(surface electromyography,sEMG)信号和诱发表面肌电信号的研究分析,寻找有效评价肌肉疲劳的分析测量方法.方法 对7名受试者进行自主运动和电刺激两种致肌疲劳的实验,并在两组实验中分别记录电刺激诱发与非诱发肌电信号,然后对每组信号进行傅里叶变换求取功率谱和近似熵.结果 随着疲劳的产生,两组实验诱发信号的频谱曲线左移效果优于非诱发信号,近似熵分析中电刺激组诱发信号出现先上升后下降的变化,自主运动组诱发信号则呈现单调递减的趋势.结论 低频电刺激诱发表面肌电信号更适于测量肌疲劳的动态变化.相对于传统功率谱,近似熵分析方法更适于处理电刺激诱发的表面肌电信号.     

基于表面肌电的人体背部负重行走肌肉疲劳特性研究

通过研究人体双肩背部负重行走时躯干及下肢主肌肉群表面肌电信号,探讨人体肌肉功能状态和疲劳特性,为改进负重方式、负重方法、背包性能、背包设计以及更加符合人体工效学的负重系统提供依据。测试20名实验对象颈肩部、背腰部及腿部主肌肉群在双肩背不同负重载荷下行走的表面肌电信号,利用统计分析软件SPSS16.0对其频域评价指标平均功率频率(MPF)进行数据处理与分析。结果表明,随着负重的增加,男性受试者斜方肌MPF下降最为显著、最易疲劳,女性受试者颈伸肌MPF下降最为显著、最易疲劳,且当负重达到一定重量时表面肌电信号出现显著差异(P0.05),男性双肩背负重上限值为自身体重的12%,女性双肩背负重上限值为自身体重的9%。     

神经肌肉电刺激诱发的下肢运动疲劳信息检测与处理技术研究

限制神经肌肉电刺激(NMES)广泛应用的一个主要因素就是由其诱发的肌疲劳.设计NMES诱发下肢运动条件下的肌疲劳检测系统.分别进行膝关节角度的检测和表面肌电信号(sEMG)的频谱分析.研究表明,平均频率(MNF)、中值频率(MDF)及AR时变参数模型参量是评价NMES诱发肌疲劳的可靠指标,并且AR模型具有显著的高分辨灵敏度,最大变化率为90.23％,大于平均频率的43.82％和中值频率的55.49％,为NMES使用过程中诱发肌疲劳的准确评价和反馈寻找到一种可行的方法.     

基于平移不变小波变换的颈肩肌电信号去噪方法研究

在采用肌电信号进行颈肩肌肉疲劳特性分析中,为提高非平稳表面肌电信号(surface electromyography,SEMG)的信噪比,抑制传统强制去噪时在信号奇异点处产生的伪吉布斯(Gibbs)现象,采用平移不变(translation invariance,TI)小波新阈值去噪的方法对肌电信号进行去噪。实验表明,该方法在保留颈肩肌电信号主要特征的前提下,与传统强制去噪方法比较,信号的信噪比(signal-noise ratio,SNR)提高了7倍,均方根误差(root mean square error)降低为原来的四分之一,故该方法更适合在充分保留肌电信号细节特征的前提下,去除颈肩肌电信号中的白噪声和50 Hz工频谐波干扰。     

Changes in soleus motoneuron pool reflex excitability and surface EMG parameters during fatiguing low- vs. high-intensity isometric contractions

