解码来自猪的体内神经信号的膀状态.
A Giannotti1, S Lo Vecchio1, S Musco2
1The BioRobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.
APL bioengineering
|October 9, 2023
概括
这项研究引入了一种新的实时膀充满度解码方法,该方法使用尾神经信号来解码. 这推动了适应性神经修饰在治疗下尿路功能障碍方面取得了进展.
科学领域:
- 神经科学是一个神经科学.
- 生物医学工程 生物医学工程
- 泌尿器科 泌尿器科 泌尿器科 泌尿器科
背景情况:
- 目前用于下尿路功能障碍的神经假肢使用开放循环刺激,导致排泄问题.
- 闭环系统提供更好的膀容量和清除功效,但缺乏实时膀状态解码.
- 神经适应持续刺激会导致功能障碍.
研究的目的:
- 开发一个强大的,实时解码策略,用于膀充满状态.
- 为了使神经假体器件的自适应性闭环刺激.
- 为了改善下尿路功能障碍的治疗.
主要方法:
- 在麻醉猪中记录了脑内神经尾神经信号.
- 使用随机森林分类器来解码三个膀填充状态 (空,满,排尿).
- 在多个动物中验证了解码算法的准确性.
主要成果:
- 在解码膀充满状态时,达到平均平衡精度超过86.67%.
- 从神经信号证明了膀状态的成功实时解码.
- 在所有五只猪中证实了算法的有效性.
结论:
- 开发的解码方法是朝着自适应性闭环神经假体迈出的重要一步.
- 这种方法可以实时调节神经,以改善膀控制.
- 铺平了"按需要辅助"神经假体的道路,用于下尿路功能障碍.
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