Deep Learning versus Professional Healthcare Equipment: A Fine-Grained Breathing Rate Monitoring Model
Joint Authors
Gong, Haigang
Dai, Xili
Guo, Zihao
Liu, Nianbo
Liu, Bang
Wang, Xiaomin
Liu, Ming
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-03-01
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Telecommunications Engineering
Abstract EN
In mHealth field, accurate breathing rate monitoring technique has benefited a broad array of healthcare-related applications.
Many approaches try to use smartphone or wearable device with fine-grained monitoring algorithm to accomplish the task, which can only be done by professional medical equipment before.
However, such schemes usually result in bad performance in comparison to professional medical equipment.
In this paper, we propose DeepFilter, a deep learning-based fine-grained breathing rate monitoring algorithm that works on smartphone and achieves professional-level accuracy.
DeepFilter is a bidirectional recurrent neural network (RNN) stacked with convolutional layers and speeded up by batch normalization.
Moreover, we collect 16.17 GB breathing sound recording data of 248 hours from 109 and another 10 volunteers to train and test our model, respectively.
The results show a reasonably good accuracy of breathing rate monitoring.
American Psychological Association (APA)
Liu, Bang& Dai, Xili& Gong, Haigang& Guo, Zihao& Liu, Nianbo& Wang, Xiaomin…[et al.]. 2018. Deep Learning versus Professional Healthcare Equipment: A Fine-Grained Breathing Rate Monitoring Model. Mobile Information Systems،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1204833
Modern Language Association (MLA)
Liu, Bang…[et al.]. Deep Learning versus Professional Healthcare Equipment: A Fine-Grained Breathing Rate Monitoring Model. Mobile Information Systems No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1204833
American Medical Association (AMA)
Liu, Bang& Dai, Xili& Gong, Haigang& Guo, Zihao& Liu, Nianbo& Wang, Xiaomin…[et al.]. Deep Learning versus Professional Healthcare Equipment: A Fine-Grained Breathing Rate Monitoring Model. Mobile Information Systems. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1204833
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1204833