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English(EN) Pose-Based Fall Detection System: Efficient Monitoring on Standard CPUs

已撤回的研究论文详述了基于CPU的跌倒检测系统

一篇已被撤回的研究论文提出了一种用于老年人护理的跌倒检测系统,该系统可在标准CPU上高效运行。该系统利用MediaPipe框架的姿态估计算法来分析运动和身体姿势,无需额外的传感器或高端硬件。这种方法旨在为辅助生活设施中的居民安全监控提供一种实用且资源高效的解决方案。 AI

影响 这项研究探索了一种在医疗保健环境中进行AI驱动监控的更易于访问的方法。

排序理由 该集群包含一篇已撤回的学术论文,其中详细介绍了技术方法。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.AI 阅读 →

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已撤回的研究论文详述了基于CPU的跌倒检测系统

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该集群包含一篇已撤回的学术论文,其中详细介绍了技术方法。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Vinayak Mali, Saurabh Jaiswal ·

    基于姿态的跌倒检测系统:在标准CPU上实现高效监控

    arXiv:2503.19501v2 Announce Type: replace-cross Abstract: Falls among elderly residents in assisted living homes pose significant health risks, often leading to injuries and a decreased quality of life. Current fall detection solutions typically rely on sensor-based systems that …