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BDFtestfiles
- matlab program for EMG
semg
- 皮肤肌电信号分析,DB4小波包变换,时频分析-semg analysis db4 wavelet packet transform
stprtool15aug08
- 捷克理工大学Hlavac教授和Franc博士提供的统计模式识别Matlab工具箱的最新版本V2.09,在原有版本基础上进行了一些修改和完善。它包括现有模式识别的大部分方法,比如SVM,PCA,LDA等。我采用其中的SVM方法进行了人体下肢假肢SEMG信号的分类,效果不错。希望能对大家有帮助。-Statistical Pattern Recognition Toolbox for Matlab (C) 1999-2008, Versio
an
- 表面肌电信号数字传感器的设计。表面肌电(suRFace electromyography, sEMG)信号是神经肌肉系统在进行随意性和非随意性活动时的生物电变化经表面电极引导、放大、显示和记录所获得的一维电压时间序列信号,其振幅约为0-5000μV,频率0-1000Hz,信号形态具有较强的随机性和不稳定性。与传统的针式肌电图相比,sEMG的空间分辨率相对较低,但是探测空间较大,重复性较好,对于体育科学研究、康复医学临床和基础研究等具有重
1
- ELman人工神经网络建模里例子,用于利用表面肌电信号识别自行车蹬踏阶段的识别研究-Elman modelling code which is used for sEMG cycling phase identification. It is of great help for researchers in surface myoelectric signal research.
SEMG
- 《基于模式识别的肌电信号动作分类性能研究》2010最新论文,从CNKI上买来的,现在共享给大家,希望对大家有用,和我课题相关,有这方面的需要可以咨询我。-" EMG Pattern Recognition Based on Classification Performance of Action," 2010 latest paper, bought from CNKI on, now shared to everyo
Noise-canceling-of-SEMG
- 利用小波变换实现表面肌电信号消噪的程序,还包括一些对比分析。-Wavelet transform SEMG denoising procedures, including some comparative analysis.
fmedian_sEMG
- calculate the median freqency of sEMG with wavelet method
sEMG-Based-on-permutation-entropy
- 针对表面肌电信号的混沌特征、噪声强等特点,该文提出了基于排列组合熵的表面肌电信号特征分析方法-The chaotic characteristics of the surface EMG signal and noise characteristics, this paper proposes a sEMG analysis method based on permutation entropy
EEG-SEMG
- 表面肌电信号与肢体运动直接相关,肢体的不同动作具有不同的肌肉收缩模式,这些模式的差别反映在表面肌电信号特征的差异上-Surface EMG and limb movements directly related to the different movements of the limbs have different muscle contraction mode, the difference between these patte
jiance
- 四通道表面肌电信号活动段检测方法(通过能量值)-action detection ways of four-channel sEMG(by energy value)
sEMG-signal-pattern-recognize
- 是一篇关于表面肌电信号处理的文章,主要是模式识别方面的。-Is an article about the surface EMG signal processing, pattern recognition is the main area.
lower-limb
- 是一篇关于表面肌电信号处理的文章,主要是下肢sEMG模式识别方面的。-Is an article about the surface EMG signal processing, mainly lower limb sEMG pattern recognition.
offline-sEMG-recognition
- 提取人体手臂肌电信号,手势识别,包括肌电信号的预处理,端点检测,特征提取,特征降维,SVM分类识别-sEMG based hand movements recognition using SVM
feature
- 可以提取肌电信号的特征,进行手部动作解码(The feature of sEMG can be extracted to decode hand motions)
sEMG feature extraction
- 提取肌电信号的时域特征,ZC,WAMP,WL,SSC,RMS。以及特征的融合。肌电信号主要是采取了脚踝关节的六个动作。在动作识别中,时域的特征最常用,而且计算复杂度低,包含的信息也充分。(The time domain features of electromyographic signals were extracted, ZC, WAMP, WL, SSC, RMS. And the fusion of features. The
肌电信号处理
- 表面肌电信号处理的matlab程序,包括带通滤波、50Hz陷波滤波程序,以及计算时域、频域的指标iMEG、RMS , MF、MPF(The matlab program of sEMG signal processing includes band-pass filter, 50 Hz notch filter program, and calculation of time and frequency domain index IME