Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran.
PLoS One. 2022 Feb 8;17(2):e0262219. doi: 10.1371/journal.pone.0262219. eCollection 2022.
The demand for long-term continuous care has led healthcare experts to focus on development challenges. On-chip energy consumption as a key challenge can be addressed by data reduction techniques. In this paper, the pseudo periodic nature of ElectroCardioGram(ECG) signals has been used to completely remove redundancy from frames. Compressing aligned QRS complexes by Compressed Sensing (CS), result in highly redundant measurement vectors. By removing this redundancy, a high cluster of near zero samples is gained. The efficiency of the proposed algorithm is assessed using the standard MIT-BIH database. The results indicate that by aligning ECG frames, the proposed technique can achieve superior reconstruction quality compared to state-of-the-art techniques for all compression ratios. This study proves that by aligning ECG frames with a 0.05% unaligned frame rate(R-peak detection error), more compression could be gained for PRD > 5% when 5-bit non-uniform quantizer is used. Furthermore, analysis done on power consumption of the proposed technique, indicates that a very good recovery performance can be gained by only consuming 4.9μW more energy per frame compared to traditional CS.
对长期持续护理的需求促使医疗保健专家专注于开发挑战。片上能耗作为一个关键挑战，可以通过数据缩减技术来解决。在本文中，心电（ECG）信号的伪周期性被用来从帧中完全去除冗余。通过压缩感知（CS）对对齐的 QRS 复合体进行压缩，会导致高度冗余的测量向量。通过去除这种冗余，可以获得高度集中的近零样本。使用标准的麻省理工学院生物医学工程研究所（MIT-BIH）数据库评估了所提出算法的效率。结果表明，通过对齐 ECG 帧，与最先进的技术相比，该技术可以在所有压缩比下实现更好的重建质量。这项研究证明，通过以 0.05%的未对准帧速率（R-峰值检测误差）对齐 ECG 帧，可以在使用 5 位非均匀量化器时，在 PRD>5%时获得更多的压缩。此外，对所提出技术的功耗分析表明，与传统的 CS 相比，每帧仅消耗 4.9μW 多的能量就可以获得非常好的恢复性能。
