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.

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:

1. Calibration phase: to determine the degree of coughs' homogeneity between patients. The control source of data will be an audio-video (AV) system consisting in a microphone and a polygraph to record cough events along with an infrared webcam to register patient's movements. At the end of the calibration period, the data generated by the device will be analysed to determine if the coughs are homogeneous or heterogeneous, according to patient follow-up and AV outcomes. The degree of homogeneity will allow establishing the correct number of patients to be followed in the interventional phase (estimated 20 patients) and to set a threshold to define when there is an exacerbation.
2. Observational phase: to collect data in about 20 patients from both sources, namely the bed sensor and the AV system in the patient's hospital room. Data will be collected in parallel by the two systems during two consecutive nights for each patient.

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.

Inclusion Criteria:

• Suffering from chronic obstructive pulmonary disease (COPD I to IV) or other respiratory diseases generating dry or productive cough and hospitalized for a minimal duration of 5 days
• Living in the Canton of Neuchâtel
• Understanding French

Exclusion Criteria:

• Suffering from cognitive disorders
• Refractory to test new technologies

Male and female subjects aged ≥ 18 years fulfilling all of the inclusion criteria are eligible for the study. The presence of any one of the exclusion criteria will lead to exclusion of the participant.