共查询到19条相似文献,搜索用时 171 毫秒
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肌电信号要作为下肢假肢的控制信息源,必须经过信号处理与特征提取。小波变换能将各种交织在一起的由不同频率组成的混合信号分解成不同频段的信号,可以检测出许多其他分析方法忽略的信号特性,因此小波变换常被用于表面肌电信号的处理。而小波包变换对信号逐渐变宽的频谱可以进一步分割细化,具有良好的局部化品质,比正交小波变换更优越。本文将利用小波包变换方法对站立与行走过程中大腿股四头肌部位的肌电信号进行分析和特征提取,并利用各频段能量构造特征矢量,经过学习矢量量化神经网络训练能够有效地从股四头肌采集的肌电信号中识别站立及行走的运动模式。 相似文献
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肌肉疲劳是由运动引起的肌肉最大随意收缩力减小的现象,其研究可应用于生理医学的职业病预防或体育工程的运动员训练等方面。本文采用短时傅里叶变换对肌音信号进行处理,提取频域特征平均功率频率(Mean Power Frequency,MPF)和中值频率(Median Frequency,MDF),研究其与肌肉疲劳程度之间的关系。9名健康的男性志愿者参与了本次试验,采用等值于60%最大随意收缩力(MVC)的力产生恒力肌肉疲劳,同步记录每一位受试者桡侧腕屈肌的肌音信号,对提取的频域参数进行分析。将持续30 s的肌肉疲劳过程分为6个时间阶段(每个阶段为5 s),并对每个时间阶段内的MPF和MDF计算均值。结果表明,随着肌肉疲劳程度加深,肌音信号的MPF和MDF在每个时间阶段内的均值均呈现近似线性下降的趋势。在30 s肌肉疲劳过程中,从第1阶段(1~5 s)到第6阶段(26~30 s),MPF均值下降了15.8%,MDF均值下降了26.1%。基于短时傅里叶变换提取的MPF和MDF指标能良好地反映疲劳敏感性和稳定性,在评定肌肉静态疲劳方面是较好的参考指标。本文采用的方法和得到的结果为后期更深入地使用肌音信号对肌肉疲劳程度进行量化研究提供了依据。 相似文献
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目的:了解健康成年人下肢膝关节等动屈伸运动至疲劳过程中下肢股内侧肌表面肌电信号(sEMG)的特征,为sEMG在动力性运动中的广泛应用提供依据。方法:选择在校男性大学生10人,使用艾力尔(Ariel)等动训练仪在60°s-1运动速度下诱发下肢股内外侧肌疲劳,同时使用ME6000表面肌电仪记录2块肌肉的sEMG,对其时域指标均方根振幅(RMS)和积分肌电(iEMG)以及频域指标中位频率(MF)和平均功率频率(MPF)进行分析。结果:在膝关节等速屈伸运动至疲劳过程中股内侧肌的时域指标RMS和iEMG显著上升(P<0.05),疲劳对iEMG影响的效应尺度大于RMS;频域指标MF和MPF显著下降(P<0.05),疲劳对MPF影响的效应尺度大于MF;肌肉疲劳过程中iEMG增加率显著高于RMS(P<0.05),MPF下降率显著大于MF(P<0.05)。结论:时域指标iEMG以及频域指标MPF可以作为评价动力性肌肉疲劳的敏感指标。 相似文献
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[目的 ]对心电图数据进行预处理和特征提取。 [方法 ]对心电 (ECG)信号的检测 ,最关键的是对QRS波群的检出。本研究利用小波在时、频两域具有表征信号局部特性的能力 ,适当选择基本小波 ,应用Mallat算法对心电图信号进行多尺度分解从而检测出QRS波。 [结果 ]在Mallat算法实现时 ,选用适当的基本小波 ,清晰的检测出了QRS波群。 [结论 ]小波变换原理检测ECG信号中QRS波群具有很好的效果 ,而且选用不同的基本小波 ,可以检测出不同频率成份的波段 ,这样也同样达到了去除噪声的目的 相似文献
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目的研究颈椎导引术对社区慢性非特异性颈痛(NCNP)患者的效果。方法将60名社区NCNP患者随机分为对照组和导引术组各30例。对照组进行颈部肌肉耐力训练,导引术组进行颈椎导引术训练,每日2次,每周5 d,连续训练2个月。采用表面肌电信号的平均功率频率(MPF)和MPF下降斜率(MPF slope)指标评价2组治疗前后疗效。结果与治疗前比较,2组双侧胸锁乳突肌和上斜方肌的MPF和MPF slope均有改善(P<0.05);其中,导引术组MPF slope改善程度优于对照组(P<0.05)。结论颈椎导引术能够增加NCNP患者的颈部肌肉耐力,改善症状,值得在社区进行推广使用。 相似文献
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目的:利用小波包工具对心电图进行时域和频域的分析,以发现心电图更多的特征值,拓展心电图的临床诊断价值。方法:以matlab为平台,利用编程方式调用小波包工具,对正常心电图、有干扰的心电图和临床常见病态心电图进行了8层小波包的分解。结果:正常心电图在小波图上有更多特征值,在8频带的低频部分与原信号拟合度高,能放大T波,干扰波多在高频部分;QRS波形比较复杂,在低频到高频均有波形,临床常见病态心电图在小波图中相对容易识别。结论:心电图的小波信号有多分辨率特征,能提供更多的诊断价值。 相似文献
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目的:基于经验模态分解(EMD)的多尺度时域滤波特性,抑制生物雷达回波信号噪声。方法将经过预处理的雷达回波信号进行EMD分解,获取固有模态函数(IMF)分量;根据噪声与信号自相关函数的特性差异将IMF区分为有用信号占主导模态与噪声占主导模态两部分;然后用基于小波软阈值的去噪方法提取噪声占主导模态部分中的有用成分,与有用信号占主导模态部分的固有模态函数叠加,获取雷达回波信号中的生命信息。结果基于EMD的噪声抑制方法有效地去除了雷达回波信号中的高频噪声成分,提取出了有用信息。结论基于EMD的噪声抑制方法能为生命体目标的识别提供更多信息。 相似文献
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GPRS移动式心电监护系统的QRS波实时检测算法 总被引:4,自引:0,他引:4
目的探讨GPRS移动式心电监护系统ECG信号QRS波的实时检测算法.方法采用四点平均对CM5导联的ECG信号进行滤波,再对ECG信号的一、二阶差分值进行平滑处理,利用ECG信号的二阶差分值极小值和一阶差分过零点在较短的时间窗内实现QRS波精确定位,并设计了具有自学习和自适应功能的信号检测门限.结果算法能抑止多种噪声对ECG信号的影响,将搜索的时间窗宽度缩小到0.02 s以下,且算法只具有多项式的复杂度;经过临床测试,动态ECG信号进QRS波检测准确率可达99.8%以上.结论该算法适合于移动心电监护系统QRS波的实时检测和分析. 相似文献
