Electrocardiogram signal modeling with adaptive parameter estimation using sequential Bayesian methods
S Edla, N Kovvali… - IEEE transactions on …, 2014 - ieeexplore.ieee.org
The automatic classification of electrocardiogram (ECG) signals is of great clinical
significance in eliminating the strenuous process of manually annotating ECG recordings …
significance in eliminating the strenuous process of manually annotating ECG recordings …
Sequential Markov chain Monte Carlo filter with simultaneous model selection for electrocardiogram signal modeling
S Edla, N Kovvali… - … Conference of the …, 2012 - ieeexplore.ieee.org
Constructing statistical models of electrocardiogram (ECG) signals, whose parameters can
be used for automated disease classification, is of great importance in precluding manual …
be used for automated disease classification, is of great importance in precluding manual …
Introduction to multimodal compression of biomedical data
A Naït-Ali, E Zeybek, X Drouot - Advanced Biosignal Processing, 2009 - Springer
The aim of this chapter is to provide the reader with a new vision of compressing jointly
medical images/videos and signals. This type of compression is called “multimodal …
medical images/videos and signals. This type of compression is called “multimodal …
Transform based approach for ECG period normalization
The irregularity in the ECG heartbeats durations and application of two dimensional ECG
compression algorithms has undoubtedly been a challenge in this field. In this paper, an …
compression algorithms has undoubtedly been a challenge in this field. In this paper, an …
Electrocardiogram signal modeling using interacting multiple models
S Edla, N Kovvali… - … Conference Record of …, 2011 - ieeexplore.ieee.org
The automatic classification of different heart diseases for monitoring cardiac health through
the use of dynamic modeling of electrocardiogram (ECG) signals would yield innovative …
the use of dynamic modeling of electrocardiogram (ECG) signals would yield innovative …
Efficient dynamic modelling of ECG with myocardial infarction using interacting multiple model and particle filter
The automatic identification of cardiac condition through dynamic modelling of
electrocardiogram (ECG) signal has immense clinical significance as it eliminates the task of …
electrocardiogram (ECG) signal has immense clinical significance as it eliminates the task of …
[图书][B] Adaptive Parameter Estimation, Modeling and Patient-Specific Classification of Electrocardiogram Signals
SR Edla - 2012 - search.proquest.com
Adaptive processing and classification of electrocardiogram (ECG) signals are important in
eliminating the strenuous process of manually annotating ECG recordings for clinical use …
eliminating the strenuous process of manually annotating ECG recordings for clinical use …
[引用][C] Compression of physiological signals
A Naït‐Ali - Compression of Biomedical Images and Signals, 2008 - Wiley Online Library
Compression of Physiological Signals Page 1 Chapter 6 Compression of Physiological Signals
6.1. Introduction The aim of this chapter is to provide the reader with a general overview of the …
6.1. Introduction The aim of this chapter is to provide the reader with a general overview of the …