However, in order to analyze the predictive value of trends in nocturnal cough rate, the symptom has to persist over multiple nights. In general, the plan of this study is as follows: With a longitudinal study design, it is possible to investigate to which extent trends in the nocturnal cough rates might have meaningful implications for future asthma control and asthma exacerbations of patients. In This study, the focus will be put specifically on nocturnal cough rate due to the technical reasons. Therefore, the purpose of this study is to explore the value which cough rate might provide for asthma self-management in more detail. Additionally, due to the cross-sectional design of existing studies, it remains unclear whether the cough rate might have any prognostic value for predicting future asthma control. uncontrolled, partially controlled and controlled asthma), the statistically significant relationship between cough rate and asthma control might not be clinically meaningful. Unfortunately, due to considerable variance of cough rates within each category of asthma control (i.e. A first cross-sectional study has indicated that the cough rate during both day and night might be a valid marker for asthma control, rendering it a potentially useful parameter for self-monitoring. However, little is known about the utility of cough tracking for self-monitoring purposes in asthmatics. Additionally, asthma is the leading cause for chronic cough, responsible for 24-29% of cases. Cough is a particularly important symptom in asthma because it predicts asthma severity, indicates a worse prognosis and is perceived to be a troublesome symptom. The symptoms often get worse at night and often cause awakenings. Common symptoms are breathlessness, coughing and wheezing. In Switzerland, 7-15% of all children and 6-7% of all adults suffer from it. Condition or diseaseĭevice: The patient will undergo no interventionĪsthma, a chronic respiratory disease, belongs to the most prevalent chronic conditions. The focus of this study will be the cough during the night time due to the limited interfering noise, which greatly facilitates manual labeling and enables a more reliable detection rate of the machine learning algorithm.Īpart from developing a machine learning algorithm for cough detection, data will be gathered for the assessment of patient's sleep quality based on data obtained from smartphone's sensors. This machine learning algorithm will be further developed in order to provide robust results in the field. Recently, a machine learning algorithm was successfully designed to automatically detect cough in a proof of concept study. Consequently, manual labeling of cough based on video or sound recordings is still considered to be the gold standard for measuring cough rates by medical guidelines. Currently, there are no cough frequency monitors available, which measure cough rates in a fully automated and unobtrusive way. Additionally, the aim will be to identify and model trends in nocturnal cough rates. The incidence of nocturnal cough in asthmatics will be described and visualized over the course of one month in the first stage of the study. The plan is to use a longitudinal study design, in order to investigate to which extent trends in the nocturnal cough rates might have meaningful implications for future asthma control and asthma exacerbations of patients. In this study, the focus will be specifically on nocturnal cough rate. The purpose of the study is to explore the value which cough rate might provide for asthma self-management.
0 Comments
Leave a Reply. |