Next Article in Journal
Design and Development of a 5-Channel Arduino-Based Data Acquisition System (ABDAS) for Experimental Aerodynamics Research
Next Article in Special Issue
Feature Representation and Data Augmentation for Human Activity Classification Based on Wearable IMU Sensor Data Using a Deep LSTM Neural Network
Previous Article in Journal
A Portable Quantum Cascade Laser Spectrometer for Atmospheric Measurements of Carbon Monoxide

Estimation of Cough Peak Flow Using Cough Sounds

Department of System Cybernetics, Institute of Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8527, Japan
Department of Rehabilitation, Faculty of Health Sciences, Hiroshima Cosmopolitan University, Hiroshima 731-3166, Japan
Division of Physical Analysis and Therapeutic Sciences, Institute of Biomedical and Health Sciences, Hiroshima University, Hiroshima 734-8553, Japan
Division of Rehabilitation, Department of Clinical Support, Hiroshima University Hospital, Hiroshima 734-8551, Japan
Authors to whom correspondence should be addressed.
Sensors 2018, 18(7), 2381;
Received: 8 June 2018 / Revised: 8 July 2018 / Accepted: 18 July 2018 / Published: 22 July 2018
(This article belongs to the Special Issue Wearable Sensors and Devices for Healthcare Applications)
Cough peak flow (CPF) is a measurement for evaluating the risk of cough dysfunction and can be measured using various devices, such as spirometers. However, complex device setup and the face mask required to be firmly attached to the mouth impose burdens on both patients and their caregivers. Therefore, this study develops a novel cough strength evaluation method using cough sounds. This paper presents an exponential model to estimate CPF from the cough peak sound pressure level (CPSL). We investigated the relationship between cough sounds and cough flows and the effects of a measurement condition of cough sound, microphone type and participant’s height and gender on CPF estimation accuracy. The results confirmed that the proposed model estimated CPF with a high accuracy. The absolute error between CPFs and estimated CPFs were significantly lower when the microphone distance from the participant’s mouth was within 30 cm than when the distance exceeded 30 cm. Analysis of the model parameters showed that the estimation accuracy was not affected by participant’s height or gender. These results indicate that the proposed model has the potential to improve the feasibility of measuring and assessing CPF. View Full-Text
Keywords: cough sound; cough peak flow; microphone; cough ability; cough strength; in-ear microphone; smartphone cough sound; cough peak flow; microphone; cough ability; cough strength; in-ear microphone; smartphone
Show Figures

Figure 1

MDPI and ACS Style

Umayahara, Y.; Soh, Z.; Sekikawa, K.; Kawae, T.; Otsuka, A.; Tsuji, T. Estimation of Cough Peak Flow Using Cough Sounds. Sensors 2018, 18, 2381.

AMA Style

Umayahara Y, Soh Z, Sekikawa K, Kawae T, Otsuka A, Tsuji T. Estimation of Cough Peak Flow Using Cough Sounds. Sensors. 2018; 18(7):2381.

Chicago/Turabian Style

Umayahara, Yasutaka, Zu Soh, Kiyokazu Sekikawa, Toshihiro Kawae, Akira Otsuka, and Toshio Tsuji. 2018. "Estimation of Cough Peak Flow Using Cough Sounds" Sensors 18, no. 7: 2381.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop