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.
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.
Coughing is the primary defence mechanism against foreign bodies in the central airways and can quantitatively be assessed by cough peak flow (CPF). We conducted a narrative review of the literature on CPF, which is most commonly used for evaluating cough strength. This review regards the method for measurement of CPF, the cough-related factors influencing CPF, the clinical significance of CPF evaluation, and a novel cough strength prediction method using cough sounds. Furthermore, this review presents various cutoff thresholds that predict extubation failure in patients on mechanical ventilation, acute respiratory failure, and aspiration risk. The published clinical evidence of CPF demonstrates reasonable diagnostic accuracy, predictive power, and validity, although additional studies on the non-contact measurement of CPF via cough sounds with better-quality methodologies are required.
Cough peak flow (CPF) is a measurement to evaluate 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.
Purpose: The purpose of this study was to investigate the influence of hyperoxic recovery on cardiopulmonary and muscle oxygenation following maximal dynamic exercise. Subjects: Eleven healthy male subjects performed cycle ergometer step exercise for 10 min at 50% predicted maximal oxygen consumption after 10 min of recovery breathing with either room air or a 100% oxygen gas mixture (random order) following maximal exercise. Pulmonary gas exchange was measured and was computed breath-bybreath among the subjects. Continuous measurements of stroke volume and cardiac output were performed using the Portapres device. Venous blood for measurement of lactate was collected before and after step exercise following maximal exercise. Near-infrared spectroscopy was used to measure peripheral tissue saturation in the right vastus lateralis muscle. Results: Repeated measures analysis of variance demonstrated that the interaction (recovery breathing × time) was statistically significant with regard to maximal oxygen consumption (P < 0.05) and tissue saturation (P < 0.05). Conclusion: Our findings suggest that muscle oxygenation during exercise at 50% predicted maximal oxygen consumption might be influenced by the hyperoxic recovery condition following maximal exercise.
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