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English(EN) Low-cost Embedded Breathing Rate Determination Using 802.15.4z IR-UWB Hardware for Remote Healthcare

低成本UWB雷达使用CNN估算呼吸率,用于远程医疗

研究人员开发了一种低成本系统,使用符合IEEE 802.15.4z标准的IR-UWB硬件,为远程医疗应用估算人类呼吸率。一个卷积神经网络(CNN)被训练用于从UWB信道冲激响应数据预测呼吸率,在未见过的情况下实现了1.73次/分钟(BPM)的平均绝对误差。该CNN模型针对嵌入式部署进行了优化,内存需求减少了67%,推理时间减少了62%,误差仅略微增加,使其可以在nRF52840片上系统上运行。该系统能效极高,一次充电可连续监测房间运行超过260天。 AI

影响 实现了低成本、连续的健康监测,可能改善呼吸系统疾病的早期检测。

排序理由 学术论文,详细介绍了UWB雷达和CNN在健康监测方面的新应用。[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 →

低成本UWB雷达使用CNN估算呼吸率,用于远程医疗

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学术论文,详细介绍了UWB雷达和CNN在健康监测方面的新应用。[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) · Anton Lambrecht, Stijn Luchie, Jaron Fontaine, Ben Van Herbruggen, Adnan Shahid, Eli De Poorter ·

    使用 802.15.4z IR-UWB 硬件进行低成本嵌入式呼吸速率测定,用于远程医疗

    arXiv:2504.03772v3 Announce Type: replace-cross Abstract: Respiratory diseases account for a significant portion of global mortality. Affordable and early detection is an effective way of addressing these ailments. To this end, a low-cost commercial off-the-shelf (COTS), IEEE 802…