发表机构
University of Liverpool; Shanghai Artificial Intelligence Laboratory; Liverpool Heart & Chest Hospital NHS Trust（利物浦大学; 上海人工智能实验室; 利物浦心胸医院NHS信托机构）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对 PPG 难以预测心脏疾病的问题，提出 P2E-VQ 框架，通过 ECG 关联表示检索增强 PPG 表示，在 5 个数据集的 6 项下游任务中性能优于预训练基线。
AI 中文摘要
光体积描记法（Photoplethysmography, PPG）因成本低、易采集而被广泛应用于消费类可穿戴设备。然而，与心电图（Electrocardiography, ECG）不同，PPG 测量的是外周脉搏动力学而非心脏电活动，这限制了其预测依赖 ECG 特定形态学线索的心脏疾病的能力。现有方法试图通过从 PPG 信号重建 ECG 信号来弥合这一差距，但这种逆映射本质上是不适定的，忠实的波形重建并不一定能转化为下游任务性能的提升。为应对这一挑战，我们提出 P2E-VQ，这是一种检索增强型框架，它用 ECG 关联表示检索替代了 ECG 波形重建。具体而言，P2E-VQ 将 PPG 补丁（patch）转换为离散 token，并从仅由训练数据构建的记忆库中检索 ECG 关联信息。该过程增强了 PPG 表示，且推理阶段仅需 PPG 信号。在涵盖 6 项下游任务（包括临床终点预测和情感状态识别）的 5 个公开数据集上开展的大量实验表明，在统一的冻结特征线性探测协议下，P2E-VQ 始终优于预训练基线方法。
英文摘要
Photoplethysmography (PPG) is widely used in consumer wearables because of its low cost and ease of acquisition. However, unlike electrocardiography (ECG), PPG measures peripheral pulse dynamics rather than cardiac electrical activity, limiting its ability to predict cardiac conditions that rely on ECG-specific morphological cues. Existing methods attempt to bridge this gap by reconstructing ECG signals from PPG signals. However, this inverse mapping is inherently ill-posed, and faithful waveform reconstruction does not necessarily translate into improved downstream performance. To address this challenge, we propose P2E-VQ, a retrieval-augmented framework that replaces ECG waveform reconstruction with ECG-linked representation retrieval. Specifically, P2E-VQ converts PPG patches into discrete tokens and retrieves ECG-linked information from a memory bank constructed exclusively from the training data. This process augments PPG representations while requiring only PPG signals during inference. Extensive experiments on five public datasets covering six downstream tasks, including clinical endpoint prediction and affective state recognition, demonstrate that P2E-VQ consistently outperforms pretrained baselines under a unified frozen-feature linear-probing protocol.
Comments10 pages, 3 figures, 5 talbles
