Analysis of QRS detection algorithms barely sensitive to the QRS shape

Sokolova, Anastasia; Pyko, Nikita S.; Pyko, Svetlana A.; Uljanitsky, Yury D.; Andreeva, Olga M.

doi:10.1109/eiconrus.2017.7910663

Cited by 6 publications

(3 citation statements)

References 2 publications

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“…Although in this recent study it has been demonstrated that improved performance could be achieved by combining the signal energy based and the derivative based analysis compared to using only one of them, the choice of the optimal weighting coefficients remains challenging, as it strongly depends on particular signal shapes, and thus also varies between individuals, leads, time fragments and so on. In turn, these variations require additional adjustments of the weighting coefficient, this way increasing the complexity of the algorithm [21].…”

Section: Event Detection Methodsmentioning

confidence: 99%

“…Following this strategy, we compared the total heartbeat interval variances 2 T σ obtained by each of the algorithms tested. Since in earlier works preliminary filtering of the raw ECG signals have been suggested [21], although its impact on the results is twofold, resulting in the noise reduction accompanied by the inevitable loss of temporal resolution, we have tested the energy based and the gradient based algorithms both with and without preliminary filtering procedure with the use of a 4 th order Chebyshev filter. Corresponding results are summarized in Table 1.…”

Section: Detection Of Qrs Waves In Long-term Ecg Recordsmentioning

confidence: 99%

See 1 more Smart Citation

Improved online event detection and differentiation by a simple gradient-based nonlinear transformation: Implications for the biomedical signal and image analysis

Sokolova

Uljanitski

Kayumov

et al. 2021

Biomedical Signal Processing and Control

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Section: Event Detection Methodsmentioning

confidence: 99%

Section: Detection Of Qrs Waves In Long-term Ecg Recordsmentioning

confidence: 99%

Improved online event detection and differentiation by a simple gradient-based nonlinear transformation: Implications for the biomedical signal and image analysis

Sokolova

Uljanitski

Kayumov

et al. 2021

Biomedical Signal Processing and Control

View full text Add to dashboard Cite

“…Following this strategy, we compared the total heartbeat interval variances σ obtained by each of the algorithms tested. Since in earlier works preliminary filtering of the raw ECG signals have been suggested [21], although its impact on the results is twofold, resulting in the noise reduction accompanied by the inevitable loss of temporal resolution, we have tested the energy based and the gradient based algorithms both with and without preliminary filtering procedure with the use of a 4 th order Chebyshev filter. Corresponding results are summarized in Table 1.…”

Section: Detection Of Qrs Waves In Long-term Ecg Recordsmentioning

confidence: 99%

Improved online event detection and differentiation by a simple gradient-based nonlinear transformation: Implications for the biomedical signal and image analysis

Sokolova

Uljanitski

Kayumov

et al. 2020

Preprint

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Despite recent success in advanced signal analysis technologies, simple and universal methods are still of interest in a variety of applications. Wearable devices including biomedical monitoring and diagnostic systems suitable for long-term operation are prominent examples, where simple online signal analysis and early event detection algorithms are required. Here we suggest a simple and universal approach to the online detection of events represented by abrupt bursts in long-term observational data series. We show that simple gradient-based transformations obtained as a product of the signal and its derivative lead to the improved accuracy of the online detection of any significant bursts in the observational data series irrespective of their particular shapes. We provide explicit analytical expressions characterizing the performance of the suggested approach in comparison with the conventional solutions optimized for particular theoretical scenarios and widely utilized in various signal analysis applications. Moreover, we estimate the accuracy of the gradient-based approach in the exact positioning of single ECG cycles, where it outperforms the conventional Pan-Tompkins algorithm in its original formulation, while exhibiting comparable detection efficacy. Finally, we show that our approach is also applicable to the comparative analysis of lanes in electrophoretic gel images widely used in life sciences and molecular diagnostics like restriction fragment length polymorphism (RFLP) and variable number tandem repeats (VNTR) methods.

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Vital Signs Telemonitoring by Using Smart Body Area Networks, Mobile Devices and Advanced Signal Processing

Costin

Rotariu

2017

Advances in Biomedical Informatics

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Analysis of QRS detection algorithms barely sensitive to the QRS shape

Cited by 6 publications

References 2 publications

Improved online event detection and differentiation by a simple gradient-based nonlinear transformation: Implications for the biomedical signal and image analysis

Improved online event detection and differentiation by a simple gradient-based nonlinear transformation: Implications for the biomedical signal and image analysis

Improved online event detection and differentiation by a simple gradient-based nonlinear transformation: Implications for the biomedical signal and image analysis

Vital Signs Telemonitoring by Using Smart Body Area Networks, Mobile Devices and Advanced Signal Processing

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