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Updated: May 10, 2026

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
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基于特征混合和多头注意力的自动编码器,用于消除电极运动噪音在心电图应用中

Szu-Ting Wang1, Wen-Yen Hsu2, Shin-Chi Lai3

  • 1Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung City, Wufeng 413310, Taiwan.

Sensors (Basel, Switzerland)
|October 29, 2025
PubMed
概括

电心电图 (ECG) 噪声来自电极运动是一个主要的诊断挑战. 一个新的深度学习模型,FMHA-AE,有效地消除了这种噪音,同时保留了对精确监测至关重要的心脏信号.

关键词:
这是ECG的拒绝.自动编码器自动编码器电极运动文物 电极运动文物多头自我注意的多头自动注意.变压器变压器变压器变压器

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Double resonance techniques in Nuclear Magnetic Resonance (NMR) spectroscopy involve the simultaneous application of two different frequencies or radiofrequency pulses to manipulate and observe two distinct nuclear spins. One important application of double resonance is spin decoupling, which selectively suppresses coupling with one type of nucleus while observing the NMR signal from another nucleus, simplifying the spectrum and enhancing resolution.
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An electrocardiography (ECG) machine is an essential piece of medical equipment used to monitor the electrical activity of the heart. It operates by detecting small electrical changes on the skin that result from the depolarization of the heart muscle during each heartbeat. However, these signals are in the microvolt range and can be easily overwhelmed by noise or interference.
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