keyword
https://read.qxmd.com/read/38436059/activation-of-cardiac-parasympathetic-and-sympathetic-activity-occur-at-different-skin-temperatures-during-face-cooling
#21
JOURNAL ARTICLE
Felipe Gorini Pereira, Muhamed McBryde, Morgan Reynolds, James R Sackett, Christopher L Chapman, Elizabeth A Gideon, Zachary J Schlader, Blair D Johnson
Sufficiently cold-water temperatures (<7o C) are needed to elicit the sympathetic response to the cold pressor test using the hand. However, it is not known if stimulating the trigeminal nerve via face cooling, which increases both sympathetic and cardiac parasympathetic activity, also has a threshold temperature. We tested the hypothesis that peak autonomic activation during a progressive face cooling challenge would be achieved when the stimulus temperature is £ 7o C. Twelve healthy participants (age: 25 ± 3 years, 4 women) completed our study...
March 4, 2024: American Journal of Physiology. Regulatory, Integrative and Comparative Physiology
https://read.qxmd.com/read/38435599/arrhythmia-classification-for-non-experts-using-infinite-impulse-response-iir-filter-based-machine-learning-and-deep-learning-models-of-the-electrocardiogram
#22
JOURNAL ARTICLE
Mallikarjunamallu K, Khasim Syed
Arrhythmias are a leading cause of cardiovascular morbidity and mortality. Portable electrocardiogram (ECG) monitors have been used for decades to monitor patients with arrhythmias. These monitors provide real-time data on cardiac activity to identify irregular heartbeats. However, rhythm monitoring and wave detection, especially in the 12-lead ECG, make it difficult to interpret the ECG analysis by correlating it with the condition of the patient. Moreover, even experienced practitioners find ECG analysis challenging...
2024: PeerJ. Computer Science
https://read.qxmd.com/read/38430664/epm-algorithm-a-stepwise-approach-to-accessory-pathway-localization-in-ventricular-pre-excitation
#23
JOURNAL ARTICLE
José Nunes de Alencar Neto, Marcel Henrique Sakai, Rogério Gomes de Almeida Neto, Matheus Kiszka Scheffer, Gabriel Pinheiro Soares Alencar E Silva, Claudio Cirenza, Angelo Amato Vincenzo de Paola
BACKGROUND: Accurate estimation of accessory pathway (AP) localization in patients with ventricular pre-excitation or Wolff-Parkinson-White (WPW) syndrome remains a diagnostic challenge. Existing algorithms have contributed significantly to this area, but alternative algorithms can offer additional perspectives and approaches to AP localization. OBJECTIVE: This study introduces and evaluates the diagnostic accuracy of the EPM algorithm in AP localization, comparing it with established algorithms Arruda and EASY...
February 28, 2024: Journal of Electrocardiology
https://read.qxmd.com/read/38425642/the-value-of-electrocardiography-in-predicting-inpatient-mortality-in-patients-with-acute-pulmonary-embolism-a-cross-sectional-analysis
#24
JOURNAL ARTICLE
Nishen Raghubeer, Sa'ad Lahri, Clint Hendrikse
INTRODUCTION: Pulmonary embolism (PE) is a significant global cause of mortality, ranking third after myocardial infarction and stroke. ECG findings may play a valuable role in the prognostication of patients with PE, with various ECG abnormalities proving to be reasonable predictors of haemodynamic decompensation, cardiogenic shock, and even mortality. This study aims to assess the value of electrocardiography in predicting inpatient mortality in patients with acute pulmonary embolism, as diagnosed with computed tomography pulmonary angiogram...
June 2024: African Journal of Emergency Medicine Revue
https://read.qxmd.com/read/38424391/12-lead-ecg-reconstruction-based-on-data-from-the-first-limb-lead
#25
JOURNAL ARTICLE
Alexey Savostin, Kayrat Koshekov, Yekaterina Ritter, Galina Savostina, Dmitriy Ritter
PURPOSE: Electrocardiogram (ECG) data obtained from 12 leads are the most common and informative source for analyzing the cardiovascular system's (CVS) condition in medical practice. However, the large number of electrodes, specific placements on the body, and the need for specialized equipment make the ECG acquisition procedure complex and cumbersome. This raises the challenge of reducing the number of ECG leads by reconstructing missing leads based on available data. METHODS: Most existing methods for reconstructing missing ECG leads rely on utilizing signals simultaneously from multiple known leads...
