An approach to cardiac arrhythmia analysis using hidden Markov models
- 1 January 1990
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Biomedical Engineering
- Vol. 37 (9) , 826-836
- https://doi.org/10.1109/10.58593
Abstract
This paper describes a new approach to ECG arrhythmia analysis based on "hidden Markov modeling" (HMM), a technique successfully used since the mid-1970's to model speech waveforms for automatic speech recognition. Many ventricular arrhythmias can be classified by detecting and analyzing QRS complexes and determining R-R intervals. Classification of supraventricular arrhythmias, however, often requires detection of the P wave in addition to the QRS complex. The hidden Markov modeling approach combines structural and statistical knowledge of the ECG signal in a single parametric model. Model parameters are estimated from training data using an iterative, maximum likelihood reestimation algorithm. Initial results suggest that this approach may provide improved supraventricular arrhythmia analysis through accurate representation of the entire beat including the P wave.Keywords
This publication has 19 references indexed in Scilit:
- BEAM. An accelerator for speech recognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- A tutorial on hidden Markov models and selected applications in speech recognitionProceedings of the IEEE, 1989
- The graph search machine (GSM): A VLSI architecture for connected speech recognition and other applicationsProceedings of the IEEE, 1987
- A hardware accelerator for speech recognition algorithmsACM SIGARCH Computer Architecture News, 1986
- An introduction to hidden Markov modelsIEEE ASSP Magazine, 1986
- A Maximum Likelihood Approach to Continuous Speech RecognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1983
- Computer diagnosis of supraventricular and ventricular arrhythmias. A new esophageal technique.Circulation, 1979
- Continuous speech recognition by statistical methodsProceedings of the IEEE, 1976
- PVC detection by the heart-beat interval data—Markov chain approachComputers and Biomedical Research, 1975
- An inequality with applications to statistical estimation for probabilistic functions of Markov processes and to a model for ecologyBulletin of the American Mathematical Society, 1967