LAUSR

1. Wearable technologies to diagnose obstructive sleep apnoea (OSA): Wearable technologies are increasingly being used to monitor various aspects of health, including sleep. Validation studies on wrist-worn devices suggest that we are rapidly moving towards devices that can reliably monitor and stage sleep. Efforts are underway to diagnoseOSAusing such technologies. Remotemonitoring approachesmay also be helpful to provide patient engagement and to allow clinicians to identify and intervene on patients who are strugglingwith therapy. 2. Plasma biomarkers to diagnose and risk stratify OSA: Biomarkers are being used increasingly to diagnose various conditions, for example plasma exosomes and microRNAs are being applied to OSA such that a clinician may ultimately be able to diagnose a patient with OSA based on a blood test. Moreover, these approaches may provide some insight into why a given patient has OSA and what is the risk of a particular complication. 3. Genome sequencing for individuals to predict risk of OSA and risk of OSA complications: Genetics studies are also providing insight into OSA risk and mechanisms. Big data approaches are now being applied to sleep medicine by using huge sample size to answer important questions. By identifying patients at risk of developing OSA, preventative strategies could be used in high-risk patients before complications develop or prior to the occurrence of irreversible changes, for example apoptosis in the hippocampus and age-related changes.