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Effects of non-uniform quantization on ECG acquired using Compressed Sensing

机译:非均匀量化对使用压缩传感获取的心电图的影响

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摘要

This paper analyzes the effects of quantization on Compressed Sensing (CS) measurements applied to Electrocardiogram (ECG) signals. Two methods of quantization are proposed in this paper: uniform and non-uniform. Reconstruction is performed using a dictionary based on the Mexican Hat wavelet. A distortion-based performance metric Percent Root-mean-squared Difference (PRD) will be monitored at various Compression Ratios (CR) to quantify the impact of quantization. The energy cost of transmission is also evaluated for different levels of quantization and compared, at certain PRD levels. The results demonstrate that non-uniform quantization outperforms the uniform approach and that employing nonuniform quantization improves implementation efficiency for applications with acceptable PRDs above 6.75%. Results show that utilizing non-uniform quantization can increase the CR from 9.8 to 14.1 for a PRD of 30%. Furthermore, this amounts to a 28.91% reduction in wireless transmission per frame from 37.7 μJ to 26.8 μJ considering Bluetooth Low Energy (BLE) as a target wireless communication protocol.
机译:本文分析了量化对应用于心电图(ECG)信号的压缩感知(CS)测量的影响。本文提出了两种量化方法:统一和非统一。使用基于墨西哥帽小波的字典执行重建。将在各种压缩比(CR)处监视基于失真的性能度量百分比均方根差(PRD),以量化量化的影响。在某些PRD级别,还针对不同的量化级别评估了传输的能量成本,并进行了比较。结果表明,非均匀量化优于统一方法,采用非均匀量化可提高PRD高于6.75%的应用程序的实现效率。结果表明,对于30%的PRD,使用非均匀量化可以将CR从9.8提高到14.1。此外,考虑到低功耗蓝牙(BLE)作为目标无线通信协议,这相当于每帧无线传输从37.7μJ减少到26.8μJ降低了28.91%。

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