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English(EN) Interaction-Gated Time-Frequency Learning for Parameter-Efficient PPG-Based Heart Rate Estimation

新的TF-IG框架改进了PPG信号的心率估计

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种名为TF-IG的新型参数高效框架，用于从光电容积脉搏波（PPG）信号估计心率。该方法通过双分支架构将时间波形分析与频域周期性提取相结合。交互门控融合模块平衡了这两个域，提高了准确性和效率。在BIDMC PPG和呼吸数据集上的实验证明了TF-IG的有效性，在仅有84.6K参数的情况下实现了1.227 BPM的平均绝对误差。 AI

影响 这项研究提供了一种使用PPG信号进行心率估计的更有效方法，有望改进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技术方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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新的TF-IG框架改进了PPG信号的心率估计

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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Anh Khoi Pham, Phat Lam, Thien Truong Nguyen Ly, Lam Pham ·

    用于参数高效 PPG 心率估计的交互门控时频学习

    arXiv:2610.28693v1 Announce Type: new Abstract: Photoplethysmography (PPG) enables low-cost and non-invasive heart rate (HR) monitoring but remains sensitive to waveform distortion, physiological variability, and measurement interference. Temporal waveform characteristics and fre…

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