在心电图中消除随机混合噪声,使用卷积断层自动编码器与变压器编码器
IEEE journal of biomedical and health informatics
|January 19, 2024
概括
这项研究引入了基于变压器的卷积异位自编码器 (TCDAE),有效地从心电图 (ECG) 信号中去除随机混合噪声 (RMN),提高诊断准确度.
科学领域:
- 生物医学信号处理
- 医疗保健中的人工智能
- 心脏病学 心脏病学
背景情况:
- 电心电图 (ECG) 信号容易受到各种类型的噪音的影响,包括基线流浪 (BW),电极运动 (EM) 工件和肌肉工件 (MA).
- 结合的噪音往往导致心脏病学家的误解,阻碍了准确的诊断.
- 现有的无声化方法可能会引入扭曲或无法有效处理复杂的混合噪声.
研究的目的:
- 开发一种新的深度学习模型,以抑制随机混合噪声 (RMN) 在ECG信号中,以最小的扭曲.
- 为了提高在噪音的情况下ECG解释的准确性和可靠性.
- 为了提高 R 峰值检测在无效的 ECG 信号中的性能.
主要方法:
- 提出了一种基于变压器的卷积退化自动编码器 (TCDAE) 模型,该模型具有堆叠的封闭卷积层和具有多头自我注意力的变压器编码器.
- 在培训期间引入了一个频率加权的休伯损失函数,以尽量减少时间和频率领域的扭曲.
- 在QT数据库 (QTDB) 和MIT-BIH噪声应力测试数据库 (NSTDB) 上训练和验证了TCDAE模型,在Icentia11k数据库上进行了概括测试.
主要成果:
- 与QTDB和NSTDB的基线方法相比,TCDAE模型在消除RMN和个别噪声类型方面表现强.
- 在Icentia11k数据库中,TCDAE取得了最先进的结果,在R峰值检测中减少了55%的虚假阳性.
- 该模型有效地捕捉了短期和长期的ECG信号特征,在严重的噪音条件下保持稳定性.
结论:
- 拟议的TCDAE模型提供了一个非常有效的解决方案,用于消除随机混合噪声损坏的ECG信号.
- 与现有方法相比,TCDAE表现出优越的性能和概括能力,显著提高了R峰检测精度.
- 该模型的计算效率使其适合临床应用,在现实场景中有望提高诊断可靠性.
更多相关视频
10:23Equipment Setup and Artifact Removal for Simultaneous Electroencephalogram and Functional Magnetic Resonance Imaging for Clinical Review in Epilepsy
Published on: June 23, 2023
2.0K
08:22Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
Published on: April 26, 2024
1.8K
相关概念视频
Energy Losses in Transformers
876
In an ideal transformer, it is assumed that there are no energy losses, and, hence, all the power at the primary winding is transferred to the secondary winding. However, in reality, the transformers always have some energy losses, and, hence, the output power obtained at the secondary winding is less than the input power at the primary winding due to energy losses.
There are four main reasons for energy losses in transformers.
The first cause can be the high resistance of the...
There are four main reasons for energy losses in transformers.
The first cause can be the high resistance of the...
876
Instrumentation Amplifier
521
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.
To overcome this challenge, an ECG machine utilizes an instrumentation amplifier. This specialized amplifier is...
To overcome this challenge, an ECG machine utilizes an instrumentation amplifier. This specialized amplifier is...
521
Types Of Transformers
977
Transformers can provide desired voltages to a circuit by modifying the number of turns in the secondary windings.
If the ratio of the number of turns in the secondary winding to that of the primary winding is greater than one, then the transformer is said to be a step-up transformer. In a step-up transformer, the voltage at the secondary winding is greater than the voltage applied at the primary winding.
However, if this ratio is less than one, the transformer is said to be a step-down...
If the ratio of the number of turns in the secondary winding to that of the primary winding is greater than one, then the transformer is said to be a step-up transformer. In a step-up transformer, the voltage at the secondary winding is greater than the voltage applied at the primary winding.
However, if this ratio is less than one, the transformer is said to be a step-down...
977
Downsampling
158
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
158
Sampling Continuous Time Signal
251
In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
In the...
251
Deconvolution
160
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
160