The fatigue-related changes in soleus motoneuron pool reflex excitability and surface electromyography (EMG) parameters, and maximal voluntary contraction (MVC) force of the plantarflexor (PF) muscles during repeatedly sustained low- (30% MVC) vs. high-intensity (70% MVC) isometric contractions were evaluated Twelve young men with mean (+/- SE) age of 22.4 +/- 0.3 years participated in two fatigue tasks on separate days with at least 1-week interval. The fatigue task consisted of three sustained isometric contractions of PF muscles at a target force level until exhaustion separated with 2-min pause between contractions. M-wave (muscle compound action potential) amplitude (M(max)), Hoffmann reflex maximal amplitude (H(max)) to M-wave amplitude ratio (H(max)/M(max)), and root mean square amplitude (RMS) and median frequency (MF) of EMG power spectrum were recorded from the soleus muscle. The M(max) remained constant immediately post-fatigue and during recovery for low- and high-intensity fatigue tasks, whereas H(max)/M(max) was significantly (p < 0.05) reduced only after high-intensity fatigue task. The increase in RMS and decrease in MF during isometric contractions, and reduction in MVC force immediately after the exercise was greater (p < 0.05) for low-intensity fatigue task. We conclude that low-intensity isometric contractions, repeatedly sustained to fatigue, resulted in a marked increase in the EMG amplitude and spectral compression without a significant post-fatigue reflex inhibition of soleus motoneuron pool. High-intensity contractions, however, resulted in post-fatigue reflex inhibition of soleus motoneuron pool and less pronounced EMG spectral compression during fatiguing contractions. A failure of neuromuscular transmission-propagation was not evident after repetitive fatiguing isometric contractions.     

The application of Hilbert�CHuang transform in the analysis of muscle fatigue during cyclic dynamic contractions

Surface electromyography (sEMG) is a common technique used in the assessment of local muscle fatigue. As opposed to static contraction situations, sEMG recordings during dynamic contractions are particularly characterised by non-stationary (and non-linear) features. Standard signal processing methods using Fourier and wavelet based procedures demonstrate well known restrictions on time-frequency resolution and the ability to process non-stationary and/or non-linear time-series, thus aggravating the spectral parameters estimation. The Hilbert-Huang transform (HHT), comprising of the empirical mode decomposition (EMD) and Hilbert spectral analysis (HSA), provides a new approach to overcome these issues. The time-dependent median frequency estimate is used as muscle fatigue indicator, and linear regression parameters are derived as fatigue quantifiers. The HHT method is utilised for the analysis of the sEMG signals recorded over quadriceps muscles during cyclic dynamic contractions. The results are compared with those obtained by the Fourier and wavelet based methods. It is shown that HHT procedure provides the most consistent and reliable assessment of spectral and derived linear regression parameters, given the time epoch width and sampling interval in the time domain. The suggested procedure successfully deals with non-stationary and non-linear properties of biomedical signals.     

Lumbar paraspinal muscle fatigability in repetitive isoinertial loading: EMG spectral indices, Borg scale and endurance time

The purpose of this study was to develop a submaximal repetitive isoinertial back muscle endurance test by defining the relationships between the power spectral indices of paraspinal muscle electromyographic (EMG) activities, endurance time and a subjective estimate of fatigue (Borg scale). Bilateral surface EMG recordings were obtained over the lumbar paraspinal muscles in ten individuals who were currently free from back pain. All subjects performed repetitive upper trunk extensions (25° flexion and 5° extension, 30 repetitions per min), while movement below the third lumbar vertebral body was mechanically restricted. The load level depended upon upper body mass, sex, and age. The tests continued for as long as the subjects were able to maintain the required repetition rate (endurance time). Median (MF) and mean power frequency (MPF) slopes were calculated by performing a fast Fourier transformation after confirmation of EMG stationarity by recurrence quantification analysis. MF and MPF correlations with endurance time/Borg scale were measured for the first 60 s (0.60–0.88/0.42–0.86), the first 90 s (0.62–0.89/0.52–0.90), the first 120 s (0.50–0.76/0.41–0.73), and the entire repetitive run (0.63–0.88/0.54–0.90). To test for the reproducibility of the spectral indices, EMGs were recorded for 2 min during repetitive loading from the same subjects on two consecutive days. Corresponding spectral slopes of MF and MPF were correlated at 60 s (0.36–0.93), 90 s (0.58–0.92), and 120 s (0.70–0.94) at the L3–L4 and L5–S1 levels, indicating good reproducibility of results from alternate recording sessions at the L5–S1 level. It is concluded that paraspinal muscle spectral indices (MF and MPF) measured before the onset of total muscle fatigue are good predictors of endurance time and are closely related to the subjective perception of fatigue.     

