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ECGdenoising
- 去除在心电信号采集过程中混入的肌电干扰 、工频干扰、基线漂移等噪声信号,避免噪声对心电信号特征点的识别和提取造成误判漏判。
gesture.rar
- 关于手势识别的一些英文文章，利用表面肌电信号,Gesture recognition on a number of English articles, the use of surface EMG
rr
- 基于肌电信号的滤波器综合设计 Matlab-EMG signal of filter-based integrated design Matlab
av_sub
- 脑电（EEG）是一种反映大脑活动的生物电信号，由于它具有很高的时变敏感性，在采集时极易受到外界的干扰。如眼球运动、眨眼、心电、肌电等都会给真实的脑电信号加入噪声（伪迹）。这些噪声给脑电信号的分析处理带来了很大的困难。从剔除EEG中的各种伪迹到去除噪声的效果评估研究者们都提出了很多方法。本文提出matlab除各种脑电信号伪伪迹减法- As a kind of physiological signals, the Electroencephalogram（EEG）represents the ele
dd
- 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，-EMG pattern recognition based on the classification performance of action " 2010 latest paper, bought from the CNKI on, now for everyone to share, we hope to be useful,
RECGGdenoisiie
- 去除在心电信号采集过程中混入的肌电干扰、工频干扰、基线漂移等噪声信信号，避免噪声对心电信号特征点的识别与提取造成误判漏判 已通过测试。 -Remove the EMG interference mixed with the signal acquisition process in mind, frequency interference, baseline drift and noise channel signal to avoid noise caused by the misjudg
MF-MPF
- 利用Matlab计算肌电信号的积分值和平均功率-Using Matlab to calculate the integral value of the EMG signal and the average power
baoluozz
- 对肌电信号中的有用信号的提取，将无用信号幅度变为0.-Useful for EMG signal extraction in the unwanted signal amplitude becomes 0.
tongue
- 对舌头肌电信号进行标准化处理，得到原始信号和标准化处理后信号的分布直方图及拟合曲线。-Standardizing for tongue muscle electrical signals, and standardized treatment after get the original signal distribution histogram and the fitting curve.
EMG-pattern-recognition
- 肌电信号模式识别，需要巴特沃斯滤波器，并伴有注释，适合初学者-EMG pattern recognition, we need Butterworth filter
surface-EMG-signals
- 基于非线性特征的表面肌电信号模式识别方法,用了球状李雅普洛夫指数和对支持向量机。-Surface EMG Pattern Recognition Based on the nonlinear characteristics, with a spherical Lyapunov exponent and support vector machine.
MFC_VoiceControl
- MFC界面，利用Myo采集肌电信号，根据肌电信号强弱实时控制计算机音量； picture控件显示手的动作状态。-MFC interface using Myo EMG acquisition, real-time control computer volume according to EMG strength picture control to display the status of hand movements.
fast_ApEn
- 近似熵，可用于生物电信号分析，包括脑电、心电、肌电等。-Approximate entropy, can be used for bio-electrical signal analysis, including EEG, ECG, EMG and so on.
肌电信号模式识别
- 实现了两种算法，在时域内分别利用肌电信号的过零点数和波长作为特征，并利用高斯重构算法进行模式识别。(Two algorithms are implemented. In the time domain, the zero crossing point and wavelength of the EMG signal are used as the features, and the Gauss reconstruction algorithm is used for pattern recogn
6.16
- EMG时域特征，针对肌电信号的时域特征值(EMG time-domain characteristics)
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 electromyographic signal mainl
MATLAB_EMG_ACTIVATION_CACLU
- 实现肌电信号激活程度的计算、幅值计算以及包络线的生成(The calculation of EMG activation degree, amplitude calculation and envelope generation are realized.)
肌电处理代码
- 处理肌电信号，得到短时傅里叶变化下的中值频率和肌肉激活度进行下一步的分析(The electromyography signal is processed, and the median frequency and muscle activation degree under the condition of short time Fourier transform are analyzed)
#-nina-semimyo-master
- 基于肌电信号的手势识别，数据来自开源数据集ninapro(Hand gesture recognition based on electromyography)
LabView
- 使用delsys trigno实现肌电信号的在线采集/显示以及根据matlab的BP神经网络模型实现手势识别(Using Delsys trigno to realize the on-line acquisition / display of EMG signal and the BP neural network model of MATLAB to realize gesture recognition)