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Employing an Incentive Spirometer to Calibrate Tidal Volumes Estimated from a Smartphone Camera
A smartphone-based tidal volume (V(T)) estimator was recently introduced by our research group, where an Android application provides a chest movement signal whose peak-to-peak amplitude is highly correlated with reference V(T) measured by a spirometer. We found a Normalized Root Mean Squared Error...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4813972/ https://www.ncbi.nlm.nih.gov/pubmed/26999152 http://dx.doi.org/10.3390/s16030397 |
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author | Reyes, Bersain A. Reljin, Natasa Kong, Youngsun Nam, Yunyoung Ha, Sangho Chon, Ki H. |
author_facet | Reyes, Bersain A. Reljin, Natasa Kong, Youngsun Nam, Yunyoung Ha, Sangho Chon, Ki H. |
author_sort | Reyes, Bersain A. |
collection | PubMed |
description | A smartphone-based tidal volume (V(T)) estimator was recently introduced by our research group, where an Android application provides a chest movement signal whose peak-to-peak amplitude is highly correlated with reference V(T) measured by a spirometer. We found a Normalized Root Mean Squared Error (NRMSE) of 14.998% ± 5.171% (mean ± SD) when the smartphone measures were calibrated using spirometer data. However, the availability of a spirometer device for calibration is not realistic outside clinical or research environments. In order to be used by the general population on a daily basis, a simple calibration procedure not relying on specialized devices is required. In this study, we propose taking advantage of the linear correlation between smartphone measurements and V(T) to obtain a calibration model using information computed while the subject breathes through a commercially-available incentive spirometer (IS). Experiments were performed on twelve (N = 12) healthy subjects. In addition to corroborating findings from our previous study using a spirometer for calibration, we found that the calibration procedure using an IS resulted in a fixed bias of −0.051 L and a RMSE of 0.189 ± 0.074 L corresponding to 18.559% ± 6.579% when normalized. Although it has a small underestimation and slightly increased error, the proposed calibration procedure using an IS has the advantages of being simple, fast, and affordable. This study supports the feasibility of developing a portable smartphone-based breathing status monitor that provides information about breathing depth, in addition to the more commonly estimated respiratory rate, on a daily basis. |
format | Online Article Text |
id | pubmed-4813972 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-48139722016-04-06 Employing an Incentive Spirometer to Calibrate Tidal Volumes Estimated from a Smartphone Camera Reyes, Bersain A. Reljin, Natasa Kong, Youngsun Nam, Yunyoung Ha, Sangho Chon, Ki H. Sensors (Basel) Article A smartphone-based tidal volume (V(T)) estimator was recently introduced by our research group, where an Android application provides a chest movement signal whose peak-to-peak amplitude is highly correlated with reference V(T) measured by a spirometer. We found a Normalized Root Mean Squared Error (NRMSE) of 14.998% ± 5.171% (mean ± SD) when the smartphone measures were calibrated using spirometer data. However, the availability of a spirometer device for calibration is not realistic outside clinical or research environments. In order to be used by the general population on a daily basis, a simple calibration procedure not relying on specialized devices is required. In this study, we propose taking advantage of the linear correlation between smartphone measurements and V(T) to obtain a calibration model using information computed while the subject breathes through a commercially-available incentive spirometer (IS). Experiments were performed on twelve (N = 12) healthy subjects. In addition to corroborating findings from our previous study using a spirometer for calibration, we found that the calibration procedure using an IS resulted in a fixed bias of −0.051 L and a RMSE of 0.189 ± 0.074 L corresponding to 18.559% ± 6.579% when normalized. Although it has a small underestimation and slightly increased error, the proposed calibration procedure using an IS has the advantages of being simple, fast, and affordable. This study supports the feasibility of developing a portable smartphone-based breathing status monitor that provides information about breathing depth, in addition to the more commonly estimated respiratory rate, on a daily basis. MDPI 2016-03-18 /pmc/articles/PMC4813972/ /pubmed/26999152 http://dx.doi.org/10.3390/s16030397 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Reyes, Bersain A. Reljin, Natasa Kong, Youngsun Nam, Yunyoung Ha, Sangho Chon, Ki H. Employing an Incentive Spirometer to Calibrate Tidal Volumes Estimated from a Smartphone Camera |
title | Employing an Incentive Spirometer to Calibrate Tidal Volumes Estimated from a Smartphone Camera |
title_full | Employing an Incentive Spirometer to Calibrate Tidal Volumes Estimated from a Smartphone Camera |
title_fullStr | Employing an Incentive Spirometer to Calibrate Tidal Volumes Estimated from a Smartphone Camera |
title_full_unstemmed | Employing an Incentive Spirometer to Calibrate Tidal Volumes Estimated from a Smartphone Camera |
title_short | Employing an Incentive Spirometer to Calibrate Tidal Volumes Estimated from a Smartphone Camera |
title_sort | employing an incentive spirometer to calibrate tidal volumes estimated from a smartphone camera |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4813972/ https://www.ncbi.nlm.nih.gov/pubmed/26999152 http://dx.doi.org/10.3390/s16030397 |
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