Zobrazeno 1 - 10
of 317
pro vyhledávání: '"R-peak detection"'
Publikováno v:
IEEE Access, Vol 12, Pp 167049-167058 (2024)
R peak detection is fundamental to the analysis of long-term electrocardiogram (ECG) signals. Despite their significant success in R peak detection, neural networks based on statistical learning usual require more than 50% of all data for training. H
Externí odkaz:
https://doaj.org/article/d2859ca70a30413fb183df918c0a8239
Publikováno v:
Applied Sciences, Vol 14, Iss 21, p 10078 (2024)
Electrocardiographic (ECG) R-peak detection is essential for every sensor-based cardiovascular health monitoring system. To validate R-peak detectors, comparing the predicted results with reference annotations is crucial. This comparison is typically
Externí odkaz:
https://doaj.org/article/6ac73602c7b644aa8208e4b740ccae2f
Publikováno v:
Mathematical Biosciences and Engineering, Vol 20, Iss 11, Pp 19191-19208 (2023)
Heart rate variability (HRV) is derived from the R-R interval, which depends on the precise localization of R-peaks within an electrocardiogram (ECG) signal. However, current algorithm assessment methods prioritize the R-peak detection's sensitivity
Externí odkaz:
https://doaj.org/article/b02ee0d8260f48e7bc80a8167da1d7ae
Publikováno v:
Sensors, Vol 24, Iss 17, p 5713 (2024)
Low-cost, portable devices capable of accurate physiological measurements are attractive tools for coaches, athletes, and practitioners. The purpose of this study was primarily to establish the validity and reliability of Movesense HR+ ECG measuremen
Externí odkaz:
https://doaj.org/article/1a16908efcbb4a52871a1559ace43320
Publikováno v:
Sensors, Vol 24, Iss 13, p 4376 (2024)
Electrocardiography (ECG) has emerged as a ubiquitous diagnostic tool for the identification and characterization of diverse cardiovascular pathologies. Wearable health monitoring devices, equipped with on-device biomedical artificial intelligence (A
Externí odkaz:
https://doaj.org/article/c938703091c94410a7d8410244e5f4c0
Publikováno v:
SoftwareX, Vol 25, Iss , Pp 101608- (2024)
The computational detection of R-peaks in an electrocardiogram (ECG) is particularly important for assessing vital signs in ambulatory settings. Algorithmic approaches are mainly open source and available for research purposes, primarily in the Pytho
Externí odkaz:
https://doaj.org/article/88089b5808e0473a91dccaf760f021c1
Akademický článek
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Publikováno v:
Sensors, Vol 23, Iss 21, p 8691 (2023)
Recently, deep learning (DL) models have been increasingly adopted for automatic analyses of medical data, including electrocardiograms (ECGs). Large, available ECG datasets, generally of high quality, often lack specific distortions, which could be
Externí odkaz:
https://doaj.org/article/fb70029cf0de42aeba31c4065a7f2b9b
Autor:
Ramón A. Félix, Alberto Ochoa-Brust, Walter Mata-López, Rafael Martínez-Peláez, Luis J. Mena, Laura L. Valdez-Velázquez
Publikováno v:
Sensors, Vol 23, Iss 21, p 8796 (2023)
Heart diseases rank among the most fatal health concerns globally, with the majority being preventable through early diagnosis and effective treatment. Electrocardiogram (ECG) analysis is critical in detecting heart diseases, as it captures the heart
Externí odkaz:
https://doaj.org/article/c017d4af81754df0996cc005227c022d
Publikováno v:
IEEE Access, Vol 10, Pp 114355-114363 (2022)
ECG is one of the most effective medical tests for heart disease diagnosis, and R-peak detection is the first step in ECG interpretation. For wearable ECG signals, the difficulty of R-peak detection mainly lies in the interference of dynamic strong n
Externí odkaz:
https://doaj.org/article/6b188babbcb24aaa9553f35e612b2373