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Description: 毕业设计--心电信号分析系统
ecg qrs波 diagnostic-Graduation Project ECG analysis system diagnostic wave ecg qrs
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Size: 1805312 |
Author: 李巍 |
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Description: 这是用于检测心电信号QRS波的源码用来双正交小波能够实现QRS波形的准确检测-This is used to detect ECG QRS wave source biorthogonal wavelet can be used to achieve accurate detection of QRS waveform
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Size: 2048 |
Author: 白洁 |
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Description: 用于生成ECG波形，包括P波，QRS波，T波-Used to generate the ECG waveform, including the P wave, QRS wave, T wave
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Size: 2048 |
Author: 白洁 |
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Description: 心电信号QRS波的R波检测，用了阈值的方法，自适应修改阈值，域加窗定位R波幅度-QRS wave of ECG R-wave detection, using a threshold approach, adaptive modification threshold, domain windowed positioning R-wave amplitude
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Size: 1024 |
Author: zhu er |
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Description: 心电信号在线数据知识化辅助诊断算法研究
摘 要:针对心电监护与诊断过程中数据量大、准确性和快速性要求高的特点,提出了一套基于数据知识化的心电
辅助诊断算法.该套算法包括数据识别、冗余处理、转换和提取过程,利用小波变换的多分辨率和抗干扰能力好的
特点,检测QRS波、P波、T波,提高了特征检测的准确性 利用聚类分析具有较好的鲁棒性和适合于大数据量分析
的特点,对QRS进行波形分类 算法结合了单独一搏诊断和串诊断以及多参数综合分析.采用MIT-BIH标准心电
数据库中的部分数据和心电专家确诊的心律失常数据文件对该算法进行了评估,检出率都在95 以上,表明该套
算法对部分心律失常可以进行有效分析.
-A series of data knowledge discovery based electrocardiograph (ECG) auxiliary diagnosis algo-
rithms were presented against the characteristics of huge data quantum, high accuracy and rapidity de-
mands in the ECG monitor and diagnosis process. The algorithm consists of several stages, including data
distinguishing, data redundant processing, data conversion and data extraction. The characteristics of
wavelet transform, multiresolution and high anti-interference, were used to detect QRS, P and T waves
and improve the accuracy of character detection. Clustering analysis characterized by better robustness and
capability to analyze huge data quantum was used to classify QRS wave. The algorithm combines diagnosis
based on one beat, string diagnosis and comprehensive analysis with multiparameters. Verified by partial
data of MIT-BIH standard ECG database and arrhythmia data files diagnosed by ECG experts, the detect-
ability exceeded 95 , which showed that the algorithm could analy
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Size: 68608 |
Author: Shi |
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Description: ECG信号处理获得各种features，包括P和T波的参数，该程序使用的数据来自mit database 如果要执行该程序，要修改ECG 信号的源文件目录-ECG signal processing to obtain a variety of features, including the P and T-wave parameters, the program uses data from mit database
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Size: 3828736 |
Author: Jun Cheng |
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Description: ECG心电信号matlab仿真画图，其中包括P波、Q波、QRS波、S波、T波和U波-Matlab simulation of ECG ECG drawing, including the P wave, Q wave, QRS wave, S wave, T wave and U wave
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Size: 285696 |
Author: 郑秋平 |
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Description: 以软件为主的方法实现QRS波的检测滤波之后的信号一般经过一些
变换以提高QRS波的份量，进而采用一系列阈值进行判别，这些阈值有固定
阈值法，也有可变阈值法。前者由于可能的干扰或高P、高T波的存在，若
其滤波后超过其阈值便会产生假阳性(FP，falsepositive)结果；另外，当心
律失常或QRS波幅度变小，阈值设置过高，会导致漏检产生假阴性(FN，
falsenegative)结果。由于固定阈值的这些缺点，有研究者提出了用可变阈
值检测，以提高检测的精确率，所采用的可变阈值包括幅度阈值、斜率阈值
和时间间隔阈值等。-Give priority to with software method for detecting QRS wave signal after some commonly after filtering
Amount of transformation in order to improve the QRS wave, then using a series of threshold to distinguish, the threshold value is fixed
Threshold value method and variable threshold value method. The former due to the possible interference or the existence of the high P and T waves, if
More than the threshold value is created after the filtering false positives (FP, falsepositive results In addition, be careful
Law of disorder or QRS wave amplitude decreases, threshold is set too high, can lead to leak to produce false negatives (FN,
Falsenegative) results. Due to these disadvantages of fixed threshold, some researchers have proposed using variable threshold
Value detection, in order to improve the precision of detection rate, adopted by the variable threshold including amplitude threshold, the slope threshold
And the time interval threshold, etc.
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Size: 5120 |
Author: 钟能枝 |
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Description: This paper gives an insight to labview software tools which helps in analysis of ECG signals. The raw ECG data are taken MIT-BIH Arrhythmia . Study of ECG signal includes filtering & preprocessing which removes the baseline wandering and noise due to breathing through wavelet transform technique. ECG features extraction VI will use for extracting various features viz P onset, P offset, QRS onset , QRS offset, T onset, T offset, R , P & T wave, with which we can calculate various parameters like Heart rate, QRS amplitude and their time duration.-This paper gives an insight to labview software tools which helps in analysis of ECG signals. The raw ECG data are taken MIT-BIH Arrhythmia . Study of ECG signal includes filtering & preprocessing which removes the baseline wandering and noise due to breathing through wavelet transform technique. ECG features extraction VI will use for extracting various features viz P onset, P offset, QRS onset , QRS offset, T onset, T offset, R , P & T wave, with which we can calculate various parameters like Heart rate, QRS amplitude and their time duration.
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Size: 388096 |
Author: aykut |
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