Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Xinqi Bao"'
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
Autor:
Xinqi Bao, Yujia Xu, Hak-Keung Lam, Mohamed Trabelsi, Ines Chihi, Lilia Sidhom, Ernest N. Kamavuako
Publikováno v:
Biomedical Engineering Advances, Vol 5, Iss , Pp 100093- (2023)
Time-Frequency Distributions (TFDs) support the heart sound characterisation and classification in early cardiac screening. However, despite the frequent use of TFDs in signal analysis, no comprehensive study has been conducted to compare their perfo
Externí odkaz:
https://doaj.org/article/efa68b70667640df9c3e75830068851b
Publikováno v:
Sensors, Vol 22, Iss 24, p 9849 (2022)
A pattern-recognition (PR)-based myoelectric control system is the trend of future prostheses development. Compared with conventional prosthetic control systems, PR-based control systems provide high dexterity, with many studies achieving >95% accura
Externí odkaz:
https://doaj.org/article/68ee3f6493494d9497e3c222b2ab4373
Publikováno v:
Sensors, Vol 22, Iss 6, p 2261 (2022)
Deep learning techniques are the future trend for designing heart sound classification methods, making conventional heart sound segmentation dispensable. However, despite using fixed signal duration for training, no study has assessed its effect on t
Externí odkaz:
https://doaj.org/article/4115b46dffea4b498b41369385d3c483
Publikováno v:
Sensors, Vol 21, Iss 15, p 5245 (2021)
Commercial myoelectric prostheses are costly to purchase and maintain, making their provision challenging for developing countries. Recent research indicates that embroidered EMG electrodes may provide a more affordable alternative to the sensors use
Externí odkaz:
https://doaj.org/article/5c1bfcbe9f974436a9011ef131a1aaf7
Publikováno v:
Sensors, Vol 21, Iss 1, p 78 (2020)
The respiratory rate (RR) is a vital physiological parameter in prediagnosis and daily monitoring. It can be obtained indirectly from Electrocardiogram (ECG) signals using ECG-derived respiration (EDR) techniques. As part of the study in designing an
Externí odkaz:
https://doaj.org/article/d8d5f1a3e2a348508955c8bcac52a542
Publikováno v:
Aging Pathobiology and Therapeutics. 2:64-72
Colorectal cancer (CRC) is among the top three cancers worldwide in terms of incidence and associated mortality. Colorectal cancer (CRC) is responsible for more than 880,000 deaths annually. The number of of CRC cases worldwide continues to increase,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e61ab9b859f83f6b845cc6a19391c408
https://doi.org/10.31491/apt.2020.06.016
https://doi.org/10.31491/apt.2020.06.016
Publikováno v:
Bao, X, Xu, Y & Kamavuako, E 2022, ' The Effect of Signal Duration on the Classification of Heart Sounds : A Deep Learning Approach ', SENSORS, vol. 22, no. 6, 2261 . https://doi.org/10.3390/s22062261
Sensors; Volume 22; Issue 6; Pages: 2261
Sensors; Volume 22; Issue 6; Pages: 2261
Deep learning techniques are the future trend for designing heart sound classification methods, making conventional heart sound segmentation dispensable. However, despite using fixed signal duration for training, no study has assessed its effect on t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e6b441e1acd6ede4ee9741dae199a92c
https://kclpure.kcl.ac.uk/ws/files/170227682/The_Effect_of_Signal_BAO_Published_online_15_Mar_22_Gold_VoR_CC_BY_.pdf
https://kclpure.kcl.ac.uk/ws/files/170227682/The_Effect_of_Signal_BAO_Published_online_15_Mar_22_Gold_VoR_CC_BY_.pdf
Publikováno v:
Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cfacff486f31453d94465cd7ef9de0b7
https://doi.org/10.5220/0010987300003123
https://doi.org/10.5220/0010987300003123