对用于低频商业近红外光谱系统中文物检测的莫莱特波形分析的评估
Tobias Bergmann1, Logan Froese2, Alwyn Gomez3,4
1Biosystems Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada.
Bioengineering (Basel, Switzerland)
|January 22, 2024
概括
波形分析有效地从区域大脑氧和 (rSO2) 信号中删除了人工物,改善了各种患者群体的非侵入性近红外光谱 (NIRS) 监测数据质量.
科学领域:
- 生物医学工程 生物医学工程
- 神经科学是一个神经科学.
- 医疗器械技术 医疗器械技术
背景情况:
- 区域大脑氧和 (rSO2) 通过近红外光谱 (NIRS) 非侵入性地测量大脑氧化.
- 在NIRS信号中的人工物显著限制了rSO2测量的可靠性.
- 手动移除文物是耗时和资源密集的.
研究的目的:
- 评估波纹分析作为一种自动化方法,用于清除rSO2数据中的简单信号损失文物.
- 评估波纹分析在不同患者群体中的有效性.
主要方法:
- 追溯观察性研究设计.
- 利用了来自健康对照组 (HC),脊椎手术患者 (SP) 和创伤性脑损伤 (TBI) 患者的动脉血压 (ABP) 和rSO2数据.
- 应用波波分析,检查波波系数和连贯性,以检测和删除文物.
主要成果:
- 波形分析表明,在物件移除方面,成功率很高:HC中100%;SP中99.8%;TBI中99.7%.
- 该方法有效地检测到rSO2信号中的信号损失工件.
- 精确地确定精确的文物时间是有限的.
结论:
- 波形分析是一种可行的自动化方法,用于清除NIRS衍生rSO2信号中的简单信号损失工件.
- 这种技术显示了集成到多层NIRS文物管理工具的潜力.
- 需要进一步的研究来完善波束分析的应用和时间精度.
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