Dynamic signal quality index for electrocardiograms

Yaghmaie, Negin; Maddah-Ali, Mohammad Ali; Jelinek, Herbert F.; Mazrbanrad, Faezeh

doi:10.1088/1361-6579/aadf02

Cited by 16 publications

(13 citation statements)

References 33 publications

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“…Another approach to assessing signal quality is to quantify the repeatability of successive events in the time–frequency domain. Accordingly, this is a more sophisticated approach than the ensemble standard deviation in the sense that it accounts for morphology [ 7 ]. A time–frequency representation of

is obtained using the smoothed pseudo Wigner–Ville transform [ 40 ],

where K is the number of frequency samples.…”

Section: Methodsmentioning

confidence: 99%

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Signal Quality Assessment of a Novel ECG Electrode for Motion Artifact Reduction

Halvaei

Sörnmo

Stridh

2021

Sensors

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Background: The presence of noise is problematic in the analysis and interpretation of the ECG, especially in ambulatory monitoring. Restricting the analysis to high-quality signal segments only comes with the risk of excluding significant arrhythmia episodes. Therefore, the development of novel electrode technology, robust to noise, continues to be warranted. Methods: The signal quality of a novel wet ECG electrode (Piotrode) is assessed and compared to a commercially available, commonly used electrode (Ambu). The assessment involves indices of QRS detection and atrial fibrillation detection performance, as well as signal quality indices (ensemble standard deviation and time–frequency repeatability), computed from ECGs recorded simultaneously from 20 healthy subjects performing everyday activities. Results: The QRS detection performance using the Piotrode was considerably better than when using the Ambu, especially for running but also for lighter activities. The two signal quality indices demonstrated similar trends: the gap in quality became increasingly larger as the subjects became increasingly more active. Conclusions: The novel wet ECG electrode produces signals with less motion artifacts, thereby offering the potential to reduce the review burden, and accordingly the cost, associated with ambulatory monitoring.

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is obtained using the smoothed pseudo Wigner–Ville transform [ 40 ],

where K is the number of frequency samples.…”

Section: Methodsmentioning

confidence: 99%

“…Especially in noisy ambulatory recordings, exclusion can become quite substantial, leading to that intermittent arrhythmias can go undetected. Signal quality assessment has in recent years become an art in itself as evidenced by the great number of studies [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

Signal Quality Assessment of a Novel ECG Electrode for Motion Artifact Reduction

Halvaei

Sörnmo

Stridh

2021

Sensors

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“…The above-mentioned approaches to signal quality assessment analyze and classify entire 5-or 10-segment, whereas the present approach operates on an event-to-event basis. While quality assessment on an event-to-event basis has been used before, e.g., to compute a set of heuristic, event-related parameters reflecting signal quality (Hayn et al, 2012) or a dynamic signal quality index (Yaghmaie et al, 2018), its significance in AF detection has not been the subject of investigation. Interestingly, few studies have been published investigating the influence of poor signal quality on the subsequent rhythm analysis.…”

Section: Comparison To Studies On Ecg Quality Assessmentmentioning

confidence: 99%

“…The review load can be reduced by identifying and excluding noisy signals segments before further processing is performed. The identification problem has been addressed from a general ECG analysis perspective in many studies (Ghaffari et al, 2010;Clifford et al, 2012;Hayn et al, 2012;Behar et al, 2013;Orphanidou et al, 2015;Daluwatte et al, 2016;Abdelazez et al, 2017;Orphanidou and Drobnjak, 2017;Yaghmaie et al, 2018;Moeyersons et al, 2019;Huerta-Herraiz et al, 2020;Smital et al, 2020), however, only a few studies have done so in relation to AF detection (Oster and Clifford, 2015;Taji et al, 2018;Bashar et al, 2019). Then, the methods for identifying poor-quality segments have been based on comparing the output of two different QRS detectors (one being more sensitive to noise than the other) (Oster and Clifford, 2015), deep belief networks (Taji et al, 2018), and time-frequency analysis combined with subband decomposition of the ECG signal (Bashar et al, 2019); the latter two studies did not rely on QRS detection.…”

Section: Introductionmentioning

confidence: 99%

Identification of Transient Noise to Reduce False Detections in Screening for Atrial Fibrillation

et al. 2021

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Screening for atrial fibrillation (AF) with a handheld device for recording the ECG is becoming increasingly popular. The poorer signal quality of such ECGs may lead to false detection of AF, often caused by transient noise. Consequently, the need for expert review in AF screening can become extensive. A convolutional neural network (CNN) is proposed for transient noise identification in AF detection. The network is trained using the events produced by a QRS detector, classified into either true beat detections or false detections. The CNN and a low-complexity AF detector are trained and tested using the StrokeStop I database, containing 30-s ECGs from mass screening for AF in the elderly population. Performance evaluation of the CNN-based quality control using a subset of the database resulted in sensitivity, specificity, and accuracy of 96.4, 96.9, and 96.9%, respectively. By inserting the CNN before the AF detector, the false AF detections were reduced by 22.5% without any loss in sensitivity. The results show that the number of recordings calling for expert review can be significantly reduced thanks to the identification of transient noise. The reduction of false AF detections is directly linked to the time and cost spent on expert review.

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“…Para valores positivos de k, γ xy describe la influencia lineal de los valores pasados de x t en y t indicando un mayor acoplamiento en las señales. Un resultado de la X-Corr cercano a 1 indica una interacción lineal positiva entre dos señales dado un retardo k [16] .…”

Section: Correlación Cruzadaunclassified

Comparación de Algoritmos Lineales y no Lineales para la Detección del Desacoplamiento Cardiorrespiratorio en Ratas Endotoxémicas

Flores-Duarte

Pliego-Carrillo

Ledesma-Ramírez

et al.

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Previous studies have shown that LPS-induced endotoxemia causes a cardiorespiratory (CRP) uncoupling owing to the physiological effects of systemic inflammation. Also, it is known that oxytocin has anti-inflammatory effects and cardioprotective properties; however, it is unknown whether it can modify the CRP coupling. This study aimed to compare different linear and nonlinear mathematics methods for the detection of cardiorespiratory uncoupling between cardiac and respiratory time series. The R-R time series of electrocardiograms of male rodents that were administered with saline solution (V); lipopolysaccharide (LPS); oxytocin (O) and LPS + oxytocin (LPS + Ox) were studied. We tested the R-R and respiratory series derived from the electrocardiogram (EDR) for the four groups to quantify the degree of coupling with cross-correlation; cross sample entropy; conditional entropy; mutual information; and Rényi's mutual information. We found that oxytocin does not seem to favor the CRP coupling during endotoxemia induced by LPS. Finally, we observed that the cross-sample entropy and the conditional entropy presented the highest statistical differences to identify the CRP uncoupling produced by LPS.

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Dynamic signal quality index for electrocardiograms

Abstract: The results indicate that dSQI provides a more accurate and continuous scalar metric for beat-by-beat ECG quality assessment, even for those with arrhythmia.

Cited by 16 publications

References 33 publications

Signal Quality Assessment of a Novel ECG Electrode for Motion Artifact Reduction

Signal Quality Assessment of a Novel ECG Electrode for Motion Artifact Reduction

Identification of Transient Noise to Reduce False Detections in Screening for Atrial Fibrillation

Comparación de Algoritmos Lineales y no Lineales para la Detección del Desacoplamiento Cardiorrespiratorio en Ratas Endotoxémicas

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