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Smartphone Enabled Detection of Nocturnal Cough Rate and Sleep Quality as a Prognostic Marker for Asthma Control

NCT03635710 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 94

Last updated 2020-01-27

No results posted yet for this study

Summary

The purpose of the study is to explore the value which cough rate might provide for asthma self-management. In this study, the focus will be specifically on nocturnal cough rate. 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. 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. Additionally, the aim will be to identify and model trends in nocturnal cough rates.

Measuring cough is very time-consuming. Currently, there are no cough frequency monitors available, which measure cough rates in a fully automated and unobtrusive way. 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. Recently, a machine learning algorithm was successfully designed to automatically detect cough in a proof of concept study. This machine learning algorithm will be further developed in order to provide robust results in the field. 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.

Apart 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.

Conditions

Interventions

DEVICE

The patient will undergo no intervention

Night coughs will be monitored using smartphone a app and interpreted using machine learning algorithm.

Sponsors & Collaborators

  • University of Zurich

    collaborator OTHER

  • University of St.Gallen

    collaborator OTHER

  • Cantonal Hospital of St. Gallen

    lead OTHER

Principal Investigators

  • Frank Rassouli, MD · Cantonal Hospital St. Gallen

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2018-01-01
Primary Completion
2019-12-31
Completion
2019-12-31

Countries

  • Switzerland

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT03635710 on ClinicalTrials.gov