Title :
Detection of VF signal by a M-ary sequential detection
Author_Institution :
Dept. of Radio & Electr., Univ. of Sci. & Technol. of China, China
Abstract :
M-ary sequential detection for an unknown mean belonging to the set {θ0, θ1, . . . θ m-1} with unknown variance is described. Its purpose is to discriminate probability distributions of ventricular tachycardia and superventricular tachycardia. Analytical expressions are developed for the algorithm performance. Original signals are first converted to binary sequences by comparison with a threshold. The probability distribution of the threshold crossing interval widths (TCIWs) is proved to be a Gaussian distribution. After the TCIW is obtained one can employ a M-ary sequential hypothesis to detect the VF signal. This algorithm is suitable for implementation in a real-time system
Keywords :
electrocardiography; signal processing; ECG signal processing; Gaussian distribution; M-ary sequential detection; VF signal detection; algorithm performance; analytical expressions; binary sequences; probability distribution; real-time system; superventricular tachycardia; threshold crossing interval width; ventricular tachycardia; Algorithm design and analysis; Error analysis; Error probability; Fibrillation; Frequency domain analysis; Probability distribution; Sequential analysis; Signal analysis; Signal detection; Testing;
Conference_Titel :
Engineering in Medicine and Biology Society, 1989. Images of the Twenty-First Century., Proceedings of the Annual International Conference of the IEEE Engineering in
Conference_Location :
Seattle, WA
DOI :
10.1109/IEMBS.1989.95622
