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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | University of Wisconsin-Madison |
| Country | United States |
| Start Date | Apr 01, 2021 |
| End Date | Sep 30, 2022 |
| Duration | 547 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2111429 |
The broader impact/commercial potential of this I-corps project is to address the gap in real-time recognition and quantification of respiratory airflow through a novel device with real-time feedback capabilities. Current monitors are not capable of providing quantitative and reproducible respiration assessment causing health care providers to rely on their subjective and biased experience and expertise.
Even though clinical end-users and health care systems operate at highly informed levels, there are still major healthcare disparities in quality of care across all specialties and health care industries. The proposed technology provides a quantifiable monitoring tool to removing bias and subjective assessments and make respiration assessment more reproducible across all levels of health care workers (with varying levels of training and expertise).
This I-Corps project is focused on developing a wearable, wireless respiratory monitor for measuring parameters related directly to airflow and other metrics of respiration. This technology may allow early notification and initiation of corrective and resuscitative measurements. The proposed approach uses ultrasound waves and machine learning methods to quantify respiratory flow through the neck tissue overcoming monitoring limitations of other technologies.
When respiratory distress/obstruction happens during sedation, it occurs suddenly and to the untrained eye, the patient appears unchanged, as though they are asleep. Current monitors do not directly measure airflow as a function of respiration instead, they monitor the downstream effects of blocked airflow (such as decrease in oxygen), resulting in delayed response times.
Adverse outcomes are more likely to occur when there is a significant delay between the development and the detection of respiratory depression/obstruction in sedated patients. Thus, the proposed technology may fill this critical need for a respiratory monitoring method that provides real time, quantitative feedback about airflow changes to allow for early recognition of respiratory depression, airway obstruction, and respiratory failure.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
University of Wisconsin-Madison
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