Variance reduction of prediction error using fractional digital differentiation: application to ECG signal processing

Ferdi, Youcef; Herbeuval, Jean-Pierre; Charef, A.

doi:10.1109/iembs.2001.1017200

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…During the last two decades, lots of research efforts have been focused on FDs due to their applications in different areas of physics and engineering. [48][49][50][51][52][53] The use of FDs in the field of signal processing is inspired by its excellent performances and robustness in the field of control theory. [54][55][56] The use of FD leads to more flexible design in ECG signal detection.…”

Section: Literature Review/related Workmentioning

confidence: 99%

Design of efficient fractional operator for ECG signal detection in implantable cardiac pacemaker systems

Kumar

Komaragiri

Kumar

2019

Circuit Theory & Apps

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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.

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Section: Literature Review/related Workmentioning

confidence: 99%

Design of efficient fractional operator for ECG signal detection in implantable cardiac pacemaker systems

Kumar

Komaragiri

Kumar

2019

Circuit Theory & Apps

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“…This STC signal is passed through two parallel IIR digital fractional order differentiators of order a and 2a such that 0.5 , a , 1. The impulse responses of these IIR digital fractional order differentiators are given, respectively, in (14) and (18). The output signals y1(k) and y2(k) of the fractional order differentiators are then used to extract the maximum peaks detected (MPD) as well as their corresponding localisations, which will be classified as R waves.…”

Section: R-wave Detectionmentioning

confidence: 99%

“…Only in recent years can one find some applications in signal processing theory [3,[14][15][16]. The interest for the introduction of these concepts in signal processing applications has been motivated by their good performances and robustness obtained in control theory.…”

Section: Introductionmentioning

confidence: 99%

Digital fractional order operators for R-wave detection in electrocardiogram signal

Benmalek

Charef

2009

IET Signal Process.

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In this study, we present an effective R-wave detection method in the QRS complex of the electrocardiogram (ECG) based on digital differentiation and integration of fractional order. The detection algorithm is performed in two steps. The pre-processing step is based on a fractional order digital band-pass filter whose fractional order is obtained by maximising the signal to noise ratio of the ECG signal, followed by a five points differentiator of fractional order 1.5 then the squaring transformation and the smoothing are used to generate peaks corresponding to the ECG parts with high slopes. The detection step is a new and simple strategy which is also based on fractional order operators for the localisation of the R waves. The MIT/ BIH arrhythmia database is used to test the effectiveness of the proposed method. The algorithm has provided very good performance and has achieved about 99.86% of the detection rate for the standard database. The results obtained are presented, discussed and compared to the most recent and efficient R-wave detection algorithms.

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Reduction of Aliasing Effects of RF PWM Modulated Signals by Cross Point Estimation

Seebacher

Singerl

Schuberth

et al. 2014

IEEE Trans. Circuits Syst. I

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Variance reduction of prediction error using fractional digital differentiation: application to ECG signal processing

Cited by 3 publications

References 8 publications

Design of efficient fractional operator for ECG signal detection in implantable cardiac pacemaker systems

Design of efficient fractional operator for ECG signal detection in implantable cardiac pacemaker systems

Digital fractional order operators for R-wave detection in electrocardiogram signal

Reduction of Aliasing Effects of RF PWM Modulated Signals by Cross Point Estimation

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