Digital illustration of a heart with clear and blurred electrical pathways, representing signal fidelity in atrial fibrillation.

Decoding Atrial Fibrillation: How Signal Fidelity Impacts Mapping Success

Nico Varela in Health & Wellness December 2025 • 4 min read.

"Discover how understanding signal fidelity in electrograms can improve the accuracy of mapping and treating atrial fibrillation."

Atrial fibrillation (AF), a common heart rhythm disorder, affects millions worldwide and significantly increases the risk of stroke and heart failure. Mapping the heart's complex electrical activity is essential for effective treatment, yet accurately identifying the sources of AF can be challenging. Researchers are constantly seeking better ways to map these erratic signals.

Traditional methods often struggle with various sources of signal contamination, making it difficult to pinpoint the precise locations driving the arrhythmia. Recent studies using advanced electrode arrays have shown promise in identifying spiral waves or rotors, which may underlie AF. However, these findings are debated, highlighting the need for improved mapping techniques.

A recent study published in Frontiers in Physiology introduces a novel approach to assess signal fidelity in electrograms—recordings of the heart's electrical activity. The study explores how signal contamination impacts the accuracy of AF mapping and proposes methods to enhance the robustness of observed rotational activity in the heart.

What is Signal Fidelity and Why Does It Matter?

Digital illustration of a heart with clear and blurred electrical pathways, representing signal fidelity in atrial fibrillation.

Signal fidelity refers to the quality and reliability of the electrical signals recorded from the heart. High signal fidelity means the electrograms accurately represent the heart's underlying electrical activity, while low signal fidelity indicates the presence of noise or distortion. Areas of low signal fidelity often correspond to the location of rotational cores, where the electrical signals are most complex and chaotic.

The research team developed a new measure to quantify signal fidelity, focusing on the consistency and clarity of deflections in the electrograms. By analyzing the phase of these signals, the researchers could distinguish between high-fidelity signals with clear, distinct deflections and low-fidelity signals with ambiguous or inconsistent deflections.

High Fidelity Signals: Distinct negative deflections (-dV/dt) align with activation times.
Low Fidelity Signals: Ambiguous deflections occur at times other than activation.
Signal Fidelity (Γ): Ranges from -1 to +1, with higher values indicating better signal quality.

Domains of low signal fidelity often pinpoint the location of rotational cores. This discovery is pivotal because it suggests that the very sources of AF are also the areas where traditional mapping techniques may be least reliable. Understanding signal fidelity can help electrophysiologists identify and focus on these critical areas.

The Future of AF Mapping: Enhancing Accuracy and Outcomes

By understanding and addressing the impact of signal fidelity, electrophysiologists can improve the accuracy of AF mapping and potentially enhance treatment outcomes. This approach may also lead to more effective ablation strategies, targeting the sources of AF with greater precision. Further research and clinical studies are needed to validate these findings and translate them into improved patient care.

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Everything You Need To Know

What is signal fidelity in the context of atrial fibrillation mapping, and why is it important?

Signal fidelity in atrial fibrillation (AF) mapping refers to the quality and reliability of electrical signals recorded from the heart, known as electrograms. High signal fidelity means the electrograms accurately represent the heart's electrical activity, while low signal fidelity indicates noise or distortion. This is crucial because accurate mapping of the heart's electrical activity is essential for effective AF treatment. Areas of low signal fidelity often correspond to the location of rotational cores, where the electrical signals are most complex. Researchers are developing new measures, like the Signal Fidelity (Γ), to quantify this and improve mapping accuracy.

How does signal contamination affect the accuracy of atrial fibrillation mapping?

Signal contamination introduces noise and distortion in electrograms, making it difficult to accurately identify the sources of atrial fibrillation. Traditional methods often struggle with these contaminated signals, potentially leading to misidentification of the areas driving the arrhythmia. Low signal fidelity, which results from contamination, can obscure the distinct electrical patterns associated with AF, such as spiral waves or rotors, hindering effective treatment strategies. The study suggests that addressing signal contamination can enhance the robustness of observed rotational activity in the heart and improve mapping accuracy.

What are the key characteristics of High Fidelity Signals versus Low Fidelity Signals in electrograms?

High fidelity signals, as captured in electrograms, are characterized by distinct negative deflections (-dV/dt) that align with activation times. This indicates a clear and accurate representation of the heart's electrical activity. Conversely, low fidelity signals exhibit ambiguous deflections, meaning they occur at times other than activation. This ambiguity arises from noise and distortion, making it difficult to interpret the underlying electrical activity. The Signal Fidelity (Γ) is a measure used to quantify this, with higher values (closer to +1) indicating better signal quality.

Can you explain the concept of the Signal Fidelity (Γ) measure and how it's used?

The Signal Fidelity (Γ) is a new measure introduced in the study to quantify the quality of electrical signals in electrograms. It ranges from -1 to +1, where higher values indicate better signal quality. Researchers analyze the phase of signals to determine the consistency and clarity of deflections in the electrograms. By analyzing the phase of these signals, the researchers could distinguish between high-fidelity signals with clear, distinct deflections and low-fidelity signals with ambiguous or inconsistent deflections. This measure helps distinguish between high-quality, reliable signals and those with noise or distortion. Understanding Signal Fidelity (Γ) can help electrophysiologists identify and focus on these critical areas.

How can understanding and addressing signal fidelity improve the treatment of atrial fibrillation?

By understanding and addressing the impact of signal fidelity, electrophysiologists can improve the accuracy of atrial fibrillation (AF) mapping. This can lead to more effective ablation strategies, targeting the sources of AF with greater precision. Accurate mapping is essential for effective treatment, and improved signal analysis helps identify areas of rotational cores which are crucial for successful treatment. Enhancing the robustness of observed rotational activity in the heart through better signal analysis may ultimately enhance treatment outcomes. Further research and clinical studies are needed to validate these findings and translate them into improved patient care.