Kurtosis as a statistical approach to identify the pivot point of the rotor

Shivaram P. Arunachalam, Elizabeth M. Annoni, Siva Mulpuru, Paul Andrew Friedman, Elena G. Tolkacheva

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia that causes stroke affecting more than 2.3 million people in the US. Catheter ablation to terminate AF is successful for paroxysmal AF but suffers limitations with persistent AF patients as current mapping methods cannot identify AF active substrates outside of pulmonary vein region. In this work, we developed a novel Kurtosis based mapping technique that can accurately identify pivot points of the rotors that were induced in ex-vivo isolated rabbit heart. The results indicate that the chaotic nature of rotor pivot point results in higher Kurtosis compared to the periphery thereby enabling its accurate identification. Our results suggest that Kurtosis technique can be further applied to intra-atrial electrograms from AF patients with rotors to accurately identify the rotor pivot point by generating 3-dimensional (3D) patient-specific Kurtosis maps. Validation of this new Kurtosis based mapping technology is required through clinical studies with both paroxysmal and persistent AF patient data.

Original languageEnglish (US)
Title of host publication2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages497-500
Number of pages4
Volume2016-October
ISBN (Electronic)9781457702204
DOIs
StatePublished - Oct 13 2016
Event38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 - Orlando, United States
Duration: Aug 16 2016Aug 20 2016

Other

Other38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
CountryUnited States
CityOrlando
Period8/16/168/20/16

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ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

Arunachalam, S. P., Annoni, E. M., Mulpuru, S., Friedman, P. A., & Tolkacheva, E. G. (2016). Kurtosis as a statistical approach to identify the pivot point of the rotor. In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 (Vol. 2016-October, pp. 497-500). [7590748] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2016.7590748