肌电信号,EMG英语短句,例句大全

肌电信号,EMG
1)EMG肌电信号
1.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
2.Method of mathematics treatment in the EMG analysis;表面肌电信号分析中的数学处理方法
3.Prosthetic Hand Control Based on EMG Signals;基于肌电信号的仿人型假手控制

英文短句/例句

1.A Method for Synthesizing Surface EMG Signals Based on Physiological EMG Model基于生理层肌电模型的表面肌电信号仿真方法
2.Characteristics of Surface Electromyography Single Change based on Isokinetic Muscle Fatigue;基于准稳态信号的动态肌肉疲劳表面肌电信号变化特征
3.The Experimental Study on the Character of Toad Gastrocnemius Muscle s Surface Electromyography Signal;蟾蜍腓肠肌表面肌电信号（sEMG）特征的研究
4.The Research and Prospects on sEMG Signal Characteristics of Muscular Fatigue;肌肉疲劳的表面肌电信号特征研究与展望
5.Largest lyapunov exponents analysis of the surface electromyograph signal of the masseter基于混沌理论的嚼肌表面肌电信号分析
6.A Denoising Method Study Based on Wavelet Transform for Electromyography of Diaphragm基于小波变换的膈肌肌电信号降噪方法研究
7.EMG Signal Analysis Based on Fuggy and Neural Network基于模糊神经网络的肌电信号的分析
8.Method of mathematics treatment in the EMG analysis表面肌电信号分析中的数学处理方法
9.The Research of Human-Computer Interactive Technology Based on Electromyography;基于肌电信号的人机接口技术的研究
10.A Study of Feature Extraction from Semg Singal Based on Entropy;基于熵的表面肌电信号特征提取研究
11.Hand Gesture Recognition Based on Vision and SEMG Fusion基于视觉与肌电信号的手势识别研究
12.Electromyography Analysis Based on the Entropy Theory and Complexity Measures基于熵理论和复杂度的肌电信号分析
13.Design of EMG Data Acquisition Instrument Based on C8051F基于C8051F的肌电信号采集仪设计
14.Changes in Muscular Tension and EMG Signals in Rats during Electric Stimulation with Low-Frequency低频电刺激过程中大鼠骨骼肌肌张力和肌电信号的变化特征
15.Serial Communication between Acquisition System of EMG and Computer肌电信号采集系统与计算机的串口通信
16.On Unification of Macro- reversible and Micro-irreversible in Statistical Physics关于拾取表面肌电信号的电路设计和探究
17.The Study Advances and Prospects of Processing Surface EMG Signal in Prosthesis Control肌电假肢控制中的表面肌电信号的研究进展与展望
18.Study on Detection and Analysis of Electrically Evoked SEMG Signal and Muscle Fatigue;电刺激诱发表面肌电信号检测分析及肌疲劳的研究

相关短句/例句

electromyography[英][i,lektr?umai'?gr?fi][美][?,l?ktroma?'ɑgr?f?]肌电信号
1.Surface electromyography processing based on recurrence quantification analysis;基于定量递归分析(RQA)方法的肌电信号处理
2.We used an algorithm based on single value decomposition to decomposed the signal into tow time- orthogonal subspaces: one contains ECG signal, the other contains artificial noise such as baseline wander and electromyography.使用一种基于奇异值分解 (SVD)的算法 ,将信号分解为两个时正交的子空间即一个包含了 ECG信号 ,另一个则包含了人工噪声 ,诸如基线漂移 (BW)和肌电信号 (EMG) ,这种方法利用了存在于 1 2导联心电图中的冗余。
3.The motion-pattern recognition arithmetic based on s u pport vector machine is proposed to enhance the discrimination rate and the real-time of multi-movement pattern recognition of surface electromyography.为了提高肌电信号多运动模式识别的准确性和实时性,提出了一种基于支持向量机的动作模式分类算法。
3)myoelectric signal肌电信号
1.Identification of Myoelectric signals of the paralysed patient’s leg motions;截瘫病人完成下肢运动的肌电信号分辨
2.The integral absolute value,autoregressive(AR) model coefficients,and linear cepstrum coefficients are extracted as feature parameters from time segments of the surface myoelectric signals.待辨识的6类手部动作肌电信号经各特征域变换,提取特征矢量后由BP神经网络分类,根据D-S证据理论对各分类器分类结果进行证据累积,并得到最终分类结果。
3.Statistical characters of the short time slices of the myoelectric signal of musculus flexor carpi ulnaris are preprocessed,then the results are given as the input of self-organization neural network to classify time slices and to find the action start time slice.提出一种提取尺侧腕屈肌表面肌电信号的短时统计特性,并将此特性预处理后作为自组织人工神经网络输入来判断运动状态,进而实现实时识别人体特定动作起始时刻的方法。
4)surface EMG肌电信号
1.Application of improved BP algorithm to surface EMG signal classification;改进的BP算法在表面肌电信号识别中的应用
2.Surface EMG Signal Classification Using Wavelet Transform;小波变换在表面肌电信号分类中的应用
3.Four types of movement of forearm,hand grasp,hand extension,wrist pronation and wrist supination can be identified from surface EMG s.针对肌电信号的非平稳特性 ,采用短时傅里叶变换方法对表面肌电信号进行分析 ,并通过奇异值分解有效地提取特征矢量进行模式识别 ,能够成功地从掌长肌和肱桡肌采集的两道表面肌电信号中识别展拳、握拳、腕内旋、腕外旋四种运动模式。
5)Electromyography(EMG)肌电信号
1.To eliminate the noise included in electromyography(EMG),a de-noising method by multi-scale product coefficient hard thresholding was presented.为了消除肌电信号中的噪声,提出了一种基于相邻尺度积系数的硬阈值滤波方法。
2.Aiming at the key issues of the human-computer technology based on biolelectricity, namely the picking up and analysis of bioelectricty signal, we do the research with academically significance and application possibilities of human-computer interactive technology based on electromyography(EMG).本文针对基于生物电信号的人机交互技术的关键问题即信息的获取和分析,开展了基于肌电信号检测的人机交互接口技术的研究,研究内容具有重要学术意义和应用前景。
6)NEMG针电极肌电信号
1.It is discussed how to evaluate muscle weariness by NEMG in the thesis.探讨如何利用针电极肌电信号来评价人体的肌肉疲劳。
2.Generally,abnormal recruitment NEMG is usually used to evaluate the injurious degree of the nerve in clinic.本文作者提出了一种对前臂肌神经损伤肌肉的针电极肌电信号建立AR模型,提取AR系数并通过BP神经网络判别肌神经损伤的方法。