OculusGraphy:使用离散和连续波形变形的内炎子模型中电网膜图的信号分析
Aleksei Zhdanov1,2, Paul Constable3, Sultan Mohammad Manjur4
1Machine Learning and Data Analytics Lab, University of Erlangen-Nuremberg, 91052 Erlangen, Germany.
Bioengineering (Basel, Switzerland)
|June 28, 2023
概括
对电网红图 (ERG) 信号的波形分析揭示了人类和子眼睛之间的差异. 哈尔波小组有效地跟踪了子内耳炎的治疗恢复,为视网膜疾病提供了新的结果指标.
科学领域:
- 眼科医生 眼科 眼科
- 生物医学工程 生物医学工程
- 信号处理 信号处理
背景情况:
- 电视网膜图 (ERG) 是一种临床工具,用于评估视网膜功能.
- ERG波形反映了各种视网膜细胞的总神经活动.
研究的目的:
- 用波形变换分析时间和时间频域中的ERG波形.
- 在使用ERG的子内炎模型中评估治疗效果.
- 为了比较子ERG与正常人ERG.
主要方法:
- 离散波形变换 (DWT) 和连续波形变换 (CWT) 应用于ERG数据.
- 使用多个母波段 (Daubechies,Ricker,bior3.1,Morlet,Haar,Gaussian) 分析了波段表.
- 子内炎的ERG信号与正常的人类ERG进行了比较.
主要成果:
- 在子和人类ERG之间的波形电脑表中观察到明显的差异.
- 子内炎模型显示波形恢复与治疗相关.
- 与儿童信号相比,成人人类ERG信号的功率更高.
结论:
- 哈尔波段在可视化频率组件中表现出优越性,用于监测内炎治疗.
- 波形分析发现了子ERGa波和b波的特定差异.
- 这种技术可以为管理视网膜疾病提供额外的结果措施.
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