English(EN) An Agent Architecture with Tools and Memory for Selective Correction of Wrist PPG Heart Rate Estimates

新型智能体架构提高腕部PPG心率估算精度

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-23 04:00

研究人员开发了一种新颖的智能体架构，旨在提高腕部光电容积脉搏波描记法（PPG）心率估算的准确性。该系统利用工具和记忆来选择性地纠正由运动伪影引起的错误，这些错误通常会降低单个测量窗口的质量。通过分析脉搏、运动和历史数据，该架构可以预测候选估算值的收益和危害，并指导风险门控以保留、校正或拒绝输出。该系统在四个公开数据集上进行了测试，结果显示平均绝对误差显著降低了高达44.5%，同时还量化了其校正的风险和收益。 AI

影响该架构通过提高心率数据的准确性，有望带来更可靠的可穿戴健康监测设备。

排序理由该条目是一篇学术论文，详细介绍了一种用于改进PPG心率估算的新型智能体架构。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Xu Wang, Shuhan Yi, Zhen Cheng · 2026-10-23 04:00

An Agent Architecture with Tools and Memory for Selective Correction of Wrist PPG Heart Rate Estimates

arXiv:2610.30688v1 Announce Type: new Abstract: Wrist photoplethysmography (PPG) heart rate estimates are vulnerable to motion artifacts, and corrections that reduce mean error can worsen individual windows. We propose an agent architecture with tools and memory around a fixed he…

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An Agent Architecture with Tools and Memory for Selective Correction of Wrist PPG Heart Rate Estimates

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