HCR.20.045 – SleepTech

Route: Health care research, sickness prevention and treatment

Cluster question: 074 How does sleep affect our health?

Sleep is a biological mystery: characterized by a striking lack of perceptual attention and behavioral reactivity towards a potentially dangerous environment, extended periods of sleep put the organism at considerable risk. To compensate for this obvious disadvantage, sleep must serve crucial biological functions. Several functions of sleep have been suggested over the years, including energy metabolism, immunological processing, brain clearance, memory consolidation, or emotion regulation. While some of these functions might be evolutionary older or more important than others, they are not mutually exclusive: sleep most likely is a multifunctional state. Accordingly, disturbed sleep has been shown to be involved in the development or perpetuation of many psychiatric, neurological or somatic diseases, and is often named as one of the most burdening symptoms by patients. Laboratory-based polysomnography as the methodological gold standard in sleep research is being used in a largely unchanged manner for several decades, however it is costly, time-consuming and inconvenient for patients, medical staff and researchers. Also for therapeutic options to treat sleep disturbances, slow progress has been made over the last decades – in particular pharmaceutical interventions often do more harm than good for the long-term outcome of sleep health. However, recent advances in sleep research and technology allow for novel sleep-focused prevention and treatment options; a development that is increasingly driven by the acknowledgement of sleep as a crucial life-style factor for health and well-being by the consumer market. In this project, a consortium of research institutes and industry partners will develop and investigate several novel technologies for the reliable measurement of sleep in both laboratory and home-based conditions, for the prevention and therapeutic intervention of sleep-related diseases, and for the integration of healthy sleep habits in everyday life.

Keywords

Big Data, EEG, machine learning, polysomnography, sleep, technology, wearables

Other organisations

Eindhoven University of Technology (TU/e), Vrije Universiteit Amsterdam (VU)

Submitter

Organisation Radboud University Medical Center (RUMC)
Name Dr. Martin Dresler
E-mail martin.dresler@donders.ru.nl
Website radboudumc.nl