膝关节骨性关节炎推拿手法的力学特征和上肢核心肌群的疲劳研究

探讨膝关节骨性关节炎推拿手法的生物力学特征和生理学(表面肌电)特征,定量分析推拿手法的力学指标,建立一种客观评价推拿医生上肢核心肌群的疲劳状况的方法。招募10位推拿科医生,实时采集推拿医生拇指垂直压力和上肢表面肌电信号,研究垂直强度、次做功期与主做功期的时间比;研究操作该推拿手法时的上肢核心肌群;研究核心肌群的疲劳状况。结果表明,该推拿手法1 min内按压4次,平均垂直强度为(228±13)N,主做功期持续时间为(4.83±0.88)s,次做功期持续时间为(11.43±1.94)s,有效做功时间比为2.37±0.63。由上肢各肌肉群的平均积分肌电值(iEMG)和贡献率的降序可知,手法涉及上肢的核心肌群为拇短展肌(8.32±0.29,21.65%)、尺侧腕屈肌(5.67±0.32,14.74%)、肱三头肌(4.79±0.36,12.46%)、桡侧腕屈肌(4.60±0.12,11.96%)。在4 min的推拿过程中,拇短展肌的平均中值频率(MF)和平均功率频率(MPF)的下降程度是最大的,分别为30%和22%,即拇短展肌更易发生疲劳。因此,所研究的膝关节骨性关节炎推拿手法的生物力学特征和生理学(表面肌电)特征,为后续的人因工程研究和研制可替代推拿医生手法的自动化装置奠定良好的基础。     

Comparison of different estimators of electromyographic spectral shifts during work when applied on short test contractions

EMG was recorded during short test contractions performed during occupational work. Mean power frequency (MPF) and median frequency (MF), calculated from EMG spectra, and zero crossing rate (ZC) of the EMG signal were compared as estimators of local muscular fatigue. The results show that there is a systematic difference between the three estimates. The difference can be explained by dividing the effect of muscle fatigue on EMG spectra into a motor unit action potential velocity effect and a firing statistics effect. Furthermore, it is shown that the phenomenon of increasing estimators of EMG spectrum shift is unlikely to be caused by motor unit action potential velocity increase. Successive recruitment of new motor units is suggested as a feasible explanation.     

驾驶人背部肌肉负荷定量研究

使用表面肌电图（sEMG）技术测定驾驶人躯干肌肌肉活动,定量驾驶人背部肌肉负荷水平。选取8名健康男性大学生作为受试者,有驾驶资质,右利手。在驾驶模拟器上以80 km/h的速度匀速驾驶。模拟器场景为三车道直道的自编场景,受试者在中间车道行驶共120 min,同步记录躯干肌中左右腰竖脊肌（LES和RES）和左右多裂肌（LMM和RMM）的肌电信号。在模拟驾驶前,测试LES、 RES、 LMM和RMM的最大自主收缩力（MVC）,以此作为数据处理的基值,并测试模拟驾驶前后受试者30%MVC的肌电信号。对等长肌肉收缩期肌电信号（即30%MVC肌电信号）进行分析,时域分析指标为参考随意收缩肌电百分比（%RVE）和频域分析指标为中位频率（MF）平均功率频率（MPF）。对连续驾驶期间肌电信号采用振幅概率分布频率（APDF）方法进行分析。时域指标结果显示, LES、RES、LMM和RMM模拟驾驶前后%RVE值均显著上升（P<0.05）;频域指标结果显示,模拟驾驶前后LES、RES、LMM和RMM的MF30%MVC值及MPF_30%MVC值均下降,经检验RES和RMM模拟驾驶前后的MF_30%MVC值及RMM驾驶前后MPF_30%MVC值差异有显著性（P<0.05）。APDF分析结果表明,连续驾驶期间,LES、RES、LMM和RMM的肌肉负荷水平分别为7.55%±5.64%、5.78%±3.06%、6.13%±3.76%和5.69%±3.41%,为低负荷水平作业。sEMG研究表明,在连续驾驶期间,驾驶人的背部肌肉产生疲劳,躯干肌疲劳程度左侧高于右侧;在连续驾驶期间,背部肌肉负荷水平为持续低水平负荷。     

