Title :
Nonlinear transforms of ECG signals for digital QRS detection: a quantitative analysis
Author :
Suppappola, Seth ; Sun, Ying
Author_Institution :
Dept. of Electr. Eng., Rhode Island Univ., Kingston, RI, USA
fDate :
4/1/1994 12:00:00 AM
Abstract :
A class of algorithms has been developed which detects QRS complexes in the electrocardiogram (ECG). The algorithms employ nonlinear transforms derived from multiplication of backward differences (MOBD). The algorithms are evaluated with the American Heart Association ECG database, and comparisons are made with the algorithms reported by Okada (1979) and by Hamilton and Tompkins (1986). The MOBD algorithms provide a good performance tradeoff between accuracy and response time, making this type of algorithm desirable for real-time microprocessor-based implementation.
Keywords :
electrocardiography; medical signal processing; signal detection; transforms; American Heart Association ECG database; ECG signals; accuracy; algorithms; backward differences multiplication; digital QRS detection; nonlinear transforms; performance tradeoff; quantitative analysis; real-time microprocessor-based implementation; response time; Algorithm design and analysis; Approximation algorithms; Databases; Detection algorithms; Electrocardiography; Filters; Frequency; Heart; Signal analysis; Sun; Algorithms; Arrhythmias, Cardiac; Databases, Factual; Electrocardiography; Heart Ventricles; Humans; Microcomputers; ROC Curve; Reproducibility of Results; Signal Processing, Computer-Assisted; Time Factors;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
