Opportunities and challenges for ultra low power signal processing in wearable healthcare

A. Casson
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引用次数: 14

Abstract

Wearable devices are starting to revolutionise healthcare by allowing the unobtrusive and long term monitoring of a range of body parameters. Embedding more advanced signal processing algorithms into the wearable itself can: reduce system power consumption; increase device functionality; and enable closed-loop recording-stimulation with minimal latency; amongst other benefits. The design challenge is in realising algorithms within the very limited power budgets available. Wearable algorithms are now emerging to answer this challenge. Using a new review, and examples from a case study on EEG analysis, this article overviews the state-of-the-art in wearable algorithms. It demonstrates the opportunities and challenges, highlighting the open challenge of performance assessment and measuring variability.
超低功耗信号处理在可穿戴医疗领域的机遇与挑战
可穿戴设备允许对一系列身体参数进行不显眼的长期监测,从而开始彻底改变医疗保健。在可穿戴设备中嵌入更先进的信号处理算法可以:降低系统功耗;增加设备功能;并以最小的延迟实现闭环记录刺激;还有其他好处。设计上的挑战在于如何在有限的可用功率预算内实现算法。可穿戴算法正在出现,以应对这一挑战。本文采用一种新的综述,并从脑电图分析的案例研究中举例,概述了可穿戴算法的最新进展。它展示了机遇和挑战,突出了绩效评估和测量可变性的公开挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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