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- Complexity Analysis of Surface EMG Signals. 表面肌电信号的复杂度特征研究。
- The system acquires images and force and surface EMG signals on line in one computer. 在该系统中图像、力和表面肌电信号都由一台计算机实时采集。
- Method Two channel surface EMG signals were extracted and analyzed to reflect the complexity degree of the dynamics of the neurophysiological system. 方法采用一种算法简单、适合短数据运算的复杂度算法 ,提取双通道表面肌电信号的复杂度信息来反映运动神经系统运动的复杂程度。
- Method Two-channel surface EMG signals were extracted and analyzed to reflect the complexity degree of the dynamics of the neurophysiological system. 方法采用一种算法简单、适合短数据运算的复杂度算法，提取双通道表面肌电信号的复杂度信息来反映运动神经系统运动的复杂程度。
- Surface EMG signal classification method based on wavelet transform is presented in this paper. 针对肌电信号的非平稳特性，采用小波变换方法对表面肌电信号进行分析。
- Method The concept of instantaneous median frequency surface EMG signal was discussed. 目的采用时频分析法分析表面肌电信号瞬时中值频率。
- Experiments show that using active electrode can improve ratio of signal and noise, reduce noise and detect surface EMG signal effectively. 实验表明,采用有源电极可以提高信噪比,减小噪声,有效地提取出表面肌电信号。
- The experiments showed that active electrode could be used to improve signal/noise ratio, reduce noise and detect surface EMG signal effectively. 实验表明 ,采用有源电极可以提高信噪比 ,减小噪声 ,有效地提取出表面肌电信号。
- The method of BP neural network improved by Levenberg-Marquardt algorithm in surface EMG signal classification is proposed. 提出用 Levenberg-Marquardt 算法改进 BP 神经网络识别表面肌电信号的方法。
- This paper introduces a method for feature extraction of surface EMG signal with fuzzy wavelet packet and classification with C4.5 decision tree. 提出了用模糊小波包提取表面肌电信号特征;并且用C4.;5决策树分类器对信号进行分类的方法。
- The detection of surface EMG signal is an noninvasive method, which has great importance in clinical diagnosis,rehabilitation medicine and sport medicine. 表面肌电信号的检测是一种无创电检测方法,它的检测分析对临床诊断及康复医学、运动医学等具有重要意义。
- This paper introduces the analysis(time domain analysis,spectrum analysis,time frequency analysis,and artificial neural network analysis) method of surface EMG signal,application of surface EMG signal and its prospect are also included in the paper. 本文介绍了表面肌电的信号分析方法 (时域分析法、频域分析法、时频分析法及人工神经网络等方法 ) ,并介绍了表面肌电信号检测分析技术的应用状况和前景展望
- The results show that EMG data is non-noisy and has determinate nonlinearity.This paper provides an objective basis for the further analysis of chaos dynamic feature of the surface EMG signal. 研究表明，EMG信号是非噪声的确定性信号，并具有确定性的非线性特性，为进一步分析其混沌动力学特性提供了客观依据。
- RQA-BASED ANALYSIS OF SURFACE EMG SIGNALS 基于定量分析方法的动作表面肌电信号分析
- Application of active electrode at detection of surface EMG signal 有源电极在肌电检测中的应用
- Surface EMG Signal Classification Method Based on Wavelet Transform 基于小波变换的肌电信号识别方法研究
- Surface EMG Signal Classification Using Wavelet Transform 小波变换在表面肌电信号分类中的应用
- Surface EMG is a complex nonlinear signal. 表面肌电信号(surface EMG,sEMG)是一种复杂的非线性信号。
- SURFACE EMG SIGNAL CLASSIFICATON METHOD BASEDON COMPLEXITY MEASURE 基于复杂性度量的表面肌电信号分类方法
- Detection of Surface EMG Signal Using Active Electrode 有源电极用于表面肌电信号的检测
