基于ROI延迟扩张和基本频率受限制的夜间IPPG算法的研究FastICAICA
Jiang Wu1, Jian Qiu1, Li Peng1
1School of Electronic Science and Engineering (School of Microelectronics), South China Normal University, Guangdong, Guangzhou 510006, People's Republic of China.
Physiological measurement
|June 27, 2025
概括
这项研究引入了一种新的方法,将FastICA与TDMDE-ROI-Ex结合起来,用于使用成像光电脉学 (IPPG) 精确的夜间心率监测. 这种方法显著减少了运动器件,提高了测量可靠性,实现了比现有方法更低的误差率.
科学领域:
- 生物医学工程 生物医学工程
- 信号处理 信号处理
- 遥感 遥感 遥感 遥感
背景情况:
- 使用成像光电脉学 (IPPG) 监测夜间心率 (HR) 面临着来自运动器件的挑战以及识别最佳感兴趣区域 (ROI) 的困难.
- 由于这些固有的局限性,现有的IPPG方法在睡眠期间难以准确和可靠.
研究的目的:
- 使用IPPG提高夜间HR测量的准确性和可靠性.
- 开发一种创新的方法,将FastICA与时间延迟多维扩展感兴趣区域提取 (TDMDE-ROI-Ex) 技术相结合.
- 为了克服夜间IPPG中运动工件和ROI识别所带来的挑战.
主要方法:
- 一种双方法策略,涉及面部检测,灰度集群用于ROI精确定位,以及用于多通道IPPG信号合成的相互信息延迟.
- 应用HR的基本频率作为FastICA (HRFFC-FastICA) 代过程中的先前约束,以减轻初始价值波动.
- 使用MR-NIRP数据集进行验证,随后进行废除研究和对现有的夜间IPPG算法进行比较评估.
主要成果:
- 拟议的HRFFC-FastICA方法实现了4.57bpm的平均绝对误差 (MAE) 和5.95bpm的根平均平方误差 (RMSE).
- 与SparsePPG和PhysNet相比,显示出显著的改进,MAE增长了8.39 bpm,RMSE减少了17.83 bpm.
- 与替代方法相比,达到了较窄的95%布兰德-阿尔特曼置信区间 (9.5到-12.8bpm),表明精确度更高.
结论:
- 在TDMDE-ROI-Ex方法显著减少依赖面部运动的ROI识别.
- 在FastICA中,HRFFC-FastICA有效地对抗运动工件和初始值灵敏度.
- 综合方法大大提高了夜间IPPG监控的稳定性和稳定性,扩大了其应用范围.
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