This paper presents an algorithm to detect strength noise segments and denoise them in dynamic ECG for improving the accuracy of auto analysis.
为提高动态心电图自动分析的准确率，本文提出一种检测动态心电图中强噪声段及去噪的方法。
The design of the multi-channel bioelectric signal acquisition module is based on Micro-Controller-Unit (MCU) which can measure ECG and detect heart rate during sleep.
基于MCU的多路电生理信号采集模块适用于睡眠中的应用，为睡眠心率检测提供最直观、严格的手段。
The wavelet transform does multi-resolution analysis on the signal which clarifies the electrocardiogram (ECG) signal characteristics to more easily detect the QRS complex.
小波分解对信号做多分辨率分解，可以突出信号的特征信息，便于QRS波群检测。
Conclusion the improved spectrum-estimating method we proposed provides a new means to detect the concealed TWA in ECG.
结论改进的谱估计法提供了一种新的TWA检测手段，可以更全面的检测和观察心电中可能隐含的TWA信号。
Invasive arterial blood pressure monitoring is very important in thoracic tumor surgery. It can help to timely detect cardiac problems during ECG interference.
开胸手术术中有创动脉压监测非常重要，在心电图受到干扰时，也可及时发现问题。
Cardiovascular disease is one of the dangerous diseases that seriously endanger the human health, while Electrocardiogram (ECG) is an effective method used in clinic to detect cardiovascular disease.
心血管疾病是当今危害人类健康的主要疾病之一，心电图(ECG)检查是临床上诊断心血管疾病的重要方法。
Result: it is an effective method to detect the heart vibration signal compared with simultaneous ECG recording.
结果：心音与心电的同步采集信号的对照显示该方法能够有效提取心音信号。
This system can detect QRS complex and analyze in real-time and embed file system, so the ECG data can be stored in text form and data's readability and translatability are enhanced.
系统采取实时的QRS波检测算法，并嵌入文件系统将心电数据以文本的形式存储，提高了数据的可读性和移植性。
Based on analysis of Wavelet Transform of ECG signal and the law of its change across different scales, this algorithm can automatically detect 6 kinds of arrhythmia.
该算法利用连续小波变换及其在不同尺度上的变化规律对心电信号进行分析，可以对常见的六种心律失常进行自动判别。
Based on analysis of Wavelet Transform of ECG signal and the law of its change across different scales, this algorithm can automatically detect 6 kinds of arrhythmia.
该算法利用连续小波变换及其在不同尺度上的变化规律对心电信号进行分析，可以对常见的六种心律失常进行自动判别。
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