A Paradigm Shift in the Treatment of Sleep Apnea
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Respiratory
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Researchers from University of Pittsburgh have developed a device designed to collect exhaled respiratory aerosols from mechanically ventilated patients. This device is designed to be non-invasive, highly efficient and can be readily placed in the exhalation line of ventilators without interfering in the functions of the ventilator. However, endotracheal aspirate by contaminated by upper airway secretions The collection of BAL is less prone to contamination, but it is invasive and unable to be repeated frequently.
Previous work led to software development and a working prototype to determine the CSA of the airways. University of Pittsburgh researchers have developed system techniques integrating artificial intelligence (AI) and smartphone sensing, namely PTEase, that can be used as a pulmonary telemedicine device by patients to accurately evaluate pulmonary disease conditions and provide clinically relevant information out of clinic. Using only a commercial smartphone and a 3D-printed attachment with this novel multi-task machine learning (ML) model, it is possible to assess airway measurements from PTEase, extract appropriate biomarkers and determine key clinical information including the probability of disease and lung function indices.
The present invention relates to systems and methods for pulmonary function testing, and, in particular, to systems and methods for estimating lung function, calculating airway mechanics and/or detecting airway obstructions using an electronic apparatus, such as a smartphone or similar device. The present invention relates to systems and methods for pulmonary function testing, and, in particular, to systems and methods for estimating lung function, calculating airway mechanics and/or detecting airway obstructions using an electronic apparatus, such as a smartphone or similar device.
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