通过线性回归来确定潮体积的传感器选择 - - 拉索与回归相对应的线性回归影响
Bernhard Laufer1, Paul D Docherty1,2, Rua Murray3
1Institute of Technical Medicine (ITeM), Furtwangen University, 78054 Villingen-Schwenningen, Germany.
Sensors (Basel, Switzerland)
|September 9, 2023
概括
这项研究通过回归分析优化了智能衫传感器的放置,以测量呼吸体积. 拉索方法被证明比里奇回归更有效,使呼吸监测更方便.
科学领域:
- 生物医学工程 生物医学工程
- 可穿戴技术可穿戴技术
- 呼吸系统生理学 呼吸系统生理学
背景情况:
- 呼吸道体积测量对于医学诊断和监测至关重要.
- 传统的螺旋计可能不方便,特别是在家庭护理或医院环境中.
- 智能衫为呼吸监测提供了一个潜在的非侵入性替代方案.
研究的目的:
- 为了确定最佳的传感器选择和放置在智能衫上,以准确估计呼吸体积.
- 为了比较Ridge回归和拉索回归方法在传感器优化方面的有效性.
- 评估使用智能衫来取代或补充螺旋计的可行性.
主要方法:
- 利用运动捕捉系统捕获的上肢表面运动数据.
- 应用回归和最小绝对收缩和选择操作员 (Lasso) 回归技术.
- 两种回归方法之间的传感器子集选择和性能比较.
主要成果:
- 拉索回归比里奇回归有优势,提供稀疏的解决方案,并提高了异常值的稳定性.
- 这两种方法都确定了类似的传感器子集,与详尽的搜索相比,大大降低了计算需求.
- 智能衫上的优化传感器放置可以准确地恢复呼吸系统参数.
结论:
- 配备了最佳位置的传感器的智能衫可以提供一种方便而准确的呼吸体积估计方法.
- 拉索回归方法有利于在呼吸监测中优化智能衫传感器.
- 这项技术有望在某些临床和家庭护理场景中取代螺旋计.
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