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English(EN) Physiological Information Reliability: Cross-Layer Adaptive Resource Allocation for Cardiovascular Sensing

新框架通过自适应资源分配增强心血管传感

研究人员开发了一个名为生理信息可靠性(PIR)的新框架,以提高心血管传感系统的准确性和效率。PIR采用上下文老虎机方法,根据信号质量、无线条件、能量水平和计算约束来调整传感和通信决策。该框架集成了心电图(ECG)和光电容积脉搏波描记图(PPG)信号质量估计与自适应网络编码层。实验表明,与传统方法相比,PIR-LinUCB在保持医疗延迟和性能的同时,降低了能耗。 AI

影响 该框架可能导致更高效、更可靠的可穿戴健康监测设备。

排序理由 该集群包含一篇详细介绍新信号处理框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新框架通过自适应资源分配增强心血管传感

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该集群包含一篇详细介绍新信号处理框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Navaneeth Krishnan Kamalakannan, Janakiraman Kamalakannan, Harinisri Velmurugan ·

    生理信息可靠性:面向心血管传感的跨层自适应资源分配

    arXiv:2609.00435v1 Announce Type: cross Abstract: Cardiovascular sensing systems must preserve clinically useful information despite signal degradation, wireless losses, energy constraints, and edge-computation latency. We introduce Physiological Information Reliability (PIR), a …