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English(EN) CogAdapt: Transferring Clinical ECG Foundation Models to Wearable Cognitive Load Assessment via Lead Adaptation

CogAdapt框架将临床心电图模型适配到可穿戴认知负荷评估

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了CogAdapt框架，旨在将现有的临床心电图基础模型适配到可穿戴认知负荷评估中。这是必要的，因为在临床数据上训练的模型由于信号配置和任务目标的差异，不能直接迁移到可穿戴传感器上。CogAdapt利用“LeadBridge”适配器将3导联可穿戴信号转换为12导联表示，并采用“ProFine”策略进行渐进式微调，在公开数据集上取得了更好的性能。 AI

影响 通过利用预训练的基础模型，能够从可穿戴设备中实现更准确和个性化的认知负荷评估。

排序理由 该集群包含一篇学术论文，详细介绍了适配现有模型的新框架和方法论。

在 arXiv cs.AI 阅读 →

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CogAdapt框架将临床心电图模型适配到可穿戴认知负荷评估

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该集群包含一篇学术论文，详细介绍了适配现有模型的新框架和方法论。
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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Amir Mousavi, Mohammad Sadegh Sirjani, Erfan Nourbakhsh, Mimi Xie, Rocky Slavin, Leslie Neely, John Davis, John Quarles ·

    CogAdapt：通过导联适应将临床心电图基础模型迁移到可穿戴认知负荷评估

    arXiv:2605.22774v1 Announce Type: new Abstract: Real-time cognitive load assessment is essential for adaptive human-computer interaction but remains challenging due to limited labeled data and poor cross-subject generalization. Recent ECG foundation models pre-trained on millions…

  2. arXiv cs.AI TIER_1 English(EN) · John Quarles ·

    CogAdapt：通过导联适应将临床心电图基础模型迁移到可穿戴认知负荷评估

    Real-time cognitive load assessment is essential for adaptive human-computer interaction but remains challenging due to limited labeled data and poor cross-subject generalization. Recent ECG foundation models pre-trained on millions of clinical recordings offer rich representatio…

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