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Description: 心电数据的匹配，对数据中出现的情况分为三类进行匹配，正常，不正常，和未知，对不正常的数据进一步分析-ECG data matching, the data is divided into the three types of matches, normal, abnormal, and unknown to normal data for further analysis
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Size: 3212 |
Author: 唐娜 |
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Description: 这是一个用于估计ECG信号的频率变化，区分正常和异常ECG信号的原程序，-This is an ECG signal used to estimate the frequency of changes in the distinction between normal and abnormal ECG signals in the original program,
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Size: 825 |
Author: 黄敏松 |
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Description: 心电数据的匹配，对数据中出现的情况分为三类进行匹配，正常，不正常，和未知，对不正常的数据进一步分析-ECG data matching, the data is divided into the three types of matches, normal, abnormal, and unknown to normal data for further analysis
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Size: 3072 |
Author: 唐娜 |
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Description:
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Size: 1024 |
Author: 黄敏松 |
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Description: 心电信号产生程序 仿真人体正常状态下的心电信号-ECG simulation of the human body have a procedure under normal ECG
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Size: 283648 |
Author: wangzhen |
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Description: 心电滤波程序及产生噪声心电波形和正常心电波形的程序-ECG noise filtering procedures and have a normal ECG waveform and process ECG waveform
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Size: 6144 |
Author: zhangfei |
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Description: After we calculate the R peaks of the ecg signal, we identify different
criteria :
a) Heart rate.
b) Regularity of the R-R peaks (Look at the R-R distances).
1. Regular (are they equidistant apart).
2. Irregular.
c) Rhythm
1. Tachycardia ==> Fast.
2. Bradychardia ==> Slow.
3. Normal.-After we calculate the R peaks of the ecg signal, we identify different
criteria :
a) Heart rate.
b) Regularity of the R-R peaks (Look at the R-R distances).
1. Regular (are they equidistant apart).
2. Irregular.
c) Rhythm
1. Tachycardia ==> Fast.
2. Bradychardia ==> Slow.
3. Normal.
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Size: 1024 |
Author: Lara |
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Description: 摘要:心电图ST段对心脏疾病的诊断具有重要意义。在正确读取采集于郑州大学一附院的运动心电图数据基础上,利用小波变换更准确地确定其ST段的起始和终止位置,初步探讨了BP神经网络用于心电图ST段识别的方法,并用此方法识别出心电图ST段的三种类型—正常、水平压低和抬高。实验结果较好。
-Abstract: ECG ST segment on the diagnosis of heart disease is important. Collected in the correct reading of the first affiliated hospital of Zhengzhou University in exercise ECG data based on the use of wavelet transform to more accurately determine the ST segment of the start and end position, discussed the BP neural network for ECG ST-recognition method, and use this method to identify three types of ECG ST segment- the normal, the level of depression and elevation. Experimental results are good.
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Size: 97280 |
Author: Lily |
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Description: 心电图的自动分析、诊断已经广泛地应用于心脏的功能检测、心血管疾病的诊断和预防以及心电监护等多方面。QRS波群的检测是心电信号分析中最为关键问题，其精确检测是心电图自动诊断的基础。这是因为只有在确定QRS波群后才有可能计算心率、心率变异性并进一步检测和分析心电的其他细节。一个正常的ECG信号是由一系列的波形-Automatic ECG analysis, diagnosis has been widely used in heart function tests, diagnosis and prevention of cardiovascular disease and other aspects of ECG monitoring. Detection of QRS wave group ECG analysis is the most critical issues, the precise detection is the basis of ECG automatic diagnosis. This is because only in determining the QRS wave group may be calculated after the heart rate, heart rate variability and further testing and analysis of ECG and other details. A normal ECG signal waveform by a series of ......
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Size: 15360 |
Author: 罗朝辉 |
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Description: 心电信号的hurst指数算法，利用该指数可以用于区别正常心电信号和窦性房型早搏的心电信号-Hurst index ECG algorithm, using the index can be used to distinguish between normal sinus ECG and ECG chamber premature
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Size: 1024 |
Author: 卢佳 |
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Description: The method mainly consists in considering a reference normal ECG segment and input ECG (unknown behavior) segment.
Each segment of the input ECG T is compared to the reference segment using SEA.
The SEA method outputs a measure in the range [0..1] in terms of the correlation factor that reflects the degree of similarity between the reference and the segment under analysis. Based on this measure, the whole segment is classified as normal or abnormal.
A user specified threshold value on the correlation factor c is used for decision -The method mainly consists in considering a reference normal ECG segment and input ECG (unknown behavior) segment.
Each segment of the input ECG T is compared to the reference segment using SEA.
The SEA method outputs a measure in the range [0..1] in terms of the correlation factor that reflects the degree of similarity between the reference and the segment under analysis. Based on this measure, the whole segment is classified as normal or abnormal.
A user specified threshold value on the correlation factor c is used for decision
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Size: 1366016 |
Author: keerthi |
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Description: ecg各个波段生成程序-The aim of the ECG simulator is to produce the typical ECG waveforms of different leads and as many arrhythmias as possible. My ECG simulator is a matlab based simulator and is able to produce normal lead II ECG waveform
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Size: 4096 |
Author: tj |
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Description: analysis of ecg using cepstrum technique.......contains analysis of a normal ecg and 3 abnormal ecg
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Size: 1024 |
Author: vinusharma |
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Description: Samples of ECG signals we used in our project the
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Size: 984064 |
Author: zz |
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Description: 编写matlab程序对心电信号作图，找出所有R波发生位置（数据中提供了R波的位置），计算出心动周期，画出心率随时间变化的曲线，体会正常心律和异常心律的差异-Write matlab program for ECG mapping to identify all the R wave position (data provided in the position of the R-wave), calculate the cardiac cycle, draw a heart rate curve changes with time, experience the difference of the normal heart rhythm and abnormal heart rhythms
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Size: 175104 |
Author: angela |
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Description: 心电图峰值提取算法，可用来处理心电数据并计算心率并判断心律正常与否
-ECG peak extraction algorithm can be used to handle ECG data and calculate the heart rate and rhythm is normal or not judged
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Size: 96256 |
Author: 冯足平 |
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Description: Normal ECG test taken on 250 Hz (sampling frequency) You can use in order to obtain (and compare) the stress (from HRV) (compare with ecg stroop & ecg matematica )
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Size: 91136 |
Author: parrex |
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Description: 对正常ECG信号与异常信号分别进行小波包分解，对分解系数进行对比-The normal ECG signal and the abnormal signal were decomposed by wavelet packet, and the decomposition coefficient was compared
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Size: 7168 |
Author: 牛慧颖 |
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Description: 心电信号产生程序 仿真人体正常状态下的心电信号-ECG simulation of the human body have a procedure under normal ECG
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Size: 281600 |
Author: zhch55 |
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Description: The aim of the ECG simulator is to produce the typical ECG waveforms of different leads and as many arrhythmias as possible. My ECG simulator is a matlab based simulator and is able to produce normal lead II ECG waveform.
The use of a simulator has many advantages in the simulation of ECG waveforms. First one is saving of time and another one is removing the difficulties of taking real ECG signals with invasive and noninvasive methods. The ECG simulator enables us to analyze and study normal and abnormal ECG waveforms without actually using the ECG machine. One can simulate any given ECG waveform using the ECG simulator.
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Size: 281600 |
Author: sariD |
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