Feasibility analysis of the fusion of pressure sensors and audio measurements for respiratory evaluations

Author:

Cohen-McFarlane Madison1,Wallace Bruce2,Xi Pengcheng3,Goubran Rafik4,Knoefel Frank5

Affiliation:

1. Carleton University,Systems and Computer Engineering,Ottawa,ON,Canada

2. Systems and Computer Engineering, Carleton University, Bruyere Research Institute, SAM3 Innovation Hub,Ottawa,ON,Canada

3. Digital Technologies Research Centre, National Research Council Canada,Ottawa,ON,Canada

4. Systems and Computer Engineering, Carleton University, Bruyere Research Institute,Ottawa,ON,Canada

5. Systems and Computer Engineering, Carleton University, Bruyere Research Institute, University of Ottawa,Faculty of Medicine,Ottawa,ON,Canada

Publisher

IEEE

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Decision Fusion in Automated Sleep Apnea Classification Using Multple Polysomnography Sensors and Convolutional Neural Networks;2023 IEEE Sensors Applications Symposium (SAS);2023-07-18

2. Data Augmentation using Reverb and Noise in Deep Learning Implementation of Cough Classification;2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA);2023-06-14

3. Assessing Driver Engagement Through Machine Learning Classification of Physiological Measures;2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA);2023-06-14

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