Abstract
BackgroundObjective evaluations of cough frequency are considered important for assessing the clinical state of patients with respiratory diseases. While cough monitors with audio recordings are used in research settings, they are rarely used in clinical settings. Issues regarding privacy and background noise (especially the sounds of someone else’s cough) with audio recordings are barriers to the wide use of these monitors in clinical settings; to solve these problems, we developed a novel automatic cough frequency monitoring system combining a triaxial accelerator and a stretchable strain sensor.MethodsEleven healthy adult volunteers and 10 adult patients with cough were enrolled. The participants sat in a chair and wore two devices for 30 minutes for the cough measurements. An accelerator was attached to the epigastric region, and a stretchable strain sensor was worn around their neck. When the subjects coughed, these devices displayed specific waveforms. For the development of the algorithm, the participants’ measurement data from both devices were divided into consecutive small “units” lasting 5 seconds each. Whether each unit corresponded to a “cough unit” was determined by the observer who manually counted the cough records. Then, the data from all the participants were categorized into a training dataset and a test dataset. Using a variational autoencoder, a machine learning algorithm with deep learning, the components of the test dataset were automatically judged as being a “cough unit” or “non-cough unit”.ResultsThe sensitivity and specificity in detecting coughs among 21 participants were 92% and 96%, respectively. The triaxial accelerometer only yielded a sensitivity of 91% and specificity of 95%. Therefore, the diagnostic accuracy improved slightly when the accelerometer was combined with a stretchable strain sensor.ConclusionsAccording to the results of the current study, a cough frequency monitor with good performance can be created by combining an accelerometer and another biometric sensor. Our cough monitor is suitable for ambulatory settings because the devices are small and light. Our cough monitoring system, which does not require audio recordings, has the potential to be widely used in clinical settings without any concerns regarding privacy or background noise.
Objective cough frequency monitoring in real-world practice
