Zobrazeno 1 - 10
of 839
pro vyhledávání: '"lung sound"'
Autor:
Hiroyuki Mochizuki, Kota Hirai, Hiroyuki Furuya, Fumio Niimura, Kenta Suzuki, Tsuyoshi Okino, Miki Ikeda, Hironori Noto
Publikováno v:
BMC Pulmonary Medicine, Vol 24, Iss 1, Pp 1-10 (2024)
Abstract Background Lung sound analysis parameters have been reported to be useful biomarkers for evaluating airway condition. We developed an automatic lung sound analysis software program for infants and children based on lung sound spectral curves
Externí odkaz:
https://doaj.org/article/ba83b7be28794ff38967112f2abf8853
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 36, Iss 8, Pp 102200- (2024)
Lung auscultation is essential for early lung condition detection. Categorizing adventitious lung sounds requires expert discrimination by medical specialists. This paper details the features of LungNeXt, a novel classification model specifically des
Externí odkaz:
https://doaj.org/article/7d98aeab27ff4b39a112013d9184116b
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2024, Iss 1, Pp 1-17 (2024)
Abstract Auscultation is the most effective method for diagnosing cardiovascular and respiratory diseases. However, stethoscopes typically capture mixed signals of heart and lung sounds, which can affect the auscultation effect of doctors. Therefore,
Externí odkaz:
https://doaj.org/article/b029a2c856174dd19229caaed9a06f7e
Autor:
Eline Lauwers, Toon Stas, Ian McLane, Annemiek Snoeckx, Kim Van Hoorenbeeck, Wilfried De Backer, Kris Ides, Jan Steckel, Stijn Verhulst
Publikováno v:
Respiratory Research, Vol 25, Iss 1, Pp 1-9 (2024)
Abstract Background Computer Aided Lung Sound Analysis (CALSA) aims to overcome limitations associated with standard lung auscultation by removing the subjective component and allowing quantification of sound characteristics. In this proof-of-concept
Externí odkaz:
https://doaj.org/article/2f7d3e38801c48769953849d98770b6a
Publikováno v:
IEEE Access, Vol 12, Pp 147301-147309 (2024)
Automated analysis of lung sounds is a non-invasive technique that has the potential to become a powerful tool for the detection of respiratory illnesses. In this paper, we propose a machine learning method tasked to predict the number of respiratory
Externí odkaz:
https://doaj.org/article/2c75d330670741f5bc176d3146ad0f3e
Publikováno v:
IEEE Access, Vol 12, Pp 87691-87700 (2024)
Identifying lung sound signal patterns is essential for detecting and monitoring respiratory diseases. Existing approaches for analyzing respiratory sounds need domain specialists. Therefore, an accurate and automated lung sound classification tool i
Externí odkaz:
https://doaj.org/article/773a39a95969487780343ad7833d62be
Autor:
Yang Yi Poh, Ethan Grooby, Kenneth Tan, Lindsay Zhou, Arrabella King, Ashwin Ramanathan, Atul Malhotra, Mehrtash Harandi, Faezeh Marzbanrad
Publikováno v:
IEEE Open Journal of Engineering in Medicine and Biology, Vol 5, Pp 345-352 (2024)
Goal: Auscultation for neonates is a simple and non-invasive method of diagnosing cardiovascular and respiratory disease. However, obtaining high-quality chest sounds containing only heart or lung sounds is non-trivial. Hence, this study introduces a
Externí odkaz:
https://doaj.org/article/68eb0d8fbb184e2383757b7c1580dc27
Publikováno v:
IEEE Access, Vol 12, Pp 73079-73094 (2024)
Lung sound classification is an important diagnostic task in the medical field. By analyzing respiratory sounds, doctors can help diagnose various respiratory system diseases. Chronic respiratory diseases worldwide are usually associated with abnorma
Externí odkaz:
https://doaj.org/article/f80110051e7b4f3aa70b5348674d2a05
Autor:
Syed Waqad Ali, Muhammad Munaf Rashid, Muhammad Uzair Yousuf, Sarmad Shams, Muhammad Asif, Muhammad Rehan, Ikram Din Ujjan
Publikováno v:
Sensors, Vol 24, Iss 21, p 6887 (2024)
Respiratory disorders are commonly regarded as complex disorders to diagnose due to their multi-factorial nature, encompassing the interplay between hereditary variables, comorbidities, environmental exposures, and therapies, among other contributing
Externí odkaz:
https://doaj.org/article/440e921d2db54017b37e3e6a325b9374
Autor:
Takashi Sakama, Mami Ichinose, Takeru Obara, Mayuko Shibata, Takanori Kagawa, Hiromitsu Takakura, Kota Hirai, Hiroyuki Furuya, Masahiko Kato, Hiroyuki Mochizuki
Publikováno v:
Allergology International, Vol 72, Iss 4, Pp 545-550 (2023)
Background: In children with asthma, there are many cases in which wheeze is confirmed by auscultation with a normal lung function, or in which the lung function is decreased without wheeze. Using an objective lung sound analysis, we examined the eff
Externí odkaz:
https://doaj.org/article/984b6a37c7f54ab1a4d8bce1c277a1d0