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https://www.readbyqxmd.com/read/28733932/a-new-algorithm-for-ecg-interference-removal-from-single-channel-emg-recording
#1
Shayan Yazdani, Mahmood Reza Azghani, Mohammad Hossein Sedaaghi
This paper presents a new method to remove electrocardiogram (ECG) interference from electromyogram (EMG). This interference occurs during the EMG acquisition from trunk muscles. The proposed algorithm employs progressive image denoising (PID) algorithm and ensembles empirical mode decomposition (EEMD) to remove this type of interference. PID is a very recent method that is being used for denoising digital images mixed with white Gaussian noise. It detects white Gaussian noise by deterministic annealing. To the best of our knowledge, PID has never been used before, in the case of EMG and ECG separation or in other 1D signal denoising applications...
July 21, 2017: Australasian Physical & Engineering Sciences in Medicine
https://www.readbyqxmd.com/read/28730749/impact-of-the-dynamic-and-static-component-of-the-sport-practiced-for-electrocardiogram-analysis-in-screening-athletes
#2
Nicolas Maillot, Charles Guenancia, Nobila V Yameogo, Aurélie Gudjoncik, Fabien Garnier, Luc Lorgis, Frédéric Chagué, Yves Cottin
BACKGROUND: To interpret the electrocardiogram (ECG) of athletes, the recommendations of the ESC and the Seattle criteria define type-1 peculiarities, those induced by training, and type-2, those not induced by training, to rule out cardiomyopathy. The specificity of the screening was improved by Sheikh who definied "Refined Criteria", which includes a group of intermediate peculiarities. The aim of our study was to investigate the influence of static and dynamic components on the prevalence of different types of abnormalities...
July 21, 2017: Scandinavian Journal of Medicine & Science in Sports
https://www.readbyqxmd.com/read/28719614/beat-id-towards-a-computationally-low-cost-single-heartbeat-biometric-identity-check-system-based-on-electrocardiogram-wave-morphology
#3
Joana S Paiva, Duarte Dias, João P S Cunha
In recent years, safer and more reliable biometric methods have been developed. Apart from the need for enhanced security, the media and entertainment sectors have also been applying biometrics in the emerging market of user-adaptable objects/systems to make these systems more user-friendly. However, the complexity of some state-of-the-art biometric systems (e.g., iris recognition) or their high false rejection rate (e.g., fingerprint recognition) is neither compatible with the simple hardware architecture required by reduced-size devices nor the new trend of implementing smart objects within the dynamic market of the Internet of Things (IoT)...
2017: PloS One
https://www.readbyqxmd.com/read/28708197/risk-stratification-personalised-model-for-prediction-of-life-threatening-ventricular-tachyarrhythmias-in-patients-with-chronic-heart-failure
#4
Alexander Vladimirovich Frolov, Tatjana Gennadjevna Vaikhanskaya, Olga Petrovna Melnikova, Anatoly Pavlovich Vorobiev, Ludmila Michajlovna Guel
BACKGROUND: The development of prognostic factors of life-threatening ventricular tachyarrhythmias (VTA) and sudden cardiac death (SCD) continues to maintain its priority and relevance in cardiology. The development of a method of personalised prognosis based on multifactorial analysis of the risk factors associated with life-threatening heart rhythm disturbances is considered a key research and clinical task. AIM: To design a prognostic and mathematical model to define personalised risk for life-threatening VTA in patients with chronic heart failure (CHF)...
2017: Kardiologia Polska
https://www.readbyqxmd.com/read/28664718/validation-of-automated-detection-of-physical-and-mental-stress-during-work-in-a-h%C3%A3-hnermobil-225
#5
Elisabeth Quendler, Katharina Trieb, Alfred Nimmerichter
<b>Introduction.</b> The effects of the use of mobile henhouses and their equipment on the physical and mental stress of farmers in the organic egg production, and the reliability of the sensor-based detection of these in work processes are insufficiently known. There are neither measurement results nor key figures, according to operation and gender especially, available in the literature. <b>Objective.</b> The aim of this case study is to quantify the physical and mental stress of work processes on the basis of heart rate and the Baevsky Stress Index, as measured by the ECG- and activity sensor Movisens®, which is used mainly in the sports and rehabilitation sectors...
