Status
Conditions
Treatments
About
Aging of the population is dramatically increasing the number of hospitalized patients, with the consequent challenges of limited medical personnel and resources in hospitals. Wireless technologies that create highly connected healthcare environments are developed to help hospitals address these issues, once these technologies are perfectly integrated in the hospital environment with respect to IT infrastructure for big data storage. Such devices have proven remarkable efficiencies in monitoring patients with high patient safety, data accuracy and security, which are essential to provide high quality patient care, reduce health-related costs and optimize the management of high numbers of patients.
Cough is the most common condition that results in a visit to the physician. Often coughs are benign, but sometimes can be the sign of exacerbations of a chronic respiratory disease. Exacerbations are defined in the Global Initiative for Chronic Obstructive Lung Disease (GOLD) document "as an acute event characterised by a worsening of the patient's respiratory symptoms that is beyond normal day-to-day variations and leads to a change in medication". It is assumed that, if coughs were remotely monitored, hospitals might be unburdened, patients would be empowered to self-manage their health, and that prevention of serious respiratory diseases might be facilitated, thus improving health outcomes. Unfortunately, remote monitoring for cough that rely on self-reporting is impractical, as patients do not record data very reliably. On the contrary, a bed sensor under the mattress connected to a medical data analysis platform might monitor patients' micro-movements at night and alert the medical staff as soon as there is a cough exacerbation.
Full description
The clinical study is designed as a prospective observational pilot study to evaluate the reliability of a wireless bed sensor and data analysis platform to monitor coughs in hospitalized patients with respiratory diseases.
The study includes three phases:
3 Data analysis phase: to correlate bed sensor's signals with the AV recorded data. AV data as well computing will enable to determine the sensitivity and the selectivity of the device-generated signals.
Enrollment
Sex
Ages
Volunteers
Inclusion criteria
Exclusion criteria
Loading...
Data sourced from clinicaltrials.gov
Clinical trials
Research sites
Resources
Legal