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首页> 外文期刊>Journal of signal processing systems for signal, image, and video technology >Coarse Grained Reconfigurable Array Based Architecture for Low Power Real-Time Seizure Detection
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Coarse Grained Reconfigurable Array Based Architecture for Low Power Real-Time Seizure Detection

机译:基于粗粒度可重构阵列的低功耗实时癫痫发作检测架构

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摘要

There is increasing research and commercial interest in miniature on-body and implantable devices for continuous real-time biosignal monitoring. A key challenge in realizing this vision is in implementation of biosignal processing algorithms with acceptably low energy consumption. In this article, we investigate implementation of the REACT algorithm for real-time epileptic seizure detection on a Coarse Grained Reconfigurable Array (CGRA) based architecture. Computationally expensive biosignal processing tasks are offloaded from a conventional Digital Signal Processor (DSP) to the CGRA. The CGRA is designed to support low power biosignal processing by means of a systolic architecture, flexible interconnect and low resource usage. The CGRA architecture is shown to provide 38% and 60% improvements in energy consumption and in performance, respectively, for the REACT system, without the use of voltage scaling or increased clock frequency.
机译:对于连续实时生物信号监测的微型人体和可植入设备的研究和商业兴趣日益增加。实现这一愿景的关键挑战是实现具有可接受的低能耗的生物信号处理算法。在本文中,我们研究了基于粗粒度可重配置阵列(CGRA)的实时癫痫发作检测的REACT算法的实现。计算上昂贵的生物信号处理任务已从常规的数字信号处理器(DSP)转移到CGRA。 CGRA旨在通过收缩架构,灵活的互连和低资源使用率来支持低功率生物信号处理。事实证明,CGRA架构可为REACT系统分别提供38%和60%的能耗和性能改进,而无需使用电压缩放或增加的时钟频率。

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