May 11, 2017: Annals of Agricultural and Environmental Medicine: AAEM
https://www.readbyqxmd.com/read/28659139/the-unique-value-of-cardiovascular-magnetic-resonance-in-patients-with-suspected-acute-coronary-syndrome-and-culprit-free-coronary-angiograms
#6
Roman Panovský, Júlia Borová, Martin Pleva, Věra Feitová, Petr Novotný, Vladimír Kincl, Tomáš Holeček, Jaroslav Meluzín, Ondřej Sochor, Radka Štěpánová
BACKGROUND: Patients with chest pain, elevated troponin, and unobstructed coronary disease present a clinical dilemma. The purpose of this study was to investigate the incremental diagnostic value of cardiovascular magnetic resonance (CMR) in a cohort of patients with suspected acute coronary syndrome (ACS) and unobstructed coronary arteries. RESULTS: Data files of patients meeting the inclusion criteria in two cardiology centres were searched and analysed. The inclusion criteria included: 1) thoracic pain suspected with ACS; 2) a significant increase in the high-sensitive Troponin T value; 3) ECG changes; 4) coronary arteries without any significant stenosis; 5) a CMR examination included in the diagnostic process; 6) an uncertain diagnosis before the CMR exam; and 7) the absence of known CMR and contrast media contraindications...
June 28, 2017: BMC Cardiovascular Disorders
https://www.readbyqxmd.com/read/28649031/noise-detection-on-ecg-based-on-agglomerative-clustering-of-morphological-features
#7
João Rodrigues, David Belo, Hugo Gamboa
Biosignals are usually contaminated with artifacts from limb movements, muscular contraction or electrical interference. Many algorithms of the literature, such as threshold methods and adaptive filters, focus on detecting these noisy patterns. This study introduces a novel method for noise and artifact detection in electrocardiogram based on time series clustering. The algorithm starts with the extraction of features that best characterize the shape and behaviour of the signal over time and groups its samples in separated clusters by means of an agglomerative clustering approach...
June 15, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28648124/knowledge-based-iterative-model-reconstruction-in-coronary-computed-tomography-angiography-comparison-with-hybrid-iterative-reconstruction-and-filtered-back-projection
#8
Min Jae Cha, Jae Seung Seo, Dong Soo Yoo, Semin Chong
Background Knowledge-based iterative model reconstruction (IMR) is known to allow radiation dose reduction while preserving image quality. Purpose To investigate the effect of IMR on coronary computed tomography angiography (CCTA) by comparing it with filtered back projection (FBP) and hybrid iterative reconstruction (HIR). Material and Methods Forty-five patients (group A) who underwent CCTA with prospective electrocardiogram (ECG) triggering at 80 kVp were included. All images were reconstructed using three algorithms: FBP, HIR, and IMR...
January 1, 2017: Acta Radiologica
https://www.readbyqxmd.com/read/28646403/routine-ct-angiography-to-detect-severe-coronary-artery-disease-prior-to-transcatheter-aortic-valve-replacement
#9
S Chava, G Gentchos, A Abernethy, B Leavitt, E Terrien, H L Dauerman
Patients undergoing TAVR undergo routine CT angiography (CTA) to assess aorto-iliac pathology and annular dimensions. While coronary CTA may exclude severe CAD in younger patients, its efficacy in defining CAD severity prior to TAVR may be limited. We retrospectively studied 50 consecutive patients undergoing both invasive coronary angiography (ICA) and routine pre-TAVR CTA. Severe CAD was defined as ≥50% stenosis by quantitative coronary angiography and compared to a blinded CTA visual estimation of ≥50% stenosis...
