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To develop a novel cough ability evaluation system through cough sounds, this study verified the effects of three types of microphones (bone conduction mic, mini speech mic, and smartphone mic) on the estimated cough peak flow. From the results of the non-linear regression analysis, the determination coefficients showed high values (greater than 0.7) for the three types of microphones investigated. Furthermore, for the cough sounds recorded with the bone conduction mic and the smartphone mic, including the height variable in the revised prediction equation of the cough peak flow improved the accuracy of the estimated cough peak flow.

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&rsquo, 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&rsquo, 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&rsquo, s height or gender. These results indicate that the proposed model has the potential to improve the feasibility of measuring and assessing CPF.