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Sensors 2018, 18(11), 3810; https://doi.org/10.3390/s18113810

A Mobile Cough Strength Evaluation Device Using Cough Sounds

1
Department of System Cybernetics, Institute of Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8527, Japan
2
Department of Rehabilitation, Faculty of Health Sciences, Hiroshima Cosmopolitan University, Hiroshima 731-3166, Japan
3
Division of Physical Analysis and Therapeutic Sciences, Institute of Biomedical and Health Sciences, Hiroshima University, Hiroshima 734-8553, Japan
4
Division of Rehabilitation, Department of Clinical Support, Hiroshima University Hospital, Hiroshima 734-8551, Japan
*
Authors to whom correspondence should be addressed.
Received: 11 October 2018 / Revised: 31 October 2018 / Accepted: 5 November 2018 / Published: 7 November 2018
(This article belongs to the Special Issue Wearable Sensors and Devices for Healthcare Applications)
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Abstract

Although cough peak flow (CPF) is an important measurement for evaluating the risk of cough dysfunction, some patients cannot use conventional measurement instruments, such as spirometers, because of the configurational burden of the instruments. Therefore, we previously developed a cough strength estimation method using cough sounds based on a simple acoustic and aerodynamic model. However, the previous model did not consider age or have a user interface for practical application. This study clarifies the cough strength prediction accuracy using an improved model in young and elderly participants. Additionally, a user interface for mobile devices was developed to record cough sounds and estimate cough strength using the proposed method. We then performed experiments on 33 young participants (21.3 ± 0.4 years) and 25 elderly participants (80.4 ± 6.1 years) to test the effect of age on the CPF estimation accuracy. The percentage error between the measured and estimated CPFs was approximately 6.19%. In addition, among the elderly participants, the current model improved the estimation accuracy of the previous model by a percentage error of approximately 6.5% (p < 0.001). Furthermore, Bland-Altman analysis demonstrated no systematic error between the measured and estimated CPFs. These results suggest that the developed device can be applied for daily CPF measurements in clinical practice. View Full-Text
Keywords: cough strength; cough sound; cough peak flow; mobile device; iOS cough strength; cough sound; cough peak flow; mobile device; iOS
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Umayahara, Y.; Soh, Z.; Sekikawa, K.; Kawae, T.; Otsuka, A.; Tsuji, T. A Mobile Cough Strength Evaluation Device Using Cough Sounds. Sensors 2018, 18, 3810.

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