• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>IEEE International Conference on Bioinformatics and Biomedicine >BpMC: A novel algorithm retrieving multilayered tissue bio-optical properties for non-invasive blood glucose measurement
【24h】

BpMC: A novel algorithm retrieving multilayered tissue bio-optical properties for non-invasive blood glucose measurement

机译：BpMC：一种用于无创血糖测量的检索多层组织生物光学特性的新颖算法

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Non-invasive blood glucose measurement is a crucial challenge in both academic and industry communities. Currently, most of non-invasive solutions are developed based on optical signals. However, their accuracy is still far from clinical requirements if these measured optical signals directly used to estimate corresponding glucose levels. To solve this challenge, a novel Back-propagation Monte Carlo (BpMC) algorithm is proposed to retrieve bio-optical properties in human multilayered tissues. Build on BpMC algorithm, two non-invasive blood glucose estimation models, namely BpMC-DEE and BpMC-CNN, are conceived. In contrast to existing black-box solutions, BpMC-DEE is a white-box model that is more reliable in clinical. BpMC-CNN is a gray-box model whose results are more accurate in cost of a larger dataset and higher computing complexity. BpMC-DEE and BpMC-CNN are embedded and implemented into our designed noninvasive device - Earlight, for clinical trials. The clinical trial results demonstrate that correlation coefficients of these two models reach 0.852 and 0.895, respectively, referring to invasive glucometers. In terms of Clarke Error Grids, our proposals account for 90.6% and 93.5% statistic points in regions A and B, respectively. Moreover, the BpMC algorithm can be applied to other components measurement of biological tissues.
机译：在学术界和行业界，无创血糖测量都是一项至关重要的挑战。当前，大多数非侵入性解决方案都是基于光信号开发的。但是，如果将这些测得的光信号直接用于估计相应的葡萄糖水平，则其准确性仍远未达到临床要求。为了解决这一挑战，提出了一种新颖的反向传播蒙特卡洛（BpMC）算法，以检索人体多层组织中的生物光学特性。在BpMC算法的基础上，提出了两种无创血糖评估模型，即BpMC-DEE和BpMC-CNN。与现有的黑盒解决方案相比，BpMC-DEE是一种白盒模型，在临床上更可靠。 BpMC-CNN是灰盒模型，其结果在更大数据集的成本和更高的计算复杂度上更为准确。 BpMC-DEE和BpMC-CNN已嵌入并实施到我们设计的无创设备-Earlight中，用于临床试验。临床试验结果表明，相对于侵入式血糖仪，这两个模型的相关系数分别达到0.852和0.895。就克拉克误差网格而言，我们的建议分别占区域A和区域B的90.6 \％和93.5 \％统计点。此外，BpMC算法可以应用于生物组织的其他成分测量。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号