研究人员开发了一种新的光电容积脉搏波描记法（PPG）基础模型，该模型通过在预训练期间利用心电图和呼吸数据等多模态生理信号来增强鲁棒性。这种方法使模型能够从嘈杂的PPG片段中学习，在不需要大量精选数据集的情况下提高其对真实世界、消费级数据的泛化能力。该模型在包括日常活动和心率预测在内的15个不同下游任务中的14个任务上取得了性能提升，使用的受试者数量明显少于现有的最先进方法。 AI
影响 增强了生理监测模型在消费级设备上的泛化能力。
排序理由 该集群包含一篇详细介绍新模型和方法的学术论文。
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arXiv:2606.07365v1 Announce Type: cross Abstract: Photoplethysmography (PPG), a non-invasive measure of changes in blood volume, is widely used in both wearable devices and clinical settings. Recent PPG foundation models either use open-source ICU datasets with pretraining paradi…
Photoplethysmography (PPG), a non-invasive measure of changes in blood volume, is widely used in both wearable devices and clinical settings. Recent PPG foundation models either use open-source ICU datasets with pretraining paradigms that require curated data and thus complicate …