February 29, 2024: Cardiovascular Engineering and Technology
https://read.qxmd.com/read/38422574/diagnostic-value-of-electrocardiographic-indices-in-discriminating-the-culprit-vessel-based-on-the-coronary-dominancy-in-inferior-acute-myocardial-infarction
#26
JOURNAL ARTICLE
Reza Rahmani, Zahra Gholami, Kimia Ghanavati, Aryan Ayati, Akbar Shafiee
BACKGROUND: Identifying the culprit during inferior myocardial infarction (MI) is still challenging. We determined the diagnostic effect of electrocardiographic (ECG) indices in identifying the culprit vessel of acute MI and the impact of coronary artery dominance on it. METHODS: This cross-sectional study included patients with acute inferior MI who presented to Imam Khomeini Hospital and Tehran Heart Center and underwent primary PCI within 12 h of the onset of symptoms...
February 23, 2024: Journal of Electrocardiology
https://read.qxmd.com/read/38421078/polymeric-conductive-adhesive-based-ultrathin-epidermal-electrodes-for-long-term-monitoring-of-electrophysiological-signals
#27
JOURNAL ARTICLE
Joo Hwan Shin, Ji Yeong Choi, Keonuk June, Hyesu Choi, Tae-Il Kim
Electrophysiology, exploring vital electrical phenomena in living organisms, anticipates broader integration into daily life through wearable devices. However, addressing the challenges of electrode durability and motion artifacts is essential to enable continuous and long-term biopotential signal monitoring, presenting a hurdle for its seamless implementation in daily life. To address these challenges, we present an ultrathin poly(3,4- ethylenedioxythiophene): poly(styrenesulfonate)/polyvinyl alcohol/d-sorbitol (PPd) electrode with enhanced adhesion, stretchability, and skin conformability...
February 29, 2024: Advanced Materials
https://read.qxmd.com/read/38420510/very-early-detection-of-atrial-fibrillation-after-ablation-evaluated-by-a-wearable-ecg-patch-predicts-late-blanking-period-recurrence-preliminary-data-from-a-prospective-registry
#28
JOURNAL ARTICLE
Miguel Marques Antunes, Pedro Silva Cunha, Bárbara Lacerda Teixeira, Guilherme Portugal, Bruno Valente, Ana Lousinha, Ana Sofia Delgado, Sandra Alves, Cátia Guerra, Rui Cruz Ferreira, Mário Martins Oliveira
INTRODUCTION: Atrial fibrillation (AF) ablation represents a safe and effective procedure to restore sinus rhythm. The idea that post-procedural AF episodes - during the blanking period - are not considered treatment failure has been increasingly challenged. The E-Patch, a single-use adhesive electrode, facilitates extended continuous ECG monitoring for 120 h. This pilot study aims to assess the effectiveness of this ambulatory monitoring device and investigate whether very-early AF recurrence correlates with delayed blanking period ablation outcomes...
April 2024: IJC Heart & Vasculature
https://read.qxmd.com/read/38418628/cardiologist-level-interpretable-knowledge-fused-deep-neural-network-for-automatic-arrhythmia-diagnosis
#29
JOURNAL ARTICLE
Yanrui Jin, Zhiyuan Li, Mengxiao Wang, Jinlei Liu, Yuanyuan Tian, Yunqing Liu, Xiaoyang Wei, Liqun Zhao, Chengliang Liu
BACKGROUND: Long-term monitoring of Electrocardiogram (ECG) recordings is crucial to diagnose arrhythmias. Clinicians can find it challenging to diagnose arrhythmias, and this is a particular issue in more remote and underdeveloped areas. The development of digital ECG and AI methods could assist clinicians who need to diagnose arrhythmias outside of the hospital setting. METHODS: We constructed a large-scale Chinese ECG benchmark dataset using data from 272,753 patients collected from January 2017 to December 2021...
February 28, 2024: Commun Med (Lond)
https://read.qxmd.com/read/38407726/the-danish-nationwide-electrocardiogram-ecg-cohort
#30
JOURNAL ARTICLE
Christoffer Polcwiartek, Mikkel Porsborg Andersen, Helle Collatz Christensen, Christian Torp-Pedersen, Kathrine Kold Sørensen, Kristian Kragholm, Claus Graff
The electrocardiogram (ECG) is a non-invasive diagnostic tool holding significant clinical importance in the diagnosis and risk stratification of cardiac disease. However, access to large-scale, population-based digital ECG data for research purposes remains limited and challenging. Consequently, we established the Danish Nationwide ECG Cohort to provide data from standard 12-lead digital ECGs in both pre- and in-hospital settings, which can be linked to comprehensive Danish nationwide administrative registers on health and social data with long-term follow-up...
