Nonlinear dynamics of two-dimensional cardiac action potential duration mapping model with memory

Kesmia, Mounira; Boughaba, Soraya; Jacquir, Sabir

doi:10.1007/s00285-018-1318-7

Cited by 5 publications

(2 citation statements)

References 61 publications

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“…One of the most fruitful of these relationships so far investigated for myocytes is the concept of cardiac restitution, the relationship between APD for a given beat to the diastolic interval (DI) of the preceding beat, DI = BCL − APD. Earlier work on this topic typically employ relationships of the form APD n+1 = F(DI n ) which can be rewritten as APD n+1 = BCL − F(APD n ) := G(APD n ) (Guevara et al, 1984;Kulkarni and Tolkacheva, 2015;Kesmia et al, 2019). These approaches are heavily dependent on pacing protocols and a steady-state response with fixed BCL and as such have limited applicability in the case of spontaneously-beating tissue such as is observed in cultures of hiPSC-CMs.…”

Section: Discussionmentioning

confidence: 99%

Automated feature extraction from large cardiac electrophysiological data sets

Jurkiewicz

Kroboth

Zlochiver

et al. 2021

Journal of Electrocardiology

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Section: Discussionmentioning

confidence: 99%

Automated feature extraction from large cardiac electrophysiological data sets

Jurkiewicz

Kroboth

Zlochiver

et al. 2021

Journal of Electrocardiology

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“…One of the most fruitful of these relationships so far investigated for myocytes is the concept of cardiac restitution, the relationship between APD for a given beat to the diastolic interval (DI) of the preceding beat, DI = BCL−APD. Earlier work on this topic typically employ relationships of the form APD n +1 = F (DI n ) which can be rewritten as APD n +1 = BCL F (APD n ): = G (APD n ) (Guevara et al, 1984; Kulkarni and Tolka-cheva, 2015; Kesmia et al, 2019). These approaches are heavily dependent on pacing protocols and a steady-state response with fixed BCL and as such have limited applicability in the case of spontaneously-beating tissue such as is observed in cultures of hiPSC-CMs.…”

Section: Discussionmentioning

confidence: 99%

Automated Feature Extraction from Large Cardiac Electrophysiological Data Sets

Jurkiewicz

Kroboth

Zlochiver

et al. 2020

Preprint

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Rationale: A new multi-electrode array-based application for the long-term recording of action potentials from electrogenic cells makes possible exciting cardiac electrophysiology studies in health and disease. With hundreds of simultaneous electrode recordings being acquired over a period of days, the main challenge becomes achieving reliable signal identification and quantification. Objective: We set out to develop an algorithm capable of automatically extracting regions of high-quality action potentials from terabyte size experimental results and to map the trains of action potentials into a low-dimensional feature space for analysis. Methods and Results. Our automatic segmentation algorithm finds regions of acceptable action potentials in large data sets of electrophysiological readings. We use spectral methods and support vector machines to classify our readings and to extract relevant features. We are able to show that action potentials from the same cell site can be recorded over days without detrimental effects to the cell membrane. The variability between measurements 24 h apart is comparable to the natural variability of the features at a single time point. Conclusions: Our work contributes towards a non-invasive approach for cardiomyocyte functional maturation, as well as developmental, pathological and pharmacological studies.

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