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Qi Wei Oung Hariharan Muthusamy Shafriza Nisha Basah Hoileong Lee Vikneswaran Vijean 《Journal of medical systems》2018,42(2):29
Parkinson’s disease (PD) is a type of progressive neurodegenerative disorder that has affected a large part of the population till now. Several symptoms of PD include tremor, rigidity, slowness of movements and vocal impairments. In order to develop an effective diagnostic system, a number of algorithms were proposed mainly to distinguish healthy individuals from the ones with PD. However, most of the previous works were conducted based on a binary classification, with the early PD stage and the advanced ones being treated equally. Therefore, in this work, we propose a multiclass classification with three classes of PD severity level (mild, moderate, severe) and healthy control. The focus is to detect and classify PD using signals from wearable motion and audio sensors based on both empirical wavelet transform (EWT) and empirical wavelet packet transform (EWPT) respectively. The EWT/EWPT was applied to decompose both speech and motion data signals up to five levels. Next, several features are extracted after obtaining the instantaneous amplitudes and frequencies from the coefficients of the decomposed signals by applying the Hilbert transform. The performance of the algorithm was analysed using three classifiers – K-nearest neighbour (KNN), probabilistic neural network (PNN) and extreme learning machine (ELM). Experimental results demonstrated that our proposed approach had the ability to differentiate PD from non-PD subjects, including their severity level – with classification accuracies of more than 90% using EWT/EWPT-ELM based on signals from motion and audio sensors respectively. Additionally, classification accuracy of more than 95% was achieved when EWT/EWPT-ELM is applied to signals from integration of both signal’s information. 相似文献
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目的:研究一种方法精确预测胸腹部肿瘤放射治疗中的非规则呼吸运动。方法:提出基于小波分解和自适应神经模糊推理系统的呼吸运动预测方法(WANFIS),利用小波分解将呼吸信号分成基线、低频和高频三部分,并分别采用线性拟合、自适应神经模糊推理系统(ANFIS)、简单移动平均进行预测,然后综合三部分预测值作为呼吸运动预测结果。基于30例临床数据回顾性分析,将WANFIS算法与神经网络(NN)、CyberKnife放射外科系统的Synchrony呼吸同步追踪系统、ANFIS这三种典型预测算法进行对照比较。结果:本文提出的WANFIS算法的归一化均方根误差(nRMSE)平均值为0.09,小于NN的0.17、Synchrony的0.11 以及ANFIS的0.11。结论:WANFIS能更好地预测非规则呼吸信号,更有效地补偿放疗系统时间延迟。 相似文献
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Three-dimensional reconstruction of digitized human liver: based on Chinese Visible Human 总被引:3,自引:0,他引:3
CHEN Gang LI Xue-cheng WU Guo-qing ZHANG Shao-xiang XIONG Xiao-feng TAN Li-wen YANG Ri-gao LI Kai YANG Shi-zhong DONG Jia-hong 《中华医学杂志(英文版)》2010,123(2):146-150
