e-learning
resources
Berlin 2001
Tuesday 25.09.2001
Inflammation markers and other respiratory measurements
Login
Search all ERS
e-learning
resources
Disease Areas
Airways Diseases
Interstitial Lung Diseases
Respiratory Critical Care
Respiratory Infections
Paediatric Respiratory Diseases
Pulmonary Vascular Diseases
Sleep and Breathing Disorders
Thoracic Oncology
Events
International Congress
Courses
Webinars
Conferences
Research Seminars
Journal Clubs
Publications
Breathe
Monograph
ERJ
ERJ Open Research
ERR
European Lung White Book
Handbook Series
Guidelines
All ERS guidelines
e-learning
CME Online
Case reports
Short Videos
SpirXpert
Procedure Videos
CME tests
Reference Database of Respiratory Sounds
Radiology Image Challenge
Brief tobacco interventions
EU Projects
VALUE-Dx
ERN-LUNG
ECRAID
UNITE4TB
Disease Areas
Events
Publications
Guidelines
e-learning
EU Projects
Login
Search
The wavelet transformation for the detection of pathological lung sounds
V. Gross, T. Penzel, U. Koehler, P. von Wichert, C. Vogelmeier (Marburg, Germany)
Source:
Annual Congress 2001 - Inflammation markers and other respiratory measurements
Session:
Inflammation markers and other respiratory measurements
Session type:
Thematic Poster Session
Number:
3079
Rating:
You must
login
to grade this presentation.
Share or cite this content
Citations should be made in the following way:
V. Gross, T. Penzel, U. Koehler, P. von Wichert, C. Vogelmeier (Marburg, Germany). The wavelet transformation for the detection of pathological lung sounds. Eur Respir J 2001; 16: Suppl. 31, 3079
You must
login
to share this Presentation/Article on Twitter, Facebook, LinkedIn or by email.
Member's Comments
No comment yet.
You must
Login
to comment this presentation.
Related content which might interest you:
Management of severe community acquired pneumonia – ERS guidelines
Predictive indexes in prolonged weaning of mechanical ventilation due to tracheostomy in patients with COVID-19 pneumonia
Middle-long term pulmonary abnormalities after severe COVID-19 pneumonia which required invasive ventilation
Related content which might interest you:
Efficient extraction of fine/coarse crackles and squawks from lung sound recordings using wavelet packets and higher-order statistics
Source: Eur Respir J 2002; 20: Suppl. 38, 33s
Year: 2002
On efficiently detecting fine/coarse crackles and squawks in lung sound recordings by means of fractal dimension
Source: Eur Respir J 2002; 20: Suppl. 38, 33s
Year: 2002
The use of computer aided lung sound analysis to characterise lung sounds in a healthy population
Source: Annual Congress 2009 - Respiratory physiotherapy assessment
Year: 2009
Application of the percussion signal shape for pulmonary pathologies detection
Source: Eur Respir J 2005; 26: Suppl. 49, 259s
Year: 2005
On efficiently categorising fine and coarse crackles using continuous wavelet transform
Source: Eur Respir J 2004; 24: Suppl. 48, 123s
Year: 2004
Power spectral analysis of lung sound in patients with emphysema and in normal subjects
Source: Eur Respir J 2001; 18: Suppl. 33, 461s
Year: 2001
Diagnostic accuracy of COPD severity grading using machine learning features and lung sounds.
Source: International Congress 2019 – Innovations in primary care assessment and management
Year: 2019
Inter-reader variation in lung segmentation of functional lung MRI quantification.
Source: International Congress 2019 – Physiology of cystic fibrosis
Year: 2019
Diagnostic accuracy of asthma severity grading using machine learning features and lung sounds
Source: International Congress 2018 – Innovations in equipment and their application
Year: 2018
Automatic wheezing-episode detector using spectrogram analysis of breath sounds
Source: Eur Respir J 2003; 22: Suppl. 45, 446s
Year: 2003
Fine crackles quantitative value can help the diagnosis of interstitial lung diseases – Clinical utility of the innovative analyzing system of respiratory sounds
Source: International Congress 2019 – Innovations in primary care assessment and management
Year: 2019
Possibilities of neural networks in the X-ray detection of lung pathology and diagnosis of pneumonia
Source: Virtual Congress 2020 – New imaging techniques applied to old problems
Year: 2020
Lung sounds in patients with asbestos-associated pleural fibrosis, asbestosis or other lung fibrosis, objectified with
vibration response imaging
Source: Annual Congress 2008 - Inorganic dust exposure and the lung
Year: 2008
Spectral bronchoscopy for evaluation of tissue vascular properties in lung cancer
Source: Annual Congress 2007 - Interventional bronchoscopy
Year: 2007
Detection of breath-synchronous variation of lung sound phase and amplitude at neighboring sites
Source: Eur Respir J 2001; 18: Suppl. 33, 259s
Year: 2001
Improving lung cancer diagnosis from exhaled-breath analysis by adding clinical parameters to the artificial neural network
Source: International Congress 2019 – Diagnostic procedures and biology of lung cancer
Year: 2019
One lung ventilation: use of the impulse oscillation system to assess lung function in an animal model
Source: Annual Congress 2008 - Assessment of the respiratory system
Year: 2008
Crackle sound analysis in a porcine ARDS model to create a non-invasive recruitment monitoring
Source: Annual Congress 2008 - Pathophysiology of acute lung injury
Year: 2008
Towards the standardisation of lung sound nomenclature
Source: Eur Respir J 2016; 47: 724-732
Year: 2016
We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. By clicking "Accept", you consent to the use of the cookies.
Accept