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Advanced Wavelet Transform Techniques for ECG Feature Extraction

机译:ECG特征提取的高级小波变换技术

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Existing life care systems simply monitor human health and rely on a centralized server to store and process sensed data, leading to a high cost of system maintenance, yet with limited services and low performance. One of the important parameter in health Monitoring is ECG and Wireless ECG acquisition has emerged as a comfortable low-cost technology for continuous Cardiac Monitoring. The analysis of ECG is widely used for diagnosing many cardiac diseases, which are the main cause mortality in developed countries. Wireless ECG sensors have been employed to monitor human health and provide life care services. We present a scheme for ECG feature extraction for capturing ECG signals that will be compared with standard database in real time by using either curvelets or shapelets. Among the various techniques developed for ECG extraction time domain analysis, frequency domain analysis and wavelet transform are predominant techniques. The new advanced Wavelet Transform specially designed for image processing like shapelets, ridgelets can give more accurate results than conventional Waveform Techniques. It is also proposed to develop this system which is compatible with various Devices such as Desktop Computers, PDA and smart phones.
机译:现有的终身保健系统只是监控人类健康,并依靠集中式服务器来存储和处理感测数据,导致系统维护的高成本,但服务有限,性能低。健康监测中的一个重要参数是ECG和无线ECG采集已成为连续心脏监测的舒适低成本技术。 ECG的分析广泛用于诊断许多心脏病,这是发达国家的主要原因。无线ECG传感器已被用于监测人类健康并提供终身保健服务。我们提出了一种ECG特征提取的方案,用于捕获ECG信号,通过使用曲线或翻头实时与标准数据库进行比较。在为ECG提取时域分析开发的各种技术中,频域分析和小波变换是主要的技术。新的高级小波变换专门设计用于图像处理,如Shapelets,Ridgelets可以提供比传统波形技术更准确的结果。还建议开发该系统,该系统与各种设备兼容,例如台式计算机,PDA和智能手机。

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