专注调节镜头的实时控制,用于使用肌肉生物潜力和人工神经网络纠正近视
Bishesh Sigdel1, Sven Schumayer1,2, Sebastian Kaltenstadler3
1Institute for Ophthalmic Research, University of Tuebingen, 72076 Tuebingen, Germany.
Bioengineering (Basel, Switzerland)
|November 27, 2025
概括
这项研究引入了一种使用肌信号和人工智能的新系统,以恢复长视 (与年龄相关的远视) 中的近视. 它可以实现动态聚焦,改善与年龄相关的视力丧失患者的视力敏度.
科学领域:
- 眼科医生 眼科 眼科
- 生物医学工程 生物医学工程
- 人工智能的人工智能
背景情况:
- 老龄化导致长视,即近视的逐渐丧失,显著影响生活质量.
- 目前对长视障碍的纠正方法提供有限的补偿,无法恢复动态视觉聚焦.
- 恢复动态适应对于解决长视障碍的功能限制至关重要.
研究的目的:
- 开发和评估一个闭环的校正系统,对长视.
- 利用来自肌和人工神经网络的生物潜能信号进行实时适应性状态预测.
- 为了使长视眼的眼睛能够具有动态聚焦能力.
主要方法:
- 使用非侵入性隐形眼镜电极收集状肌肉生物潜能数据.
- 一个多层感知器人工神经网络分类了预处理的生物潜能信号.
- 一个控制系统根据分类器的输出调整了一个外部可调节焦点的镜头.
主要成果:
- 该系统实现了0.79的预测准确度,用于眼睛的适应性状态.
- 记录了F1得分为0.78的住宿和0.77的失住预测.
- 长视患者近视敏度显著改善,而远视敏度保持稳定.
结论:
- 这项研究表明,使用神经肌肉信号和自适应性透镜控制,可以恢复近视近视的近自然适应.
- 开发的系统有望改善与年龄相关的视力丧失患者的视觉功能.
- 未来的工作将集中在系统验证,数据集扩展和植入式设备的临床前测试上.
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