Cargando…
Single-Frequency Ultrasound-Based Respiration Rate Estimation with Smartphones
Respiration monitoring is helpful in disease prevention and diagnosis. Traditional respiration monitoring requires users to wear devices on their bodies, which is inconvenient for them. In this paper, we aim to design a noncontact respiration rate detection system utilizing off-the-shelf smartphones...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5960545/ https://www.ncbi.nlm.nih.gov/pubmed/29853985 http://dx.doi.org/10.1155/2018/3675974 |
_version_ | 1783324602577977344 |
---|---|
author | Ge, Linfei Zhang, Jin Wei, Jing |
author_facet | Ge, Linfei Zhang, Jin Wei, Jing |
author_sort | Ge, Linfei |
collection | PubMed |
description | Respiration monitoring is helpful in disease prevention and diagnosis. Traditional respiration monitoring requires users to wear devices on their bodies, which is inconvenient for them. In this paper, we aim to design a noncontact respiration rate detection system utilizing off-the-shelf smartphones. We utilize the single-frequency ultrasound as the media to detect the respiration activity. By analyzing the ultrasound signals received by the built-in microphone sensor in a smartphone, our system can derive the respiration rate of the user. The advantage of our method is that the transmitted signal is easy to generate and the signal analysis is simple, which has lower power consumption and thus is suitable for long-term monitoring in daily life. The experimental result shows that our system can achieve accurate respiration rate estimation under various scenarios. |
format | Online Article Text |
id | pubmed-5960545 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-59605452018-05-31 Single-Frequency Ultrasound-Based Respiration Rate Estimation with Smartphones Ge, Linfei Zhang, Jin Wei, Jing Comput Math Methods Med Research Article Respiration monitoring is helpful in disease prevention and diagnosis. Traditional respiration monitoring requires users to wear devices on their bodies, which is inconvenient for them. In this paper, we aim to design a noncontact respiration rate detection system utilizing off-the-shelf smartphones. We utilize the single-frequency ultrasound as the media to detect the respiration activity. By analyzing the ultrasound signals received by the built-in microphone sensor in a smartphone, our system can derive the respiration rate of the user. The advantage of our method is that the transmitted signal is easy to generate and the signal analysis is simple, which has lower power consumption and thus is suitable for long-term monitoring in daily life. The experimental result shows that our system can achieve accurate respiration rate estimation under various scenarios. Hindawi 2018-05-06 /pmc/articles/PMC5960545/ /pubmed/29853985 http://dx.doi.org/10.1155/2018/3675974 Text en Copyright © 2018 Linfei Ge et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Ge, Linfei Zhang, Jin Wei, Jing Single-Frequency Ultrasound-Based Respiration Rate Estimation with Smartphones |
title | Single-Frequency Ultrasound-Based Respiration Rate Estimation with Smartphones |
title_full | Single-Frequency Ultrasound-Based Respiration Rate Estimation with Smartphones |
title_fullStr | Single-Frequency Ultrasound-Based Respiration Rate Estimation with Smartphones |
title_full_unstemmed | Single-Frequency Ultrasound-Based Respiration Rate Estimation with Smartphones |
title_short | Single-Frequency Ultrasound-Based Respiration Rate Estimation with Smartphones |
title_sort | single-frequency ultrasound-based respiration rate estimation with smartphones |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5960545/ https://www.ncbi.nlm.nih.gov/pubmed/29853985 http://dx.doi.org/10.1155/2018/3675974 |
work_keys_str_mv | AT gelinfei singlefrequencyultrasoundbasedrespirationrateestimationwithsmartphones AT zhangjin singlefrequencyultrasoundbasedrespirationrateestimationwithsmartphones AT weijing singlefrequencyultrasoundbasedrespirationrateestimationwithsmartphones |