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Updated: Jan 23, 2026

Non-restraining EEG Radiotelemetry: Epidural and Deep Intracerebral Stereotaxic EEG Electrode Placement
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使用元启发和深度学习技术的神经假肢设备的高级EEG信号分类

Thippagudisa Kishore Babu1, Damodar Reddy Edla1, Suresh Dara2

  • 1Department of Computer Science and Engineering, National Institute of Technology, Cuncolim, Goa, India.

Frontiers in digital health
|January 22, 2026
PubMed
概括

本研究引入了一种使用Coati优化算法 (COA) 和卷积神经网络 (CNN) 的新框架,以改进神经假体的电脑学 (EEG) 信号分类. COA+CNN模型的准确率达到96.8%,大大提高了脑电脑界面的性能.

关键词:
电脑电图信号分类 电脑电图信号分类科蒂的优化算法 (COA)深度学习是一种深度学习.功能选择 功能选择运动图像图像学神经假肢设备的神经假肢设备

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