云计算将使可穿戴设备驱动的纵向血液动力图成为可能
Cyrus Tanade1, Emily Rakestraw1, William Ladd1
1Duke University, Durham, NC, USA.
International Conference for High Performance Computing, Networking, Storage and Analysis : [proceedings]. SC (Conference : Supercomputing)
|June 28, 2024
概括
本研究介绍了一个基于云的框架,用于从可穿戴设备数据中创建3D患者特定的血液动力学图. 这项创新使长期的血液动力学跟踪成为可能,克服了以前的计算限制.
科学领域:
- 心血管研究的心血管研究.
- 计算流体动力学 计算流体动力学
- 医疗器械技术 医疗器械技术
背景情况:
- 纵向血液动力学监测至关重要,但面临着重大的技术和计算障碍.
- 目前的个性化数字双胞胎模型需要大量的计算资源,这限制了它们在日常患者监测中的应用.
- 现有的方法很难在较长时间内扩展血液动力学流量采样.
研究的目的:
- 开发一种新的基于云的,时间平行框架,用于生成患者特定的3D纵向血液动力学图.
- 克服当前用于血液动力学数字双胞胎模拟的计算局限性.
- 通过可穿戴设备的数据实现连续的血液动力学跟踪.
主要方法:
- 实现基于云的,时间平行计算框架.
- 从可穿戴设备集成连续数据流.
- 验证使用已确定的基础真相数据对750次心跳进行验证.
- 利用一组初始的固定模拟来提供可穿戴数据.
主要成果:
- 成功生成了第一个针对患者的3D纵向血液动力学图.
- 拟议方法与地面真相数据的证明有效性.
- 与传统模拟方法相比,计算时间显著减少.
结论:
- 拟议的框架有效地解决了长期血液动力学监测的挑战.
- 与云计算相结合的可穿戴设备集成为个性化,纵向血液动力学评估提供了可行的解决方案.
- 这种方法为先进的患者监测和治疗评估铺平了道路.
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