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Design of efficient fractional operator for ECG signal detection in implantable cardiac pacemaker systems
Author(s) -
Kumar Ashish,
Komaragiri Rama,
Kumar Manjeet
Publication year - 2019
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/cta.2667
Subject(s) - detector , qrs complex , thresholding , operator (biology) , computer science , filter (signal processing) , algorithm , pattern recognition (psychology) , artificial intelligence , mathematics , computer vision , medicine , telecommunications , biochemistry , chemistry , repressor , transcription factor , image (mathematics) , gene
Summary A low power and high‐performance digital electrocardiogram (ECG) detector has become a basic requirement in modern implantable cardiac pacemakers. A fractional operator‐based digital ECG detector for modern pacemaker systems is proposed in this work. Instead of conventional thresholding, an adaptive slope prediction threshold is utilized for the detection of ECG peaks. A stochastic search‐based algorithm, namely, cuckoo search algorithm, is used to design an optimal fractional operator that is used for ECG denoising. It has been found that the proposed adaptive slope prediction threshold increases the QRS complex detection performance. A low detection error rate (DER) ranges from 0.01% to 0.56%, positive predictivity (P+) ranges from 99.32% to 99.98%, sensitivity (Se) ranges from 99.45% to 99.98%, and a detection accuracy (Acc) ranges from 99.43% to 99.96% for different databases are achieved for the proposed ECG detector, which is better compared with the existing ECG detectors. The proposed design of fractional order operator based on the lattice wave digital filter (LWDF) requires a minimum number of the multipliers for its structural realization.