February 26, 2024: European Journal of Epidemiology
https://read.qxmd.com/read/38405776/automated-diagnostic-reports-from-images-of-electrocardiograms-at-the-point-of-care
#31
Akshay Khunte, Veer Sangha, Evangelos K Oikonomou, Lovedeep Singh Dhingra, Arya Aminorroaya, Andreas Coppi, Sumukh Vasisht Shankar, Bobak J Mortazavi, Deepak L Bhatt, Harlan M Krumholz, Girish Nadkarni, Akhil Vaid, Rohan Khera
Timely and accurate assessment of electrocardiograms (ECGs) is crucial for diagnosing, triaging, and clinically managing patients. Current workflows rely on a computerized ECG interpretation using rule-based tools built into the ECG signal acquisition systems with limited accuracy and flexibility. In low-resource settings, specialists must review every single ECG for such decisions, as these computerized interpretations are not available. Additionally, high-quality interpretations are even more essential in such low-resource settings as there is a higher burden of accuracy for automated reads when access to experts is limited...
February 18, 2024: medRxiv
https://read.qxmd.com/read/38403620/-developments-of-ex-vivo-cardiac-electrical-mapping-and-intelligent-labeling-of-atrial-fibrillation-substrates
#32
JOURNAL ARTICLE
Yi Chang, Ming Dong, Bin Wang, Lihong Fan
Cardiac three-dimensional electrophysiological labeling technology is the prerequisite and foundation of atrial fibrillation (AF) ablation surgery, and invasive labeling is the current clinical method, but there are many shortcomings such as large trauma, long procedure duration, and low success rate. In recent years, because of its non-invasive and convenient characteristics, ex vivo labeling has become a new direction for the development of electrophysiological labeling technology. With the rapid development of computer hardware and software as well as the accumulation of clinical database, the application of deep learning technology in electrocardiogram (ECG) data is becoming more extensive and has made great progress, which provides new ideas for the research of ex vivo cardiac mapping and intelligent labeling of AF substrates...
February 25, 2024: Sheng Wu Yi Xue Gong Cheng Xue za Zhi, Journal of Biomedical Engineering, Shengwu Yixue Gongchengxue Zazhi
https://read.qxmd.com/read/38401509/intelligent-assessment-of-atrial-fibrillation-gradation-based-on-sinus-rhythm-electrocardiogram-and-baseline-information
#33
JOURNAL ARTICLE
Biqi Tang, Sen Liu, Xujian Feng, Chunpu Li, Hongye Huo, Aiguo Wang, Xintao Deng, Cuiwei Yang
BACKGROUND: Atrial fibrillation (AF) is a progressive arrhythmia that significantly affects a patient's quality of life. The 4S-AF scheme is clinically recommended for AF management; however, the evaluation process is complex and time-consuming. This renders its promotion in primary medical institutions challenging. This retrospective study aimed to simplify the evaluation process and present an objective assessment model for AF gradation. METHODS: In total, 189 12-lead electrocardiogram (ECG) recordings from 64 patients were included in this study...
February 18, 2024: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/38400474/wearable-technology-for-monitoring-electrocardiograms-ecgs-in-adults-a-scoping-review
#34
REVIEW
Ekta Singh Dahiya, Anubha Manju Kalra, Andrew Lowe, Gautam Anand
In the rapidly evolving landscape of continuous electrocardiogram (ECG) monitoring systems, there is a heightened demand for non-invasive sensors capable of measuring ECGs and detecting heart rate variability (HRV) in diverse populations, ranging from cardiovascular patients to sports enthusiasts. Challenges like device accuracy, patient privacy, signal noise, and long-term safety impede the use of wearable devices in clinical practice. This scoping review aims to assess the performance and safety of novel multi-channel, sensor-based biopotential wearable devices in adults...
February 18, 2024: Sensors
https://read.qxmd.com/read/38400317/multi-feature-automatic-extraction-for-detecting-obstructive-sleep-apnea-based-on-single-lead-electrocardiography-signals
#35
JOURNAL ARTICLE
Yu Zhou, Kyungtae Kang
Obstructive sleep apnea (OSA), a prevalent sleep disorder, is intimately associated with various other diseases, particularly cardiovascular conditions. The conventional diagnostic method, nocturnal polysomnography (PSG), despite its widespread use, faces challenges due to its high cost and prolonged duration. Recent developments in electrocardiogram-based diagnostic techniques have opened new avenues for addressing these challenges, although they often require a deep understanding of feature engineering. In this study, we introduce an innovative method for OSA classification that combines a composite deep convolutional neural network model with a multimodal strategy for automatic feature extraction...