Background Comparing with two dimensional (2D) imaging, both in diagnosis and treatment, three dimensional (3D) imaging has many advantages in clinical medicine. 3D reconstruction makes the target easier to identify and reveals the volume and shape of the organ much better than 2D imaging. A 3D digitized visible model of the liver was built to provide anatomical structure for planing of hepatic operation and for realizing accurate simulation of the liver on the computer. Methods Transverse sections of abdomen were chosen from the Chinese Visible Human dataset. And Amira software was selected to segment and reconstruct the structures of the liver. The liver was reconstructed in three-dimensions with both surface and volume rendering reconstruction. Results Accurately segmented images of the main structures of the liver were completed. The reconstructed structures can be displayed singly, in small groups or as a whole and can be continuously rotated in 3D space at different velocities. Conclusions The reconstructed liver is realistic, which demonstrates the natural shape and exact position of liver structures, tt provides an accurate model for the automated segmentation algorithmic study and a digitized anatomical mode of viewing the liver. 相似文献
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朱龙坤 《福建医科大学学报》1995,(2)
在PC/XT兼容机上添置模/数,数/模接口卡,编制信号处理软件及微机模拟实验软件,组成一套微机生理学实验教学系统,能对教学实验中的生理信号进行实时检测和处理,由微机重塑神经纤维的动作电位并能对影响动脉压的因素及甲状腺激素分泌的功能调节等内容进行微机模拟。该系统在近3年的部分教学中取得了较好的效果。 相似文献
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The volume of patient monitoring video acquired in hospitals is very huge and hence there is a need for better compression
of the same for effective storage and transmission. This paper presents a new motion segmentation technique, which improves
the compression of patient monitoring video. The proposed motion segmentation technique makes use of a binary mask, which
is obtained by thresholding the standard deviation values of the pixels along the temporal axis. Two compression methods,
which make use of the proposed motion segmentation technique, are presented. The first method uses MPEG-4 coder and 9/7-biorthogonal
wavelet for compressing the moving and stationary portions of the video respectively. The second method uses 5/3-biorthogonal
wavelet for compressing both the moving and the stationary portions of the video. The performances of these compression algorithms
are evaluated in terms of PSNR and bitrate. From the experimental results, it is found that the proposed motion technique
improves the performance of the MPEG-4 coder. Among the two compression methods presented, the MPEG-4 based method performs
better for bitrates less than 767 Kbps whereas for bitrates above 767 Kbps the performance of the wavelet based method is
found superior. 相似文献
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目的分析交流干扰滤波器对心肌细胞动作电位信号的影响。方法将心肌细胞动作电位经玻璃微电极、微电极放大器、微分器、A/D转换器输入微型计算机。在使用和不使用交流干扰滤波器两种情况下,对心肌细胞动作电位波形进行比较分析。结果使用交流干扰滤波器,将使动作电位波形严重失真,0期上升时间延长,最大上升速度减小。结论心肌细胞动作电位波形中含有50Hz信号成分,信号放大通路中不能使用交流干扰滤波器。 相似文献