Zobrazeno 1 - 10
of 10 349
pro vyhledávání: '"detrended"'
Autor:
Ian Meneghel Danilevicz, Vincent Theodoor van Hees, Frank C. T. van der Heide, Louis Jacob, Benjamin Landré, Mohamed Amine Benadjaoud, Séverine Sabia
Publikováno v:
BMC Medical Research Methodology, Vol 24, Iss 1, Pp 1-15 (2024)
Abstract Accelerometers, devices that measure body movements, have become valuable tools for studying the fragmentation of rest-activity patterns, a core circadian rhythm dimension, using metrics such as inter-daily stability (IS), intradaily variabi
Externí odkaz:
https://doaj.org/article/43e2e95bad4f47f58b49c71ed72dd869
Akademický článek
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Akademický článek
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Autor:
Martin O. Mendez, Anna M. Bianchi, Florian Recker, Brigitte Strizek, J. S. Murguía, Pierluigi Reali, Jorge Jimenez-Cruz
Publikováno v:
Frontiers in Cardiovascular Medicine, Vol 11 (2024)
Understanding the complex dynamics of heart rate variability (HRV) during pregnancy is crucial for monitoring both maternal well-being and fetal health. In this study, we use the Multifractal Detrended Fluctuations Analysis approach to investigate HR
Externí odkaz:
https://doaj.org/article/bfd376305826459fa1d783d942df5b0a
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 18235-18246 (2024)
Snow depth monitoring is crucial for hydrology, climate research, and avalanche prediction. While traditional global navigation satellite system (GNSS) reflectometer methods offer cost-effective snow thickness retrieval, they suffer from poor accurac
Externí odkaz:
https://doaj.org/article/00253e5eb2d24badb00473379c9e135a
Autor:
Deshan Ma, Conghui Li, Wenbin Shi, Yong Fan, Hong Liang, Lixuan Li, Zhengbo Zhang, Chien-Hung Yeh
Publikováno v:
IEEE Journal of Translational Engineering in Health and Medicine, Vol 12, Pp 520-532 (2024)
Slow and deep breathing (SDB) is a relaxation technique that can increase vagal activity. Respiratory sinus arrhythmia (RSA) serves as an index of vagal function usually quantified by the high-frequency power of heart rate variability (HRV). However,
Externí odkaz:
https://doaj.org/article/f0b88bb0f5bb45c9a3abe90e51157b86
Autor:
Cinantya Nirmala Dewi, Febty Febriani, Titi Anggono, Syuhada Syuhada, Mohamad Ramdhan, Mohammad Hasib, Aditya Dwi Prasetio, Hendra Suwarta Suprihatin, Suaidi Ahadi, Mohammad Nafian, Suwondo Suwondo, Faiz Muttaqy, Muhamad Syirojudin, Hasanudin Hasanudin, Indah Marsyam
Publikováno v:
Rudarsko-geološko-naftni Zbornik, Vol 39, Iss 1, Pp 55-64 (2024)
Ultra-low frequency (ULF) geomagnetic analysis is a robust method for earthquake (EQ) forecasting. We conducted a simultaneous study of EQ precursors around the western part of Java Island in 2020 using wavelet transform (WT) and detrended fluctuatio
Externí odkaz:
https://doaj.org/article/192f7b9937264197a37f40007aff8525
Publikováno v:
Applied Sciences, Vol 14, Iss 23, p 10866 (2024)
In this work, a new method for denoising signals is developed that is based on variational mode decomposition (VMD) and a novel metric using detrended fluctuation analysis (DFA). The proposed method first decomposes the signal into band-limited intri
Externí odkaz:
https://doaj.org/article/8fa7cddf0d244c5f8e2d0f7f9326c9df
Publikováno v:
Sensors, Vol 24, Iss 22, p 7252 (2024)
Human locomotion contains innate variability which may provide health insights. Detrended fluctuation analysis (DFA) has been used to quantify the temporal structure of variability for treadmill running, although it has been less commonly applied to
Externí odkaz:
https://doaj.org/article/58df647c5d374136964ca80ae373c2dd
Autor:
Frigyes Samuel Racz, Satyam Kumar, Zalan Kaposzta, Hussein Alawieh, Deland Hu Liu, Ruofan Liu, Akos Czoch, Peter Mukli, José del R. Millán
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
Riemannian geometry-based classification (RGBC) gained popularity in the field of brain-computer interfaces (BCIs) lately, due to its ability to deal with non-stationarities arising in electroencephalography (EEG) data. Domain adaptation, however, is
Externí odkaz:
https://doaj.org/article/a075b55974134bd19bca5fcfd8cfe536