Tidal Volume Estimation Using the Blanket Fractal Dimension of the Tracheal Sounds Acquired by Smartphone
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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-04-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/15/5/9773 |
| _version_ | 1798004003526672384 |
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| author | Natasa Reljin Bersain A. Reyes Ki H. Chon |
| author_facet | Natasa Reljin Bersain A. Reyes Ki H. Chon |
| author_sort | Natasa Reljin |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T12:16:41Z |
| format | Article |
| id | doaj.art-eb98090bd1e048e6a9b2f253b8a22d17 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T12:16:41Z |
| publishDate | 2015-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-eb98090bd1e048e6a9b2f253b8a22d172022-12-22T04:24:18ZengMDPI AGSensors1424-82202015-04-011559773979010.3390/s150509773s150509773Tidal Volume Estimation Using the Blanket Fractal Dimension of the Tracheal Sounds Acquired by SmartphoneNatasa Reljin0Bersain A. Reyes1Ki H. Chon2Department of Biomedical Engineering, University of Connecticut, 260 Glenbrook Road, Storrs, CT 06269, USADepartment of Biomedical Engineering, University of Connecticut, 260 Glenbrook Road, Storrs, CT 06269, USADepartment of Biomedical Engineering, University of Connecticut, 260 Glenbrook Road, Storrs, CT 06269, USAIn 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.http://www.mdpi.com/1424-8220/15/5/9773blanket fractal dimensiontidal volumetracheal soundssmartphone |
| spellingShingle | Natasa Reljin Bersain A. Reyes Ki H. Chon Tidal Volume Estimation Using the Blanket Fractal Dimension of the Tracheal Sounds Acquired by Smartphone Sensors blanket fractal dimension tidal volume tracheal sounds smartphone |
| title | Tidal Volume Estimation Using the Blanket Fractal Dimension of the Tracheal Sounds Acquired by Smartphone |
| title_full | Tidal Volume Estimation Using the Blanket Fractal Dimension of the Tracheal Sounds Acquired by Smartphone |
| title_fullStr | Tidal Volume Estimation Using the Blanket Fractal Dimension of the Tracheal Sounds Acquired by Smartphone |
| title_full_unstemmed | Tidal Volume Estimation Using the Blanket Fractal Dimension of the Tracheal Sounds Acquired by Smartphone |
| title_short | Tidal Volume Estimation Using the Blanket Fractal Dimension of the Tracheal Sounds Acquired by Smartphone |
| title_sort | tidal volume estimation using the blanket fractal dimension of the tracheal sounds acquired by smartphone |
| topic | blanket fractal dimension tidal volume tracheal sounds smartphone |
| url | http://www.mdpi.com/1424-8220/15/5/9773 |
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