通过分形维对表面肌电信号进行识别分类。
Surface electromyogram (EMG) signals were identified by fractal dimension.
介绍了表面肌电信号数字传感器的设计方法。
Design of surface electromyography digital transducer was discussed.
表面肌电信号分析是评价局部肌肉疲劳有效的工具。
Surface myoelectric signal analysis has been proved effective for assessing the electrical manifestations of localized muscle fatigue.
提出了一种基于基本尺度熵的表面肌电信号特征的提取方法。
According to the chaotic characteristic of surface electromyography signal, a novel method that USES basic-scale entropy to extract feature from surface electromyography signal (SEMG) was proposed.
表面肌电信号分析技术是近年来日渐完善的腰部肌肉功能评价方法。
In recent years, the analysis skill of SEMG has become a better way to evaluate the function of lumbar muscle.
目的：研究肌肉疲劳过程中表面肌电信号的特征，实现疲劳状态的定量描述。
Objective:To study the characteristics of surface electromyogram(EMG) signals and to realize the quantitative analysis during muscle fatigue.
表面肌电信号（SEMG）是使用方便且无痛苦的表面电极测得的肌电信号。
Surface electromyography (SEMG) has been proved to be a successful method of non-invasive measurement of EMG.
采用可重复性好、受噪声影响小的电刺激方式诱发表面肌电信号（SEMG）。
Electrically evoked SEMG signals which are high repeatability and little influenced by noise were adopted in the experiment.
目的应用表面肌电信号(SEMG)技术对重复性搬举所致的竖脊肌疲劳进行评价。
Objective Using surface electromyography (SEMG) technique to evaluate repetitive lifting task induced fatigue of back muscles.
表面肌电信号是一种复杂的表皮下肌肉活动在皮肤表面处的时间和空间上的综合结果。
The surface electromyogram(SEMG) signals are the time and space synthesis result of complicated muscle electricity active on the top of the skin.
目的：设计一种简单的拾取电路采集表面肌电信号，拟应用于动作肌电信号的特征识别。
OBJECTIVE:To design a detection circuit according to the characteristics of the sEMG, which can pick-up the SEMG signals for action recognition.
如何方便有效地采集提取表面肌电信号(SEMG)已成为SEMG应用的关键技术之一。
How to acquire and extract surface electromyography (SEMG) expediently and effectively had been one of the key factors to apply the SEMG.
这种方法可以用于人手动作的识别，为研究多自由度假手表面肌电信号控制方法提供了新途径。
Thus, it provides an alternative novel approach to use the surface EMG in control the multi-freedom prosthetic hand.
结论该方法模拟出的SEMG信号更能逼近真实表面肌电信号的特征，可用于验证SEMG分解算法。
Conclusion the simulated SEMG signal based on this method has key characters similar to those of the real SEMG, and it can be used to test the decomposition algorithms.
试验结果表明，采用该SEMG检测电极可以进一步提高信噪比，减少噪声，提取到有效的表面肌电信号。
The Experimental result shows that the SEMG detection electrode can further improve SNR, reduce the noise and get effective surface electromyographic signal.
当一块肌肉完成持续的收缩时，所记录的表面肌电信号的分析是一个用于评价局部疲劳进行性的有用的工具。
The analysis of the surface myoelectric signal is a valuable and the signal is recorded while a muscle is performing a sustained contraction tool for assessing the progression of localized fatigue.
表面肌电信号的检测是一种无创电检测方法，它的检验分析对临床诊断及康复医学、运动医学等具有重要意义。
The detection of surface EMG signal is a noninvasive method, which has great importance in clinical diagnosis, rehabilitation medicine and sport medicine.
采用基于二阶统计量的盲源分离算法对多导表面肌电信号进行处理，实现噪声的分离和表面肌电信号的初步分解。
Some methods of SEMG signal pretreatment based on blind source separation using second order statistics were proposed for noise separation and the elementary decomposition of multi-channel SEMG.
利用隐马尔克夫模型与支持向量机相结合，对站立和行走过程中的下肢表面肌电信号进行分类，用来控制多功能假肢。
Classifying myoelectric signals using hidden Markov model and support vector machine to process myoelectric signals, with the task of discrimination five classes of multifunction prosthesis movement.
方法14名受试者分别参加肱二头肌和腰部脊竖肌等长运动负荷实验，取表面肌电信号进行FF T功率谱及其功率谱二维地形图分析。
Methods Static isometric loading of the biceps and low back muscle was performed in 14 subjects, using FFT power spectrum and its two dimensional mapping to analyze SEMG signals from these muscles.
目的通过表面肌电探讨腰椎间盘突出症腰部肌肉和下肢肌肉失衡的可能依据，并试图建立一种检测下肢腓肠肌表面肌电信号的实验方法。
ObjectiveTo explore the reason of imbalance for the lumbar and lower limb muscles by observing sEMG; Trying to establish a method of detecting sEMG for gastrocnemius.
将一维的表面肌电信号转换为二维的散点图，在这二维的平面空间中研究散点在一周360度的各个方向上的分布情况，提出了象限信息熵的概念。
Converte the one dimension time series into two dimension spot figure, then study the distribution of the spot around the 360 degree directions, compute the quadrant information entropy.
本文旨在通过分析肌肉在静动态收缩的过程中表面肌电特征参数的变化，研究肌电信号中的疲劳特征。
The purpose of this thesis is to analyze the characteristic parameters of sEMG during muscle static and dynamic contractions, and to study sEMG characteristics of muscle fatigue.
肌电信号是在皮肤表面记录下来的神经和肌肉的系统活动时的生物电信号，有很好的临床价值。
EMG signal is an one-dimensional time series signal of neuromuscular system, which is very helpful for doctors to analysis the illness of patients.
肌电信号是在皮肤表面记录下来的神经和肌肉的系统活动时的生物电信号，有很好的临床价值。
EMG signal is an one-dimensional time series signal of neuromuscular system, which is very helpful for doctors to analysis the illness of patients.
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