Intelligent Analysis of Premature Ventricular Contraction Based on Features and Random Forest

被引：12

作者：

Xie, Tiantian ^{[1
,2
]}

Li, Runchuan ^{[1
,2
]}

Shen, Shengya ^{[3
]}

Zhang, Xingjin ^{[1
,2
,4
]}

Zhou, Bing ^{[1
,2
]}

Wang, Zongmin ^{[1
,2
]}

机构：

[1] Zhengzhou Univ, Sch Informat Engn, Zhengzhou 450000, Henan, Peoples R China

[2] Zhengzhou Univ, Cooperat Innovat Ctr Internet Healthcare, Zhengzhou 450000, Henan, Peoples R China

[3] Zhongyuan Univ Technol, Coll Informat & Business, Zhengzhou 450000, Henan, Peoples R China

[4] State Key Lab Math Engn & Adv Comp, Zhengzhou 450000, Henan, Peoples R China

来源：

JOURNAL OF HEALTHCARE ENGINEERING | 2019年 / 2019卷

基金：

中国国家自然科学基金;

关键词：

FUZZY NEURAL-NETWORK; WAVELET TRANSFORM; CLASSIFICATION; SELECTION;

D O I：

10.1155/2019/5787582

中图分类号：

R19 [保健组织与事业（卫生事业管理）];

学科分类号：

摘要：

Premature ventricular contraction (PVC) is one of the most common arrhythmias in the clinic. Due to its variability and susceptibility, patients may be at risk at any time. The rapid and accurate classification of PVC is of great significance for the treatment of diseases. Aiming at this problem, this paper proposes a method based on the combination of features and random forest to identify PVC. The RR intervals (pre_RR and post_RR), R amplitude, and QRS area are chosen as the features because they are able to identify PVC better. The experiment was validated on the MIT-BIH arrhythmia database and achieved good results. Compared with other methods, the accuracy of this method has been significantly improved.

引用

页数：10

共 50 条

[31] Effortless detection of premature ventricular contraction using computerized analysis of photoplethysmography signal
Dhar, Sandipan
Chakraborty, Abhishek
Sadhukhan, Deboleena
Pal, Saurabh
Mitra, Madhuchhanda
SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES, 2022, 47 (01):
[32] Effortless detection of premature ventricular contraction using computerized analysis of photoplethysmography signal
Sandipan Dhar
Abhishek Chakraborty
Deboleena Sadhukhan
Saurabh Pal
Madhuchhanda Mitra
Sādhanā, 2022, 47
[33] A Novel Method for Diagnosing Premature Ventricular Contraction Beat Based on Chaos Theory
Du, Haiman
Bai, Yang
Zhou, Suiping
Wang, Hongrui
Liu, Xiuling
2014 11TH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (FSKD), 2014, : 497 - 501
[34] Similarity based on the importance of common features in random forest
Chen X.
Han L.
Leng M.
Pan X.
International Journal of Performability Engineering, 2019, 15 (04) : 1171 - 1180
[35] VENTRICULAR FILLING IS INCREASED INDEPENDENT OF RELAXATION FOLLOWING PREMATURE VENTRICULAR CONTRACTION
COURTOIS, M
FISCHER, AE
BARZILAI, B
LUDBROOK, PA
CLINICAL RESEARCH, 1990, 38 (02): : A333 - A333
[36] Association between ventricular premature contraction burden and ventricular repolarization duration
Soylemez, Nihat
Yaman, Belma
REVISTA DA ASSOCIACAO MEDICA BRASILEIRA, 2022, 68 (11): : 1571 - 1575
[37] Premature ventricular contraction increases the risk of heart failure and ventricular tachyarrhythmia
Kim, Yun Gi
Choi, Yun Young
Han, Kyung-Do
Min, Kyoung Jin
Choi, Ha Young
Shim, Jaemin
Choi, Jong-Il
Kim, Young-Hoon
SCIENTIFIC REPORTS, 2021, 11 (01)
[38] Cardiac characteristics in the premature ventricular contraction patients with or without ventricular tachycardia
Su, Yafen
Xia, Meng
Cao, Junxian
Gao, Qianping
INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL MEDICINE, 2018, 11 (06): : 6106 - 6112
[39] Premature ventricular contraction increases the risk of heart failure and ventricular tachyarrhythmia
Yun Gi Kim
Yun Young Choi
Kyung-Do Han
Kyoung Jin Min
Ha Young Choi
Jaemin Shim
Jong-Il Choi
Young-Hoon Kim
Scientific Reports, 11
[40] INCREASED LEFT VENTRICULAR STIFFNESS IN PATIENTS WITH SYMPTOMATIC PREMATURE VENTRICULAR CONTRACTION
Fukuhara, Eiji
Mine, Takanao
Kishima, Hideyuki
Ishihara, Masaharu
JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, 2020, 75 (11) : 339 - 339

← 1 2 3 4 5 →