Corpus ID: 237572363

Deep Spatio-temporal Sparse Decomposition for Trend Prediction and Anomaly Detection in Cardiac Electrical Conduction

@article{Zhao2021DeepSS,
  title={Deep Spatio-temporal Sparse Decomposition for Trend Prediction and Anomaly Detection in Cardiac Electrical Conduction},
  author={Xinyu Zhao and Hao Yan and Zhiyong Hu and Dongping Du},
  journal={ArXiv},
  year={2021},
  volume={abs/2109.09317}
}
  • Xinyu Zhao, Hao Yan, +1 author D. Du
  • Published 20 September 2021
  • Computer Science, Engineering
  • ArXiv
Electrical conduction among cardiac tissue is commonly modeled with partial differential equations, i.e., reaction-diffusion equation, where the reaction term describes cellular stimulation and diffusion term describes electrical propagation. Detecting and identifying of cardiac cells that produce abnormal electrical impulses in such nonlinear dynamic systems are important for efficient treatment and planning. To model the nonlinear dynamics, simulation has been widely used in both cardiac… Expand

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