A novel method based on shifted rank-1 reconstruction for removing EMG artifacts in ECG signals

模式识别(心理学) 计算机科学 树遍历 人工智能 噪音(视频) 基质(化学分析) 秩(图论) 信号(编程语言) 投影(关系代数) QRS波群 数学 算法 图像(数学) 医学 材料科学 复合材料 心脏病学 程序设计语言 组合数学
作者
Xieqi Chen,Shibao Zheng,Lele Peng,Qianwen Zhong,He Li
出处
期刊:Biomedical Signal Processing and Control [Elsevier]
卷期号:85: 104967-104967
标识
DOI:10.1016/j.bspc.2023.104967
摘要

Electrocardiogram (ECG) signal is an essential feature of human health monitoring and detection. Electromyogram (EMG) artifacts will be involved as the noise distortion and make it difficult for the doctor’s diagnosis. By comparing with the characteristics of these two signals, ECG signals have periodicity while EMG artifacts are random. However, they overlap in the frequency domain. According to the periodicity of ECG signals, several methods of extracting ECG signals from EMG artifacts are proposed. The core of ECG extraction is to form a rank-1 trajectory matrix for reconstruction. However, due to the EMG artifacts, most formed matrices are not strict rank-1 matrices, and the length of traversal segment selected for pure ECG reconstructions is not easily determined. Therefore, a new ECG extraction method based on shifted rank-1 reconstruction is proposed. Given an approximated traversal segment length, the trajectory matrix is constructed. Through the optimization of lambda in the low rank matrix, the constructed approximation matrix is approximated by shift vectors to obtain a strict rank-1 matrix. Pure ECG signals can be reconstructed via the singular values of shifted matrix. The validation of the proposed method is made by applying the algorithm to ECG records from four different databases. The quantitative and qualitative analysis are carried out and compared with other methods. The results indicate that the proposed SR1 method can remove EMG artifacts and does not require any specific traversal segment lengths to extract clean ECG signals. The QRS complexes and ST segments can be retained in reconstructed ECG signals.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
长孙兰溪发布了新的文献求助200
刚刚
2秒前
诚c发布了新的文献求助10
2秒前
xiexiaopa发布了新的文献求助10
3秒前
苗儿发布了新的文献求助10
4秒前
issl完成签到,获得积分10
6秒前
wyl发布了新的文献求助10
7秒前
7秒前
JIaaaa发布了新的文献求助10
8秒前
9秒前
nhb0912发布了新的文献求助10
9秒前
9秒前
完美世界应助韩熙采纳,获得10
9秒前
打打应助zzz采纳,获得10
10秒前
11秒前
Avert.完成签到 ,获得积分10
11秒前
万能图书馆应助xiexiaopa采纳,获得10
12秒前
ynscw应助乐橙采纳,获得20
12秒前
Cary发布了新的文献求助10
12秒前
12秒前
苹果鸽子完成签到,获得积分10
12秒前
12秒前
默默的硬币完成签到,获得积分10
13秒前
无花果应助wilsonht采纳,获得30
13秒前
13秒前
苗儿完成签到,获得积分20
13秒前
着急的寒梅完成签到 ,获得积分10
14秒前
华仔应助ykk采纳,获得10
14秒前
aliupeifang完成签到,获得积分10
14秒前
Gin发布了新的文献求助10
14秒前
啊哦嘿发布了新的文献求助10
15秒前
玩命的大侠完成签到,获得积分10
15秒前
花心的小白菜完成签到,获得积分10
15秒前
畅快寄容完成签到,获得积分20
16秒前
16秒前
aliupeifang发布了新的文献求助10
18秒前
竹筏过海应助研友_LMBa6n采纳,获得30
18秒前
一口饺子发布了新的文献求助10
18秒前
鲜艳的怜烟完成签到,获得积分10
18秒前
高分求助中
The Young builders of New china : the visit of the delegation of the WFDY to the Chinese People's Republic 1000
юрские динозавры восточного забайкалья 800
English Wealden Fossils 700
Chen Hansheng: China’s Last Romantic Revolutionary 500
宽禁带半导体紫外光电探测器 388
COSMETIC DERMATOLOGY & SKINCARE PRACTICE 388
Case Research: The Case Writing Process 300
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3142116
求助须知:如何正确求助?哪些是违规求助? 2793077
关于积分的说明 7805362
捐赠科研通 2449427
什么是DOI,文献DOI怎么找? 1303232
科研通“疑难数据库(出版商)”最低求助积分说明 626807
版权声明 601291