August 2017: Journal of Thrombosis and Thrombolysis
https://www.readbyqxmd.com/read/28644795/a-novel-short-term-event-extraction-algorithm-for-biomedical-signals
#10
Sasan Yazdani, Sibylle Fallet, Jean-Marc Vesin
In this paper we propose a fast novel non-linear filtering method named Relative-Energy (Rel-En), for robust short-term event extraction from biomedical signals. We developed an algorithm that extracts short- and long-term energies in a signal and provides a coefficient vector with which the signal is multiplied, heightening events of interest. This algorithm is thoroughly assessed on benchmark datasets in three different biomedical applications namely, ECG QRS-complex detection, EEG K-complex detection, and imaging photoplethysmography (iPPG) peak detection...
June 21, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28644794/electrocardiogram-signal-quality-assessment-based-on-structural-image-similarity-metric
#11
Yalda Shahriari, Richard Fidler, Michele Pelter, Yong Bai, Andrea Villaroman, Xiao Hu
OBJECTIVE: We developed an image-based electrocardiographic (ECG) quality assessment technique that mimics how clinicians annotate ECG signal quality. METHODS: We adopted the Structural Similarity Measure (SSIM) to compare images of two ECG records that are obtained from displaying ECGs in a standard scale. Then a subset of representative ECG images from the training set was selected as templates through a clustering method. SSIM between each image and all the templates were used as the feature vector for the linear discriminant analysis (LDA) classifier...
June 21, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28635670/single-lead-fetal-ecg-extraction-based-on-a-parallel-marginalized-particle-filter
#12
Zhidong Zhao, Huiling Tong, Yanjun Deng, Wen Xu, Yefei Zhang, Haihui Ye
This paper presents a novel method for extracting the fetal ECG (FECG) from a single-lead abdominal signal. A dynamical model for a modified abdominal signal is proposed, in which both the maternal ECG (MECG) and the FECG are modeled, and then a parallel marginalized particle filter (par-MPF) is used for tracking the abdominal signal. Finally, the FECG and MECG are simultaneously separated. Several experiments are conducted using both simulated and clinical signals. The results indicate that the method proposed in this paper effectively extracts the FECG and outperforms other Bayesian filtering algorithms...
June 21, 2017: Sensors
https://www.readbyqxmd.com/read/28626057/abnormal-p-wave-axis-and-ischemic-stroke-the-aric-study-atherosclerosis-risk-in-communities
#13
Ankit Maheshwari, Faye L Norby, Elsayed Z Soliman, Ryan J Koene, Mary R Rooney, Wesley T O'Neal, Alvaro Alonso, Lin Y Chen
BACKGROUND AND PURPOSE: Abnormal P-wave axis (aPWA) has been linked to incident atrial fibrillation and mortality; however, the relationship between aPWA and stroke has not been reported. We hypothesized that aPWA is associated with ischemic stroke independent of atrial fibrillation and other stroke risk factors and tested our hypothesis in the ARIC study (Atherosclerosis Risk In Communities), a community-based prospective cohort study. METHODS: We included 15 102 participants (aged 54...
June 16, 2017: Stroke; a Journal of Cerebral Circulation
https://www.readbyqxmd.com/read/28624712/classification-of-ecg-heartbeats-using-nonlinear-decomposition-methods-and-support-vector-machine
#14
Kandala N V P S Rajesh, Ravindra Dhuli
Classifying electrocardiogram (ECG) heartbeats for arrhythmic risk prediction is a challenging task due to minute variations in the amplitude, duration and morphology of the ECG signal. In this paper, we propose two feature extraction approaches to classify five types of heartbeats: normal, premature ventricular contraction, atrial premature contraction, left bundle branch block and right bundle branch block. In the first approach, ECG beats are decomposed into intrinsic mode functions (IMFs) using ensemble empirical mode decomposition (EEMD)...
June 15, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28622529/automatic-multimodal-detection-for-long-term-seizure-documentation-in-epilepsy
#15
F Fürbass, S Kampusch, E Kaniusas, J Koren, S Pirker, R Hopfengärtner, H Stefan, T Kluge, C Baumgartner
OBJECTIVE: This study investigated sensitivity and false detection rate of a multimodal automatic seizure detection algorithm and the applicability to reduced electrode montages for long-term seizure documentation in epilepsy patients. METHODS: An automatic seizure detection algorithm based on EEG, EMG, and ECG signals was developed. EEG/ECG recordings of 92 patients from two epilepsy monitoring units including 494 seizures were used to assess detection performance...
