DocumentCode
2958513
Title
QRS detection using a fuzzy neural network
Author
Cohen, Kevin P. ; Tompkins, Willis J. ; Djohan, Adrianus ; Webster, John G. ; Hu, Yu H.
Author_Institution
Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA
Volume
1
fYear
1995
fDate
20-25 Sep 1995
Firstpage
189
Abstract
We developed a QRS detection algorithm which uses a fuzzy neural network (FNN) to process lead II recordings of the ECG. We trained and tested our algorithm using the MIT/BIH arrhythmia database, and compared our results to existing algorithms. For tapes 100, 105 and 108, our FNN reduced the total number of combined false-positive and false-negative detections from 174 to 44
Keywords
electrocardiography; feature extraction; fuzzy neural nets; learning (artificial intelligence); medical signal processing; ECG; MIT/BIH arrhythmia database; QRS detection algorithm; false-negative detections; false-positive detections; fuzzy neural network; lead II recordings; Band pass filters; Data mining; Detection algorithms; Electrocardiography; Feature extraction; Finite impulse response filter; Fuzzy neural networks; Fuzzy systems; Neural networks; Noise level;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 1995., IEEE 17th Annual Conference
Conference_Location
Montreal, Que.
Print_ISBN
0-7803-2475-7
Type
conf
DOI
10.1109/IEMBS.1995.575064
Filename
575064
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