J Shanghai Jiaotong Univ Sci ›› 2025, Vol. 30 ›› Issue (1): 66-80.doi: 10.1007/s12204-023-2591-1
• Medicine-Engineering Interdisciplinary • Previous Articles
BALASUBRAMANIAN S1*, NARUKA Mahaveer Singh2, TEWARI Gaurav3
Accepted:
2022-11-22
Online:
2025-01-28
Published:
2025-01-28
[1] WANG G, YANG L, LIU M, et al. ECG signal denoising based on deep factor analysis [J]. Biomedical Signal Processing and Control, 2020, 57: 101824. [2] LASTRE-DOM′INGUEZ C, SHMALIY Y S, IBARRA-MANZANO O, et al. ECG signal denoising and features extraction using unbiased FIR smoothing [J]. BioMed Research International, 2019, 2019: 2608547. [3] CHIANG H T, HSIEH Y Y, FU S W, et al. Noise reduction in ECG signals using fully convolutional denoising autoencoders [J]. IEEE Access, 2019, 7: 60806-60813. [4] CHATTERJEE S, THAKUR R S, YADAV R N, et al. Review of noise removal techniques in ECG signals [J]. IET Signal Processing, 2020, 14(9): 569-590. [5] BING P P, LIU W, ZHANG Z H. DeepCEDNet: An efficient deep convolutional encoder-decoder networks for ECG signal enhancement [J]. IEEE Access, 2021, 9: 56699-56708. [6] ZHANG D Y, WANG S S, LI F, et al. An efficient ECG denoising method based on empirical mode decomposition, sample entropy, and improved threshold function [J]. Wireless Communications and Mobile Computing, 2020, 2020: 1-11. [7] MUKHERJEE P, BAKSHI A. System for ECG signal denoising [C]//2020 International Conference on Communication and Signal Processing. Chennai: IEEE, 2020: 321-325. [8] SUNDARARAJ V. Optimised denoising scheme via opposition-based self-adaptive learning PSO algorithm for wavelet-based ECG signal noise reduction [J]. International Journal of Biomedical Engineering and Technology, 2019, 31(4): 325. [9] CHANDRA M, GOEL P, ANAND A, et al. Design and analysis of improved high-speed adaptive filter architectures for ECG signal denoising [J]. Biomedical Signal Processing and Control, 2021, 63: 102221. [10] VARGAS R N, VEIGA A C P. Electrocardiogram signal denoising by a new noise variation estimate [J]. Research on Biomedical Engineering, 2020, 36(1): 13-20. [11] HAO H Q, LIU M, XIONG P, et al. Multi-lead modelbased ECG signal denoising by guided filter [J]. Engineering Applications of Artificial Intelligence, 2019, 79: 34-44. [12] BING P P, LIU W, WANG Z, et al. Noise reduction in ECG signal using an effective hybrid scheme [J]. IEEE Access, 2020, 8: 160790-160801. [13] KUMAR A, TOMAR H, MEHLA V K, et al. Stationary wavelet transform based ECG signal denoising method [J]. ISA Transactions, 2021, 114: 251-262. [14] GUPTA V, MITTAL M. Arrhythmia detection in ECG signal using fractional wavelet transform with principal component analysis [J]. Journal of the Institution of Engineers (India): Series B, 2020, 101(5): 451-461. [15] MANJU B R, SNEHA M R. ECG denoising using Wiener filter and Kalman filter [J]. Procedia Computer Science, 2020, 171: 273-281. [16] WASIMUDDIN M, ELLEITHY K, ABUZNEID A S, et al. Stages-based ECG signal analysis from traditional signal processing to machine learning approaches: A survey [J]. IEEE Access, 2020, 8: 177782- 177803. [17] WIDROW B, GLOVER J R, MCCOOL J M, et al. Adaptive noise cancelling: Principles and applications [J]. Proceedings of the IEEE, 1975, 63(12): 1692-1716. [18] SHELTON L Y, CANO G G, COAST D A, et al. Detection of late potentials by adaptive filtering [J]. Journal of Electrocardiology, 1990, 23: 138-143. [19] MIRZA A, KABIR S M, AYUB S, et al. Impulsive Noise Cancellation of ECG signal based on SSRLS [J]. Procedia Computer Science, 2015, 62: 196-202. [20] DONG S P, YUAN M, WANG Q S, et al. A modified empirical wavelet transform for acoustic emission signal decomposition in structural health monitoring [J]. Sensors, 2018, 18(5): 1645. [21] WANG D, ZHAO Y, YI C, et al. Sparsity guided empirical wavelet transform for fault diagnosis of rolling element bearings [J]. Mechanical Systems and Signal Processing, 2018, 101: 292-308. [22] LIU W, CHEN W. Recent advancements in empirical wavelet transform and its applications [J]. IEEE Access, 2019, 7: 103770-103780. [23] FRANCIS A, MURUGANANTHAM C. An adaptive denoising method using empirical wavelet transform [J]. International Journal of Computer Applications, 2015, 117(21): 18-20. [24] DAS M, KUMAR R, SAHANA B. Implementation of effective hybrid window function for E.C.G signal denoising [J]. Traitement Du Signal, 2020, 37(1): 119-128. [25] HASHIM F A, HOUSSEIN E H, HUSSAIN K, et al. Honey Badger Algorithm: New metaheuristic algorithm for solving optimization problems [J]. Mathematics and Computers in Simulation, 2022, 192: 84-110. |