May 25, 2017: Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology
https://www.readbyqxmd.com/read/28619766/diagnostic-performance-of-an-automatic-blood-pressure-measurement-device-microlife-watchbp-home-a-for-atrial-fibrillation-screening-in-a-real-world-primary-care-setting
#16
Pak-Hei Chan, Chun-Ka Wong, Louise Pun, Yu-Fai Wong, Michelle Man-Ying Wong, Daniel Wai-Sing Chu, Chung-Wah Siu
OBJECTIVE: To evaluate the diagnostic performance of a UK National Institute for Health and Care Excellence-recommended automatic oscillometric blood pressure (BP) measurement device incorporated with an atrial fibrillation (AF) detection algorithm (Microlife WatchBP Home A) for real-world AF screening in a primary healthcare setting. SETTING: Primary healthcare setting in Hong Kong. INTERVENTIONS: This was a prospective AF screening study carried out between 1 September 2014 and 14 January 2015...
June 15, 2017: BMJ Open
https://www.readbyqxmd.com/read/28604628/privacy-preserving-electrocardiogram-monitoring-for-intelligent-arrhythmia-detection
#17
Junggab Son, Juyoung Park, Heekuck Oh, Md Zakirul Alam Bhuiyan, Junbeom Hur, Kyungtae Kang
Long-term electrocardiogram (ECG) monitoring, as a representative application of cyber-physical systems, facilitates the early detection of arrhythmia. A considerable number of previous studies has explored monitoring techniques and the automated analysis of sensing data. However, ensuring patient privacy or confidentiality has not been a primary concern in ECG monitoring. First, we propose an intelligent heart monitoring system, which involves a patient-worn ECG sensor (e.g., a smartphone) and a remote monitoring station, as well as a decision support server that interconnects these components...
June 12, 2017: Sensors
https://www.readbyqxmd.com/read/28603478/physiological-signal-based-method-for-measurement-of-pain-intensity
#18
Yaqi Chu, Xingang Zhao, Jianda Han, Yang Su
The standard method for prediction of the absence and presence of pain has long been self-report. However, for patients with major cognitive or communicative impairments, it would be better if clinicians could quantify pain without having to rely on the patient's self-description. Here, we present a newly pain intensity measurement method based on multiple physiological signals, including blood volume pulse (BVP), electrocardiogram (ECG), and skin conductance level (SCL), all of which are induced by external electrical stimulation...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28600268/slow-wave-sleep-estimation-for-healthy-subjects-and-osa-patients-using-r-r-intervals
#19
Hee Nam Yoon, Su Hwan Hwang, Jae Won Choi, Yu Jin Lee, Do Un Jeong, Kwang Suk Park
We developed an automatic slow-wave sleep (SWS) detection algorithm that can be applied to groups of healthy subjects and patients with obstructive sleep apnea (OSA). This algorithm detected SWS based on autonomic activations derived from the heart rate variations of a single sensor. An autonomic stability, which is an SWS characteristic, was evaluated and quantified using R-R intervals from an electrocardiogram (ECG). The thresholds and the heuristic rule to determine SWS were designed based on the physiological backgrounds for sleep process and distribution across the night...
June 7, 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28596962/a-novel-ecg-eigenvalue-detection-algorithm-based-on-wavelet-transform
#20
Ziran Peng, Guojun Wang
This study investigated an electrocardiogram (ECG) eigenvalue automatic analysis and detection method; ECG eigenvalues were used to reverse the myocardial action potential in order to achieve automatic detection and diagnosis of heart disease. Firstly, the frequency component of the feature signal was extracted based on the wavelet transform, which could be used to locate the signal feature after the energy integral processing. Secondly, this study established a simultaneous equations model of action potentials of the myocardial membrane, using ECG eigenvalues for regression fitting, in order to accurately obtain the eigenvalue vector of myocardial membrane potential...
2017: BioMed Research International
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