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Tidal volume estimation using the blanket fractal dimension of the tracheal sounds acquired by smartphone.

Reljin N, Reyes BA, Chon KH - Sensors (Basel) (2015)

Bottom Line: The estimated volumes were compared to the true values, obtained with a Respitrace system, which was considered as a reference.The results show that the BFD outperformed the SE (at least twice smaller NRMSE was obtained).In addition, it was shown that the fitting curves calculated during the first day of experiments could be successfully used for at least the five following days.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, University of Connecticut, 260 Glenbrook Road, Storrs, CT 06269, USA. reljin@engr.uconn.edu.

ABSTRACT
In this paper, we propose the use of blanket fractal dimension (BFD) to estimate the tidal volume from smartphone-acquired tracheal sounds. We collected tracheal sounds with a Samsung Galaxy S4 smartphone, from five (N = 5) healthy volunteers. Each volunteer performed the experiment six times; first to obtain linear and exponential fitting models, and then to fit new data onto the existing models. Thus, the total number of recordings was 30. The estimated volumes were compared to the true values, obtained with a Respitrace system, which was considered as a reference. Since Shannon entropy (SE) is frequently used as a feature in tracheal sound analyses, we estimated the tidal volume from the same sounds by using SE as well. The evaluation of the performed estimation, using BFD and SE methods, was quantified by the normalized root-mean-squared error (NRMSE). The results show that the BFD outperformed the SE (at least twice smaller NRMSE was obtained). The smallest NRMSE error of 15.877% ± 9.246% (mean ± standard deviation) was obtained with the BFD and exponential model. In addition, it was shown that the fitting curves calculated during the first day of experiments could be successfully used for at least the five following days.

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An example of the volume estimation from smartphone acquired tracheal sounds using BFD features and exponential model of one subject. The true volumes while breathing through a tube (green circles) are limited to a range from 0.2 to 1 L. (a) The inspiration phase; (b) The expiration phase.
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sensors-15-09773-f005: An example of the volume estimation from smartphone acquired tracheal sounds using BFD features and exponential model of one subject. The true volumes while breathing through a tube (green circles) are limited to a range from 0.2 to 1 L. (a) The inspiration phase; (b) The expiration phase.

Mentions: An example of the volume estimation from smartphone acquired tracheal sounds using BFD features and exponential model, for both inspiration and expiration, of one subject is shown in Figure 5. The true tidal volume values (from Respitrace system) and their corresponding BFD values when breathing through 800 mL bag and tube are represented in blue squares and green circles, respectively, while the estimated volumes and their corresponding BFD features are depicted as brown triangles. The three points, shown as black marks in Figure 5 and given with Equation (9), are used for obtaining the exponential fitting curve, which is shown as a solid red curve.


Tidal volume estimation using the blanket fractal dimension of the tracheal sounds acquired by smartphone.

Reljin N, Reyes BA, Chon KH - Sensors (Basel) (2015)

An example of the volume estimation from smartphone acquired tracheal sounds using BFD features and exponential model of one subject. The true volumes while breathing through a tube (green circles) are limited to a range from 0.2 to 1 L. (a) The inspiration phase; (b) The expiration phase.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4481932&req=5

sensors-15-09773-f005: An example of the volume estimation from smartphone acquired tracheal sounds using BFD features and exponential model of one subject. The true volumes while breathing through a tube (green circles) are limited to a range from 0.2 to 1 L. (a) The inspiration phase; (b) The expiration phase.
Mentions: An example of the volume estimation from smartphone acquired tracheal sounds using BFD features and exponential model, for both inspiration and expiration, of one subject is shown in Figure 5. The true tidal volume values (from Respitrace system) and their corresponding BFD values when breathing through 800 mL bag and tube are represented in blue squares and green circles, respectively, while the estimated volumes and their corresponding BFD features are depicted as brown triangles. The three points, shown as black marks in Figure 5 and given with Equation (9), are used for obtaining the exponential fitting curve, which is shown as a solid red curve.

Bottom Line: The estimated volumes were compared to the true values, obtained with a Respitrace system, which was considered as a reference.The results show that the BFD outperformed the SE (at least twice smaller NRMSE was obtained).In addition, it was shown that the fitting curves calculated during the first day of experiments could be successfully used for at least the five following days.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, University of Connecticut, 260 Glenbrook Road, Storrs, CT 06269, USA. reljin@engr.uconn.edu.

ABSTRACT
In this paper, we propose the use of blanket fractal dimension (BFD) to estimate the tidal volume from smartphone-acquired tracheal sounds. We collected tracheal sounds with a Samsung Galaxy S4 smartphone, from five (N = 5) healthy volunteers. Each volunteer performed the experiment six times; first to obtain linear and exponential fitting models, and then to fit new data onto the existing models. Thus, the total number of recordings was 30. The estimated volumes were compared to the true values, obtained with a Respitrace system, which was considered as a reference. Since Shannon entropy (SE) is frequently used as a feature in tracheal sound analyses, we estimated the tidal volume from the same sounds by using SE as well. The evaluation of the performed estimation, using BFD and SE methods, was quantified by the normalized root-mean-squared error (NRMSE). The results show that the BFD outperformed the SE (at least twice smaller NRMSE was obtained). The smallest NRMSE error of 15.877% ± 9.246% (mean ± standard deviation) was obtained with the BFD and exponential model. In addition, it was shown that the fitting curves calculated during the first day of experiments could be successfully used for at least the five following days.

Show MeSH