Project description
Your heart needs a good night’s sleep
Obstructive sleep apnoea (OSA) increases risks for cardiovascular disease – coronary artery disease, congestive heart failure and stroke. The underlying reasons behind this complex association between sleep disordered breathing and cardiovascular disease are not entirely defined. Experimental observation and data analysis are crucial to identify the mechanisms at work. The EU-funded DEEPDREAM project is combining advanced computational modelling, signal processing and interpretation techniques to assess the activation of the neural mechanisms related to intermittent hypoxia. The results will bring us one step closer to the prevention of cardiovascular diseases.
Objective
Prediction is crucial to reduce the risk of cardiovascular complications caused by CRDs, a significant public health issue. Intermittent hypoxia caused by obstructive sleep apnea (OSA) is known to contribute to impaired autonomic cardiac function, but the impact of apneas severity on autonomic cardiac function remains unclear.
Prediction is performed by using biomarkers, which can be proposed only if the pathophysiological mechanisms which link the severity of sleep apneas with heart rate variability alterations become clearer. A crucial condition to clarify these mechanisms is a close and continuous interaction between experimental observations and data analysis/modeling.
This project, which combined advanced computational modeling and signal processing and interpretation techniques to assess the activation of the neural mechanisms related to intermittent hypoxia, offers a concrete possibility to go one step further in the prevention of cardiovascular diseases in OSA.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- medical and health sciencesclinical medicinepsychiatrysleep disorders
- medical and health scienceshealth sciencespublic health
- medical and health scienceshealth sciencesinfectious diseasesRNA virusescoronaviruses
- natural sciencescomputer and information sciencescomputational science
- medical and health sciencesclinical medicinecardiologycardiovascular diseases
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Programme(s)
Funding Scheme
MSCA-IF-EF-ST - Standard EFCoordinator
08028 Barcelona
Spain