Separation of atrial and ventricular components of body surface potentials in atrial fibrillation using principal component analysis: a computer modelling study

Haigh, A.J.; Murray, Alan; Langley, Philip

doi:10.1109/cic.2005.1588105

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…The sum of these components may then be used to test procedures aiming at subtracting the ventricular involvement, with the simulated AF components serving as the gold standard [164]. Some recent developments in ECG processing techniques, such as cancellation of the ventricular activity [165], [166], vectorcardiogram analysis [167], estimation of the dominant frequency of the ECG [168] were validated in part by using signals originating from an atrial model combined with a torso geometry.…”

Section: A Evaluation Of Signal Processing Techniquesmentioning

confidence: 99%

Modeling Atrial Arrhythmias: Impact on Clinical Diagnosis and Therapies

Jacquemet

Kappenberger

Henriquez

2008

IEEE Rev. Biomed. Eng.

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Atrial arrhythmias are the most frequent sustained rhythm disorders in humans and often lead to severe complications such as heart failure and stroke. Despite the important insights provided by animal models into the mechanisms of atrial arrhythmias, direct translation of experimental findings to new therapies in patients has not been straightforward. With the advances in computer technology, large-scale electroanatomical computer models of the atria that integrate information from the molecular to organ scale have reached a level of sophistication that they can be used to interpret the outcome of experimental and clinical studies and aid in the rational design of therapies. This paper reviews the state-of-the-art of computer models of the electrical dynamics of the atria and discusses the evolving role of simulation in assisting the clinical diagnosis and treatment of atrial arrhythmias.

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Section: A Evaluation Of Signal Processing Techniquesmentioning

confidence: 99%

Modeling Atrial Arrhythmias: Impact on Clinical Diagnosis and Therapies

Jacquemet

Kappenberger

Henriquez

2008

IEEE Rev. Biomed. Eng.

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Ventricular Fibrillation Prediction and Detection: A Comprehensive Review of Modern Techniques

Fira,

Costin,

Goraș

2024

Applied Sciences

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This review offers a detailed examination of modern ECG signal processing techniques employed in the prediction and detection of ventricular fibrillation (VF). It contains a thorough analysis of recent advancements in the field, exploring the strengths, limitations, and real-world applications of these techniques. By evaluating the current state of research, the review seeks to identify the most effective approaches and highlight key areas where further investigation is needed, ultimately guiding future research efforts toward improving VF prediction and detection. Overall, AI has shown significant potential in a range of VF-related tasks. However, real-world implementation encounters several challenges, including difficulties in accurately interpreting ECG signals, the variability in individual physiological responses, and the infrequency of ventricular fibrillation events. Additionally, there are issues related to the critical timing required for detecting VF, the presence of similar arrhythmias, the need for adaptation to new ECG devices, energy consumption concerns, and the complex process of obtaining regulatory and legislative approvals for integrating software components into medical equipment. We consider that the present work might be useful in approaching the above challenges.

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Separation of atrial and ventricular components of body surface potentials in atrial fibrillation using principal component analysis: a computer modelling study

Cited by 2 publications

References 3 publications

Modeling Atrial Arrhythmias: Impact on Clinical Diagnosis and Therapies

Modeling Atrial Arrhythmias: Impact on Clinical Diagnosis and Therapies

Ventricular Fibrillation Prediction and Detection: A Comprehensive Review of Modern Techniques

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