February 9, 2024: Sensors
https://read.qxmd.com/read/38400282/ventricular-arrhythmias-in-left-ventricular-assist-device-patients-current-diagnostic-and-therapeutic-considerations
#36
REVIEW
Laura Załucka, Ewa Świerżyńska, Michał Orczykowski, Krzysztof Dutkowski, Jarosław Szymański, Jarosław Kuriata, Rafał Dąbrowski, Piotr Kołsut, Łukasz Szumowski, Maciej Sterliński
Left ventricular assist devices (LVAD) are used in the treatment of advanced left ventricular heart failure. LVAD can serve as a bridge to orthotopic heart transplantation or as a destination therapy in cases where orthotopic heart transplantation is contraindicated. Ventricular arrhythmias are frequently observed in patients with LVAD. This problem is further compounded as a result of diagnostic difficulties arising from presently available electrocardiographic methods. Due to artifacts from LVAD-generated electromagnetic fields, it can be challenging to assess the origin of arrhythmias in standard ECG tracings...
February 8, 2024: Sensors
https://read.qxmd.com/read/38399629/harmony-in-chaos-deciphering-the-influence-of-ischemic-cardiomyopathy-and-non-cardiac-comorbidities-on-holter-ecg-parameters-in-chronic-heart-failure-patients-a-pilot-study
#37
JOURNAL ARTICLE
Ștefania-Teodora Duca, Minerva Codruta Badescu, Alexandru-Dan Costache, Adriana Chetran, Radu Ștefan Miftode, Ionuț Tudorancea, Ovidiu Mitu, Irina Afrăsânie, Radu-George Ciorap, Ionela-Lăcrămioara Șerban, D Robert Pavăl, Bianca Dmour, Maria-Ruxandra Cepoi, Irina-Iuliana Costache-Enache
Background and Objective : In the landscape of heart failure, non-cardiac comorbidities represent a formidable challenge, imparting adverse prognostic implications. Holter ECG monitoring assumes a supplementary role in delineating myocardial susceptibility and autonomic nervous system dynamics. This study aims to explore the potential correlation between Holter ECG parameters and comorbidities in individuals with ischemic cardiomyopathy experiencing heart failure (HF), with a particular focus on the primary utility of these parameters as prognostic indicators...
February 19, 2024: Medicina
https://read.qxmd.com/read/38398346/an-artificial-intelligence-analysis-of-electrocardiograms-for-the-clinical-diagnosis-of-cardiovascular-diseases-a-narrative-review
#38
REVIEW
Assunta Di Costanzo, Carmen Anna Maria Spaccarotella, Giovanni Esposito, Ciro Indolfi
Artificial intelligence (AI) applied to cardiovascular disease (CVD) is enjoying great success in the field of scientific research. Electrocardiograms (ECGs) are the cornerstone form of examination in cardiology and are the most widely used diagnostic tool because they are widely available, inexpensive, and fast. Applications of AI to ECGs, especially deep learning (DL) methods using convolutional neural networks (CNNs), have been developed in many fields of cardiology in recent years. Deep learning methods provide valuable support for rapid ECG interpretation, demonstrating a diagnostic capability overlapping with specialists in the diagnosis of CVD by a classical analysis of macroscopic changes in the ECG trace...
February 11, 2024: Journal of Clinical Medicine
https://read.qxmd.com/read/38390100/computational-ensemble-expert-system-classification-for-the-recognition-of-bruxism-using-physiological-signals
#39
JOURNAL ARTICLE
Pragati Tripathi, M A Ansari, Tapan Kumar Gandhi, Faisal Albalwy, Rajat Mehrotra, Deepak Mishra
This study aimed to develop an automatic diagnostic scheme for bruxism, a sleep-related disorder characterized by teeth grinding and clenching. The aim was to improve on existing methods, which have been proven to be inefficient and challenging. We utilized a novel hybrid machine learning classifier, facilitated by the Weka tool, to diagnose bruxism from biological signals. The study processed and examined these biological signals by calculating the power spectral density. Data were categorized into normal or bruxism categories based on the EEG channel (C4-A1), and the sleeping phases were classified into wake (w) and rapid eye movement (REM) stages using the ECG channel (ECG1-ECG2)...
February 29, 2024: Heliyon
https://read.qxmd.com/read/38388761/a-novel-atrial-fibrillation-automatic-detection-algorithm-based-on-ensemble-learning-and-multi-feature-discrimination
#40
JOURNAL ARTICLE
Xiangkui Wan, Yizheng Liu, Xiaoyu Mei, Jinxing Ye, Chunyan Zeng, Yunfan Chen
Atrial fibrillation (AF) is a prevalent cardiac arrhythmia disorder that necessitates long-time electrocardiogram (ECG) data for clinical diagnosis, leading to low detection efficiency. Automatic detection of AF signals within short-time ECG recordings is challenging. To address these issues, this paper proposes a novel algorithm called Ensemble Learning and Multi-Feature Discrimination (ELMD) for the identification and detection of AF signals. Firstly, a robust classifier, BSK-Model, is constructed using ensemble learning...
February 23, 2024: Medical & Biological Engineering & Computing
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