English(EN) End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables

研究人员优化用于可穿戴血压监测的深度神经网络

作者 PulseAugur 编辑部 · [1 个来源] · 2026-04-28 04:00

研究人员开发了一个全自动化流程来优化用于可穿戴设备血压估算的深度神经网络。该方法结合了神经架构搜索、剪枝和混合精度搜索，以创建紧凑高效的模型。优化后的网络在参数和内存使用量方面显著减少，同时保持或提高了准确性，从而能够进行设备端处理以增强用户隐私。 AI

影响实现了更高效的设备端健康监测AI，提高了隐私性并减少了对云处理的依赖。

排序理由这是一篇研究论文，详细介绍了一种用于优化可穿戴设备特定应用神经网络的新方法。

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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arXiv cs.LG TIER_1 English(EN) · Francesco Carlucci, Giovanni Pollo, Xiaying Wang, Massimo Poncino, Enrico Macii, Luca Benini, Sara Vinco, Alessio Burrello, Daniele Jahier Pagliari · 2026-04-28 04:00

面向可穿戴设备基于PPG的血压估算的全自动深度神经网络优化

arXiv:2604.10117v2 Announce Type: replace Abstract: Photoplethysmography (PPG)-based blood pressure (BP) estimation is a challenging task, particularly on resource-constrained wearable devices. However, fully on-board processing is desirable to ensure user data confidentiality. R…