2022
DOI: 10.1038/s41598-022-10656-4
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Reliable P wave detection in pathological ECG signals

Abstract: Accurate automated detection of P waves in ECG allows to provide fast correct diagnosis of various cardiac arrhythmias and select suitable strategy for patients’ treatment. However, P waves detection is a still challenging task, especially in long-term ECGs with manifested cardiac pathologies. Software tools used in medical practice usually fail to detect P waves under pathological conditions. Most of recently published approaches have not been tested on such the signals at all. Here we introduce a novel metho… Show more

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Cited by 21 publications
(14 citation statements)
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“…This makes the annotations as accurate as possible, as they reflect the exact time the depolarizing wave crossed the left atrium. Accurate detection of P waves in patients is complicated by arrhythmia manifestations in ECGs [11]. Our database could be especially useful in such applications, as intracardiac records -contrary to the surface ECGs -successfully capture even atrial activity overlaid by the ventricular one (e.g.…”
Section: Discussionmentioning
confidence: 99%
“…This makes the annotations as accurate as possible, as they reflect the exact time the depolarizing wave crossed the left atrium. Accurate detection of P waves in patients is complicated by arrhythmia manifestations in ECGs [11]. Our database could be especially useful in such applications, as intracardiac records -contrary to the surface ECGs -successfully capture even atrial activity overlaid by the ventricular one (e.g.…”
Section: Discussionmentioning
confidence: 99%
“…Other approaches explore nonparametric and nonlinear ECG transformations into latent spaces potentially correlated with the P-wave shape. These transformations include empirical mode decomposition (Hossain et al, 2019), phase transformation (Martínez et al, 2010;Saclova et al, 2022), and optimization using evolutionary algorithms (Panigrahy and Sahu, 2018). Ventricular activity suppression methods aim to isolate the P-wave by removing ventricular activity from the ECG signal.…”
Section: Related Work P Wave Segmentation Algorithmsmentioning
confidence: 99%
“…In Figure 5H, the 12-lead ECG of the volunteer measured in the hospital with the sensor location at the 4th rib space on the left edge of the sternum, and the wave groups and bands of the human heart could be seen in the ECG map, which showed the R-wave, S-wave, and T-wave as well as the ST Segment. [37][38][39] In Figure 5I, a magnified view of the ECG measured by the volunteer using the PCP sensor was shown (for the graph in the red rectangle in Figure 5E,F). From the comparison of the peak shapes in the two figures, it can be seen that the PCP sensor could detect three waveforms a band, in the trend of the peak shape and the signal trajectory, they were most similarities such as R-wave S-wave T-wave, but they were some differences in the U-wave, which could not be guaranteed to be detected every time.…”
Section: Pcp Hydrogel For Human Motion Detectionmentioning
confidence: 99%