Opportunities and challenges for ultra low power signal processing in wearable healthcare
Opportunities and challenges for ultra low power signal processing in wearable healthcare
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DOI：
10.1109/eusipco.2015.7362418
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发表时间：
2015-12
期刊：
影响因子：
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通讯作者：
A. Casson
中科院分区：
文献类型：
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作者：
A. Casson
可穿戴设备通过允许对一系列身体参数进行不显眼和长期的监测，开始彻底改变医疗保健。将更先进的信号处理算法嵌入可穿戴设备本身可以：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;以及其他好处。设计的挑战是在非常有限的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。使用一个新的审查，并从EEG分析的案例研究的例子，本文概述了最先进的可穿戴算法。它展示了机遇和挑战，突出了业绩评估和衡量可变性的公开挑战。
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.