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BeatFlow-ECG：从可穿戴信号重建ECG
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BeatFlow-ECG 是一项关于从可穿戴信号重建心电图（ECG）的研究。最新报道（2026-10-08，arXiv · Machine Learning Theory）提出一种条件修正流模型（rectified flow），从同步光电容积脉搏波（PPG）与惯性测量信号重构单通道 ECG。该模型采用卷积编码器-解码器结构，并加入 Transformer 瓶颈与显式流时间条件。这是目前该事件唯一报道，尚未见早期版本或矛盾信息。
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LatestOct 8
2026-10-08 报道提出条件修正流模型，从同步PPG与惯性测量重构单通道ECG。Timeline
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Oct 8, 2026
- arXiv · Machine Learning TheoryBeatFlow-ECG：用修正流模型从间接可穿戴信号重构 ECG
BeatFlow-ECG 提出一种条件修正流模型，从同步 PPG 与惯性测量重构单通道 ECG，采用卷积编码器-解码器加 Transformer 瓶颈与显式流时间条件。
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