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Sensors 2016, 16(8), 1305; doi:10.3390/s16081305

High-Resolution Time-Frequency Spectrum-Based Lung Function Test from a Smartphone Microphone

1
Department of Biomedical Engineering, Wonkwang University School of Medicine, 460 Iksandeaero, Iksan, Jeonbuk 570-749, Korea
2
Imaging Science based Lung and Bone Disease Research Center, Wonkwang University, 460 Iksandeaero, Iksan, Jeonbuk 570-749, Korea
3
Department of Internal Medicine, Wonkwang University School of Medicine, 460 Iksandeaero, Iksan, Jeonbuk 570-749, Korea
4
Department of Radiology, Wonkwang University School of Medicine, 460 Iksandeaero, Iksan, Jeonbuk 570-749, Korea
*
Authors to whom correspondence should be addressed.
Academic Editor: Ki H. Chon
Received: 29 April 2016 / Revised: 3 August 2016 / Accepted: 10 August 2016 / Published: 17 August 2016
(This article belongs to the Special Issue Smartphone-Based Sensors for Non-Invasive Physiological Monitoring)
View Full-Text   |   Download PDF [2249 KB, uploaded 17 August 2016]   |  

Abstract

In this paper, a smartphone-based lung function test, developed to estimate lung function parameters using a high-resolution time-frequency spectrum from a smartphone built-in microphone is presented. A method of estimation of the forced expiratory volume in 1 s divided by forced vital capacity (FEV1/FVC) based on the variable frequency complex demodulation method (VFCDM) is first proposed. We evaluated our proposed method on 26 subjects, including 13 healthy subjects and 13 chronic obstructive pulmonary disease (COPD) patients, by comparing with the parameters clinically obtained from pulmonary function tests (PFTs). For the healthy subjects, we found that an absolute error (AE) and a root mean squared error (RMSE) of the FEV1/FVC ratio were 4.49% ± 3.38% and 5.54%, respectively. For the COPD patients, we found that AE and RMSE from COPD patients were 10.30% ± 10.59% and 14.48%, respectively. For both groups, we compared the results using the continuous wavelet transform (CWT) and short-time Fourier transform (STFT), and found that VFCDM was superior to CWT and STFT. Further, to estimate other parameters, including forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), and peak expiratory flow (PEF), regression analysis was conducted to establish a linear transformation. However, the parameters FVC, FEV1, and PEF had correlation factor r values of 0.323, 0.275, and −0.257, respectively, while FEV1/FVC had an r value of 0.814. The results obtained suggest that only the FEV1/FVC ratio can be accurately estimated from a smartphone built-in microphone. The other parameters, including FVC, FEV1, and PEF, were subjective and dependent on the subject’s familiarization with the test and performance of forced exhalation toward the microphone. View Full-Text
Keywords: smartphone microphone; pulmonary function test; FEV1/FVC; COPD; high-resolution time-frequency smartphone microphone; pulmonary function test; FEV1/FVC; COPD; high-resolution time-frequency
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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. (CC BY 4.0).

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MDPI and ACS Style

Thap, T.; Chung, H.; Jeong, C.; Hwang, K.-E.; Kim, H.-R.; Yoon, K.-H.; Lee, J. High-Resolution Time-Frequency Spectrum-Based Lung Function Test from a Smartphone Microphone. Sensors 2016, 16, 1305.

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