Respiratory Monitor For Asthma And Other Pulmonary Conditions
- 技術優勢
- Features -Continuous monitoring of pulmonary function -Minimally invasive -Low cost -Automatic machine learning algorithm for predictive and preventative diagnosis of asthma attacks Benefits -Improve the quality of life for those with respiratory complications such as asthma or COPD -Large data sets that could be used to potentially draw correlation between different vitals signs and disease progression.
- 技術應用
- Continuous health monitoring, specifically pulmonary functionPreventing and predicting asthma attacks
- 詳細技術說明
- Asthma causes 250,000 fatal attacks annually world-wide that can be easily prevented with the proper monitoring of lung function. By measuring decreased lung function prior to an asthma attack one could request medical attention if needed to prevent a fatality. Current devices such as a peak flow meter could be used as a point of care diagnostic to assess lung function but are not an ideal solution. Peak flow meters provide highly variable, discrete measurements that are often challenging to obtain from young children. There exists a clinical unmet need for a device that can minimally invasively and continuously monitor pulmonary output. A novel fabrication method and patch sensor device have been developed to address the shortcomings of the standard of care. Shape memory plastics capable of shrinking by 2000% have been used to create robust highly wrinkled metal thin film structures. These wrinkled metal thin films are then mounted onto flexible single use biocompatible plastics that allow them to be used on the human body to determine chest wall expansion via strain measurements. Strain measurements can then be converted to lung flow volumes through a simple device calibration. Said devices can then continuously monitor and analyze pulmonary function via a paired mobile device machine learning platform to predict and prevent fatal asthma attacks from occurring.
- *Abstract
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A patch sensor that is able to continuously monitor breathing rate and volume to diagnose pulmonary function and possibly predict and possibly prevent fatal asthma attacks.
- *Principal Investigation
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Name: Michelle Khine
Department:
Name: Francis Duhay
Department:
Name: Eugene Lee
Department:
Name: Jonathan Pegan
Department:
- 其他
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State Of Development
- Sensors have been developed and tested to track respiration.
- Strain measurements have been correlated to spirometry for calibration
- Machine learning algorithm has been developed
- iPhone crowd sourced app has to be developed
Related Materials
Highly Flexible Wrinkled Carbon Nanotube Thin Film Strain Sensor to Monitor Human Movement.
Related Technologies
Tech ID/UC Case
28930/2017-208-0
Related Cases
2017-208-0, 2014-922-0, 2016-463-0
- 國家/地區
- 美國
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