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Asynchronous Binary Compressive Sensing for Wireless Body Sensor Networks

机译:无线人体传感器网络的异步二进制压缩传感

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Next-generation Wireless Body Sensor Networks (WBSNs) calls for miniaturization and power-efficient integration for long-term monitoring, real-time diagnostics and patient-centered healthcare solutions. However, state-of-the-art WBSN prototypes remain challenged by stringent power constraints and large form factors. The recently proposed asynchronous compressive sensing scheme suggests an efficient way to improve power consumption by reducing the data volume in energy-hungry radio links. In this paper, we present a modified front-end called Asynchronous Binary Compressive Sensing (ABCS) for WBSNs. A low-cost reconstruction method is proposed that exploits the embedded binary signal structure in the ABCS. By incorporating binary amplitude as a prior, better signal recovery performance is obtained comparing with the traditional approaches. Analyses and simulations with an ECG recording confirm the ABCS front-end outperforms the conventional CS approaches in terms of hardware complexity, power consumption and system flexibility.
机译:下一代无线人体传感器网络(WBSN)要求实现小型化和高能效集成,以进行长期监控,实时诊断和以患者为中心的医疗保健解决方案。但是,最新的WBSN原型仍然受到严格的功率限制和大尺寸因素的挑战。最近提出的异步压缩感测方案提出了一种有效的方法,可以通过减少耗能的无线电链路中的数据量来提高功耗。在本文中,我们提出了一种用于WBSN的改进的称为异步二进制压缩感知(ABCS)的前端。提出了一种利用ABCS中嵌入的二进制信号结构的低成本重建方法。通过将二进制幅度作为先验,与传统方法相比,可以获得更好的信号恢复性能。通过ECG记录进行的分析和仿真证实,ABCS前端在硬件复杂性,功耗和系统灵活性方面优于传统CS方法。

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