A real‐time signal processing software package for the electrophysiology laboratory. - Tiver, Kathryn D.; Strong, Campbell; Dharmaprani, Dhani; Chapman, Darius; Jenkins, Evan; Shahrbabaki, Sobhan Salari; Ganesan, Anand N. (Journal of Cardiovascular Electrophysiology, 2024)
Background: Real‐time signal processing has to date been difficult to implement in the clinical electrophysiology laboratory. To date, no open access software solutions are available in electrophysiology (EP) laboratories to facilitate real‐time intraprocedural signal analysis. We aimed to develop an open access, scalable Python plug‐in to allow real‐time signal processing during human EP procedures. Methods and Results: A Python‐based plug in for the widely available EnsiteX mapping system was developed. This plug‐in utilized the LiveSync feature of the system to allow real‐time signal analysis. An open access library was developed to allow end‐users to implement real‐time signal analysis using this platform, implemented in the Python programming language https://github.com/anand9176/WaveWatch5000Public. Conclusion: We have developed and demonstrated the feasibility of a readily scalable and open‐access Python‐based plug in to an electroanatomic mapping system (EnSiteX) to allow real‐time processing and display of electrogram (EGM) based information for the procedural electrophysiologist to view intraprocedurally in the electrophysiology laboratory. The availability, to the clinician, of traditional and novel EGM‐based metrics at the time of intervention, such as atrial fibrillation ablation, allows for key mechanistic insights into critical unresolved questions regarding arrhythmia mechanism.