Affiliation:
1. Center on Nanoenergy Research School of Physical Science and Technology Guangxi University Nanning 530004 China
2. Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences Beijing 101400 China
3. School of Nanoscience and Technology University of Chinese Academy of Sciences Beijing 100049 China
4. School of Life Science Institute of Engineering Medicine Beijing Institute of Technology Beijing 100081 China
5. Key Laboratory of Biomechanics and Mechanobiology Ministry of Education Beijing Advanced Innovation Center for Biomedical Engineering School of Biological Science and Medical Engineering School of Engineering Medicine Beihang University Beijing 100191 China
Abstract
AbstractCoronavirus disease 2019 (COVID‐19) patients may experience persistent impairment of the lungs after recovery and discharge, which can cause a decline in pulmonary function. Therefore, regular pulmonary function tests are essential for COVID‐19 recovered patients, and portable, home‐based pulmonary function test devices are of great significance during the pandemic. Herein, a portable self‐powered turbine spirometer (PSTS) is designed for respiratory flow measurement and assessment of pulmonary function with high accuracy, humidity resistance, good durability, and low cost. The respiratory airflow can directly drive PSTS to produce a sinusoidal signal with a signal‐to‐noise of 40.64 dB. By utilizing the long short‐term memory (LSTM) model, the flow is successfully predicted, and the “lag‐before‐start” and “spin‐after‐stop” defects of the turbine spirometer are eliminated effectively. For pulmonary function tests, the flow‐volume loop curve can be obtained from PSTS, and pulmonary function parameters such as inspiratory capacity (IC), forced vital capacity (FVC) and forced expiratory volume in the first 1 s (FEV1) can be calculated. The accuracy of IC is over 95%, and others can reach over 97%. A portable smart pulmonary function assessment system is further developed and used to test the pulmonary function of COVID‐19 patients one month after symptom onset, demonstrating potential for assessing rehabilitation trends and long‐term follow‐up of COVID‐19 recovered patients.
Funder
National Natural Science Foundation of China
Natural Science Foundation of Beijing Municipality
Fundamental Research Funds for the Central Universities
National Postdoctoral Program for Innovative Talents
China Postdoctoral Science Foundation
Subject
Industrial and Manufacturing Engineering,Mechanics of Materials,General Materials Science
Cited by
4 articles.
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