EMG power spectrum as a measure of muscular fatigue at different levels of contraction

The shift in the power spectrum resulting from a 5-7 min fatigue-inducing effort followed by a 1-2 min recovery period of two elbow flexors, the biceps brachii (BB) and the brachio-radialis (BR), was assessed using two variables, the mean frequency Fm and the median or central frequency Fmd. These two variables were calculated in pre- and post-fatigue conditions and following a brief recovery, at four levels, namely 20, 40, 60 and 80 per cent of maximum voluntary contraction (MVC). These were taken from a ramped isometric effort that is from 0 to 100 per cent MVC. The EMG activity of the two flexors was recorded with bipolar surface electrodes from a group of ten volunteers. Following muscle fatigue, induced with a maintained 60 per cent MVC isometric contraction, a statistically significant (p less than 0.05) shift towards the lower frequencies was observed for both Fm and Fmd for both muscles. Following a brief recovery, a shift towards the pre-fatigue higher frequencies was statistically significant (p less than 0.05). These two synergists responded to muscle fatigue and recovery similarly, as they both demonstrated parallel shifts in power spectrum. The power spectrum is consequently a reliable measure of muscular fatigue. It is also complementary to the net articular moment results.     

Relationship between average muscle fibre conduction velocity and EMG power spectra during isometric contraction,recovery and applied ischemia

Summary The relationship between muscle fibre conduction velocity (MFCV) and the power spectrum of surface EMGs in 3 human volunteers was studied during isometric contractions at 40% maximum voluntary contraction. In addition, the recovery of these two parameters was measured during short lasting contractions at the same force level every 30 s. The recovery phase was also studied during ischaemia, thereby preventing the recovery of MFCV.The mean MFCV was calculated by the cross-correlation method. The measurements were facilitated by a real-time estimation of the cross-correlation and the MFCV and by a graphic display of the digitised signal.During contraction a nearly linear relation was found between MFCV and the median frequency of the power spectrum (MPF). During recovery this relationship was lost in one subject: MPF restored much faster then MFCV. During recovery under ischemia MFCV did not recover, but MPF recovered partially in all subjects.It is concluded that the shift of the power spectrum to lower frequencies during fatigue cannot be explained by changes in MFCV alone. Central mechanisms also influence the power spectrum and studying the recovery of local muscle fatigue during ischemia may separate these influences from that of MFCV on the power spectrum during fatigue.     

Development of muscle fatigue as assessed by electromyography and mechanomyography during continuous and intermittent low-force contractions: effects of the feedback mode

The goal of the present study was to investigate the significance of low-force continuous or intermittent static contraction and feedback mode (visual or proprioceptive) on the development of muscle fatigue as assessed by electromyography (EMG) and mechanomyography (MMG). Visual (force control) and proprioceptive (displacement control) feedback was investigated during intermittent (6 s contraction, 4 s rest) and continuous static contractions at 10% and 30% of the maximum voluntary contraction (MVC). Mean force, force fluctuation, rating of perceived exertion and root mean square (RMS) and mean power frequency (MPF) of the EMG and MMG signals were analysed. The general pattern for MMG RMS and EMG RMS values and the rating of perceived exertion was an increase with contraction time, while the EMG MPF values decreased (P<0.05). The increase in RMS values was generally more pronounced for the MMG compared with the EMG, while the decrease in MPF values was more consistent for the EMG compared with the MMG signal. During the intermittent contractions, the main effect was on MPF for both EMG and MMG. Lower force fluctuation and larger rating of perceived exertion (P<0.05), greater slopes of EMG and MMG RMS and MPF values versus time were observed with proprioceptive feedback compared with visual feedback. The findings suggest that (1) the EMG and MMG signals give complementary information about localised muscle fatigue at low-level contraction: they responded differently in terms of changes in the time and frequency domain during continuous contraction, while they responded in concert in the frequency domain during intermittent contractions, and (2) the different centrally mediated motor control strategies used during fatiguing contraction may be dependent upon the feedback modality. Electronic Publication