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Low Complexity Adaptive Noise Canceller for Mobile Phones Based Remote Health Monitoring

机译:用于手机的远程健康监测的低复杂度自适应噪声消除器

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Mobile phones are gaining acceptance to become an effective tool for remote health monitoring. On one hand, during electrocardiographic (ECG) recording, the presence of various forms of noise is inevitable. On the other hand, algorithms for adaptive noise cancellation must be shared by limited computational power offered by the mobile phones. This paper describes a new adaptive noise canceller scheme, with low computational complexity, for simultaneous cancellation of various forms of noise in ECG signal. The proposed scheme is comprised of two stages. The first stage uses an adaptive notch filters, which are used to eliminate power-line interference from the primary and reference input signals, whereas the other noises are reduced using modified LMS algorithm in the second stage. Low power consumption and lower silicon area are key issues in mobile phones based adaptive noise cancellation. The reduction in complexity is obtained by using log-log LMS algorithm for updating adaptive filters in the proposed scheme. A comprehensive complexity and performance analysis between the proposed and traditional schemes are provided.
机译:移动电话正逐渐被接受,成为一种用于远程健康监控的有效工具。一方面,在心电图(ECG)记录期间,不可避免地会出现各种形式的噪声。另一方面,用于自适应噪声消除的算法必须由移动电话提供的有限计算能力来共享。本文介绍了一种新的自适应噪声消除器方案,该方案具有低计算复杂度,可同时消除ECG信号中各种形式的噪声。提议的方案包括两个阶段。第一级使用自适应陷波滤波器,该滤波器用于消除来自主输入信号和参考输入信号的电力线干扰,而在第二级中,使用改进的LMS算法降低了其他噪声。低功耗和低硅片面积是基于移动电话的自适应噪声消除的关键问题。通过使用对数对数LMS算法来更新所提出方案中的自适应滤波器,可以降低复杂度。提供了建议的方案与传统方案之间的综合复杂性和性能分析。

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