[1] | ZHAO Yanfei1,2,3(赵艳飞), XIAO Peng4 (肖鹏), WANG Jingchuan1,2,3* (王景川), GUO Rui4*(郭锐). Semi-Autonomous Navigation Based on Local Semantic Map for Mobile Robot [J]. J Shanghai Jiaotong Univ Sci, 2025, 30(1): 27-33. |
[2] | FU Hang1 (傅航),XU Jiangchang1 (许江长), LI Yinwei2,4* (李寅炜),ZHOU Huifang2,4 (周慧芳),CHEN Xiaojun1,3* (陈晓军). Augmented Reality Based Navigation System for Endoscopic Transnasal Optic Canal Decompression [J]. J Shanghai Jiaotong Univ Sci, 2025, 30(1): 34-42. |
[3] | DING Lihui1,2(丁黎辉), FU Lijun1,3* (付立军), YANG Guang4(杨光), WAN Lin4,5 (万林), CHANG Zhijun7(常志军). Video-Based Detection of Epileptic Spasms in IESS: Modeling, Detection, and Evaluation [J]. J Shanghai Jiaotong Univ Sci, 2025, 30(1): 1-9. |
[4] | KONG Huiyang1 (孔会扬),WANG Shuyi1* (王殊轶),ZHANG Can2 (张璨),CHEN Zan2,3 (陈赞). Augmented Reality Navigation Using Surgical Guides Versus Conventional Techniques in Pedicle Screw Placement [J]. J Shanghai Jiaotong Univ Sci, 2025, 30(1): 10-17. |
[5] | ZHOU Su (周苏), ZHONG Zebin∗ (钟泽滨). Real-Time Ranging of Vehicles and Pedestrians for Mobile Application on Smartphones [J]. J Shanghai Jiaotong Univ Sci, 2024, 29(6): 1081-1090. |
[6] | ZHOU Cheng (周成), JIANG Zuhua∗ (蒋祖华). Named Entity Recognition of Design Specification Integrated with High-Quality Topic and Attention Mechanism [J]. J Shanghai Jiaotong Univ Sci, 2024, 29(6): 1169-1180. |
[7] | YAN Congqiang1,2 (鄢丛强), GUO Zhengyun3,4 (郭正玉), CAI Yunze1,2∗∗ (蔡云泽). Data Augmentation of Ship Wakes in SAR Images Based on Improved CycleGAN [J]. J Shanghai Jiaotong Univ Sci, 2024, 29(4): 702-711. |
[8] | CHEN Yini(陈旖旎), JIANG Zuhua* (蒋祖华). Multi-AGVs Scheduling with Vehicle Conflict Consideration in Ship Outfitting Items Warehouse [J]. J Shanghai Jiaotong Univ Sci, 2024, 29(3): 492-508. |
[9] | LONARE Savita1,2* , BHRAMARAMBA Ravi2. Federated Approach for Privacy-Preserving Traffic Prediction Using Graph Convolutional Network [J]. J Shanghai Jiaotong Univ Sci, 2024, 29(3): 509-517. |
[10] | LV Feng(吕峰), WANG Xinyan* (王新彦), LI Lei(李磊), JIANG Quan(江泉), YI Zhengyang(易政洋). Tree Detection Algorithm Based on Embedded YOLO Lightweight Network [J]. J Shanghai Jiaotong Univ Sci, 2024, 29(3): 518-527. |
[11] | SONG Liboa (宋立博), FEI Yanqiongb (费燕琼). New Lite YOLOv4-Tiny Algorithm and Application on Crack Intelligent Detection [J]. J Shanghai Jiaotong Univ Sci, 2024, 29(3): 528-536. |
[12] | GU Xinghai顾星海),HUA Bao(花 豹),LIU Yahui(刘亚辉),SUN Xuemin(孙学民),BAO Jinsong∗(鲍劲松). Semantic Entity Recognition and Relation Construction Method for Assembly Process Document [J]. J Shanghai Jiaotong Univ Sci, 2024, 29(3): 537-556. |
[13] | ZHANG Jingke1 (张静克), HE Xinlin2 (何新林), QI Zongfeng1 (戚宗锋), MA Chao2 (马 超), LI Jianxun2 (李建勋). Unbalanced Graph Multi-Scale Fusion Node Classification Method [J]. J Shanghai Jiaotong Univ Sci, 2024, 29(3): 557-565. |
[14] | CHEN Liyue1 (陈利跃), HONG Daojian2 (洪道鉴), HE Xing3* (何星), LU Dongqi2 (卢东祁), ZHANG Qian2 (张乾), XIE Nina2 (谢妮娜), XU Yizhou2 (徐一洲), YING Huanghao2 (应煌浩). Distributed Photovoltaic Real-Time Output Estimation Based on Graph Convolutional Networks [J]. J Shanghai Jiaotong Univ Sci, 2024, 29(2): 290-296. |
[15] | HUANG Rong (黄荣), CHANG Qing∗ (常青), ZHANG Yang (张扬). Unsupervised Oral Endoscope Image Stitching Algorithm [J]. J Shanghai Jiaotong Univ Sci, 2024, 29(1): 81-90. |
Viewed | ||||||||||||||||||||||||||||||||||||||||||||||
Full text 3
|
|
|||||||||||||||||||||||||||||||||||||||||||||
Abstract 245
|
|
|||||||||||||||||||||||||||||||||||||||||||||