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11 results for “Electrocardiogram Signal”
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Research ArticleOpen accessPhrase in the titleAn Efficient Method for Fetal Electrocardiogram Extraction from the Abdominal Electrocardiogram SignalMuhammad Asraful Hasan, Muhammad Ibn Ibrahimy, Mamun Bin Ibn ReazProblem statement: FECG (Fetal Electrocardiogram) signal contains potentially precise information that could assist clinicians in making more appropriate and timely decisions during pregnancy and labor. Approach: Conventional techniques were often unable to achieve the extraction of FECG from the Abdominal ECG (AECG) in satisfactorily level. A new methodology by combining the Artificial Neural Network (ANN) and Correlation (ANNC) approach had … …Journal of Computer Science, Vol. 5, Issue 9 · 30 Sep 2009 · 7,353 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA LIGHT-WEIGHT CRYPTOGRAPHY ANALYSIS FOR WIRELESS BASED HEALTHCARE APPLICATIONSS. Sangari, Martin Leo ManickamPatient health monitoring devices are flexible. Powerful ECG acquisition system is used at anytime and anywhere in the patient monitoring system. The increasing feasibility and convenience of mobile healthcare has already introduced several significant challenges in hospitals, healthcare providers, policy makers and patients. This study provides adaptive humming bird algorithm of light weight cryptography. This method has higher level of … …Journal of Computer Science, Vol. 10, Issue 10 · 28 Jun 2014 · 6,893 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFetal Electrocardiogram Extraction Using Let TechniquesS. Hemajothi, K. Helen PrabhaFetal Electrocardiogram Extraction (FECG) identifies the congenital heart problems at the earlier stage. The major problem in the non invasive procedure is the extraction of FECG from Maternal ECG (MECG) and many interferences. The proposed methods (i) Combination of Adaptive Neuro Fuzzy Inference (ANFIS) and Fractional spline wavelet (ii) Combination of Fractional spline wavelet and ANFIS (iii) Combination of ANFIS … …Journal of Computer Science, Vol. 8, Issue 9 · 16 Aug 2012 · 7,311 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Novel Technique for Extraction Foetal Electrocardiogram using Adaptive Filtering and Simple Genetic AlgorithmMahmoud Ahmed Suliman Ali, XiaoPing ZengProblem statement: Foetal electrocardiogram (FECG) was the best method used to diagnose Foetal heart problem. Knowledge of the foetal heart signal prevents Foetal problems in the earlier stage. Recently, there has been a growing interest in noninvasive method rather than the old invasive method which was more risky for the mother's health. The most significant problem in noninvasive method is … …Current Research in Biostatistics, Vol. 1, Issue 2 · 31 Dec 2010 · 10,407 accessesView PDFCite
Research ArticleOpen accessIn the keywordsElectrophysiology and Biopotential Issues on Human Electrocardiogram: A ReviewMahmoud Ahmed Suliman Ali, Xiao Ping Zeng, Guo Jun LiProblem statement: The heart is the first organ and most importantly to form in the body, where is found the most powerful generator of electromagnetic energy in the human body. Electrophysiology was the best method used to diagnose human heart problem. Knowledge of the electrical potentials in human heart was a quantum leap in the science of the human heart. … …American Journal of Engineering and Applied Sciences, Vol. 4, Issue 3 · 18 Aug 2011 · 7,868 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid BiGRU-BiLSTM Model for Real-Time ECG Arrhythmia Detection Using Wearable SensorsPrem Narayan Singh, Rajendra Prasad MahapatraAccurate and real-time detection of cardiac arrhythmias is essential for timely medical intervention. Advances in wearable devices and deep learning have made it feasible to continuously monitor electrocardiogram (ECG) signals, facilitating early identification of abnormal heart rhythms. For arrhythmia detection, this study presents a hybrid deep learning architecture combining Bidirectional Gated Recurrent Units (Bi-GRU) and Bidirectional Long Short-Term Memory (Bi-LSTM). … …Journal of Computer Science, Vol. 22, Issue 5 · 5 Jun 2026 · 1,331 accessesView PDFCite
Research ArticleOpen accessIn the abstractCardiovascular Diseases Identification Using Wavelet Optimization and Modify Cuckoo Search AlgorithmBanit Negi, Abhilekh Bartwal, Agya Ram Verma et al.The problem the author aims to solve is the extraction of discriminatory features in ECG (Electrocardiogram) signals for classification purposes. The scope of the work is to propose a new method for building wavelets that best reflect the discriminatory capacity of ECG signals. The approach involves optimizing the wavelets specifically for the classification function under consideration. To address the problem, … …Journal of Computer Science, Vol. 19, Issue 8 · 3 Aug 2023 · 5,403 accessesView PDFCite
Research ArticleOpen accessIn the abstractECG Energy Change Study Based on Variational Mode DecompositionKai Dong, Lin Sun, Hongjun Xiong, Wenbo WangVariational Mode Decomposition (VMD) decomposes the signal into a series of Intrinsic Mode Type Functions (IMTFs) according with variational model and fluctuating characteristics of the signal itself, thus very suitable for the analysis of nonlinear and non-stationary Electrocardiogram (ECG) signal. Energy of ECG signal has certain distribution rules, but which could be affected by diseases; therefore, the study of ECG … …American Journal of Biochemistry and Biotechnology, Vol. 16, Issue 1 · 12 Mar 2020 · 7,397 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Evaluation of Adaptive Filter and Neuro-Fuzzy Filter in Artifacts Removal From Electroencephalogram SignalPaulchamy Balaiah, IlavennilaProblem statement: This study presents an effective method for removing mixed artifacts (EOG-Electro-ocular gram, ECG-Electrocardiogram, EMG-Electromyogram) from the EEG-Electroencephalogram records. The noise sources increases the difficulty in analyzing the EEG and obtaining clinical information. EEG signals are multidimensional, non-stationary (i.e., statistical properties are not invariant in time), time domain biological signals, which are not reproducible. It is supposed to contain … …American Journal of Applied Sciences, Vol. 9, Issue 10 · 15 Aug 2012 · 7,087 accessesView PDFCite
Research ArticleOpen accessIn the abstractQuality Evaluation of Reconstructed Biological SignalsMikhled Alfaouri, Khaled Daqrouq, Ibrahim N. Abu-Isbeih et al.This research presents the use of wavelet transforms for reconstructed signal evaluation for biological signals. The method adapted on this research, is a new modeling technique and based on calculating the reconstruction error of the wavelet transform sub-signals that have different frequency bands and different deformation degree. The paper processes a special set of application in biomedical field, called Electrocardiogram … …American Journal of Applied Sciences, Vol. 6, Issue 1 · 31 Jan 2009 · 9,107 accessesView PDFCite