XBioSiP：一种边缘近似生物信号处理方法
XBioSiP: A Methodology for Approximate Bio-Signal Processing at the Edge
摘要：
生物信号表现出高冗余性，并且用于其处理的算法具有固有的错误恢复能力。这种特性可以通过近似计算的新兴趋势来提高物联网边缘（可穿戴设备）的能效。本文介绍了XBioSiP，一种新的方法，用于近似生物信号处理，采用两个质量评估阶段，在预处理和生物信号处理阶段，以确定近似参数。因此，它实现了高能量节省，同时满足用户确定的质量约束。我们的方法实现了，高达19倍和22倍的QRS峰值检测算法的能量消耗减少0%和<1%的峰值检测精度损失，分别。
英文摘要：
Bio-signals exhibit high redundancy, and the algorithms for their processing are inherently error resilient. This property can be leveraged to improve the energy-efficiency of IoT-Edge (wearables) through the emerging trend of approximate computing. This paper presents XBioSiP, a novel methodology for approximate bio-signal processing that employs two quality evaluation stages, during the pre-processing and bio-signal processing stages, to determine the approximation parameters. It thereby achieves high energy savings while satisfying the user-determined quality constraint. Our methodology achieves, up to 19x and 22x reduction in the energy consumption of a QRS peak detection algorithm for 0% and <1% loss in peak detection accuracy, respectively.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
