Low Resource Complexity R-peak Detection Based on Triangle Template Matching and Moving Average Filter

Nguyen, Thanh-Sang; Dinh, Anh; Bui, Francis M.

doi:10.3390/s19183997

Cited by 26 publications

(19 citation statements)

References 42 publications

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“…Our claim is supported by the results obtained by the proposed optimization scheme evaluated on the MIT-BIH dataset shown in Table 2. As expected, the obtained band-pass filter cut off frequencies by our procedure [4,24] Hz are wider than the ones of the original Pan-Tompkins algorithm, [5,15] Hz. This allowed detecting many QRS waves that were missed by the Pan-Tompkins algorithm.…”

Section: Resultssupporting

confidence: 83%

“…Concerning the execution time, the proposed scheme requires 1.3 seconds to detect 2273 beats from the 100m MIT/BIH record, which has a duration of 30 minutes and contains 650000 samples, using an Intel i5 M480 2.67 GHz with 4GB of RAM running on MATLAB software, corresponding to 57.19 ms to detect a beat, or 2 µs to process a sample, making our scheme suitable for real-time and embedded systems. Our detector outperforms all existing methods except two works, Nguyen et al [15] with 0.16 seconds to process 30 minutes of recording, and 0.43 seconds at mean reported by Elgendi [5]. However, the proposed scheme is superior in detection and accuracy.…”

Section: Resultsmentioning

confidence: 63%

“…However, the proposed scheme is superior in detection and accuracy. On the benchmark MIT arrhythmia, our algorithm generates 0.17% of DER error, where Nguyen et al [15] reported 0.49% of error. Also, in terms of sensitivity and specificity, the work of Elgendi [5] is inferior to ours with 99.78% of sensitivity and 99.87% of specificity, where our detector achieved 99.92% of sensitivity and 99.91% of specificity.…”

Section: Resultsmentioning

confidence: 84%

“…Mourad and Fethi [12] detect QRS complex from wavelet coefficients after filtering for denoising. Nguyen et al [15] proposed the triangle template matching for the determination of the QRS positions. Xiang et al [26] used two Convolutional Neural Networks and an MLP for the estimation of the QRS positions.…”

Section: Introductionmentioning

confidence: 99%

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Untitled

2019

IAJIT

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The QRS detection is a crucial step in ECG signal analysis; it has a great impact on the beats segmentation and in the final classification of the ECG signal. The Pan-Tompkins is one of the first and best-performing algorithms for QRS detection. It performs filtering for noise suppression, differentiation for slope dominance, and thresholding for decision making. All of the parameters of the Pan-Tompkins algorithm are selected empirically. However, we think that the Pan-Tompkins method can achieve better performance if the parameters were optimized. Therefore, we propose an adaptive algorithm that looks for the best set of parameters that improves the Pan-Tompkins algorithm performance. For this purpose, we formulate the parameter design as an optimization problem within a particle swarm optimization framework. Experiments conducted on the 24 hours recording of the MIT/BIH arrhythmia benchmark dataset achieved an overall accuracy of 99.83% which outperforms the state-of-the-art time-domain algorithms.

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Section: Resultssupporting

confidence: 83%

Section: Resultsmentioning

confidence: 63%

Section: Resultsmentioning

confidence: 84%

Section: Introductionmentioning

confidence: 99%

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2019

IAJIT

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“…8 (a). In this way, the cutoff frequencies were defined in order to remove low noise (baseline wander and DC) and 50-60Hz artifacts, while preserving the features of R-waves whose central frequency content is in 17 Hz [39].…”

Section: Bio-sensing Applicationmentioning

confidence: 99%

A 59 pA/V and 62 nW Differential OTA with 0.35% THD for Biomedical Applications

Silva

Rodovalho

Marques

et al. 2021

JICS

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This paper presents a novel differential pA/V Operational Transconductance Amplifier (OTA) topology. The circuit is suitable for the implementation of fully integrated operational transconductance amplifier-capacitance (OTA-C) filters with small feature size capacitors, suited for electrophysiological signal acquisition and conditioning. Unlike typical OTA-Cs, the proposed topology consists of transconductance reduction technique based on unbalanced output branches thatallow current subtraction thus enabling transconductances in the order of pA/V. The technique is demonstrated through the design of a 59pA/V transconductor, which is very suited for designing long-time-constant filters. This OTA-C achieved a worst-case 0.35% THD with just 61.7nW average power consumption, which allows its applicability to biomedical implants. Simulations were carried out with STMicroelectronics 0.13µm HCMOS9 node using Cadence’s IC design tools. Weemployed the OTA in a design of a fourth-order bandpass filter with a narrow bandwidth of 12.5–21.8Hz. Similar results to the ideal transfer function, turn the proposed OTA ideal for biosensing-based applications.

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A Robust R-Peaks Detection Algorithm of ECG Signals by Using Adaptive Combined Threshold

Cui

2021

Lecture Notes in Electrical Engineering

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Accurate identification of R-peaks is the basis of ECG correlation analysis. In this paper, we propose a method that first enhances the features of R-peaks using difference-square operations, and then locates R-peaks by threshold detection, slope judgment and backtracking search, where the threshold is a set of combined thresholds that are related to R peak amplitude, R-R interval and noise, respectively. The algorithm was tested on the MIT-BIH arrhythmia database, and the sensitivity Se = 99.59%, while the positive prediction rate +P = 99.71%. The method shows robustness with the addition of different noise levels. The experimental results show that the proposed algorithm reduces the false detection rate and increases the recognition rate, takes into account the real-time and anti-interference performance, and is suitable for the correlation analysis of ECG.

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Low Resource Complexity R-peak Detection Based on Triangle Template Matching and Moving Average Filter

Cited by 26 publications

References 42 publications

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A 59 pA/V and 62 nW Differential OTA with 0.35% THD for Biomedical Applications

A Robust R-Peaks Detection Algorithm of ECG Signals by Using Adaptive Combined Threshold

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