sCAVA - Sleep Assessment Using the CAVA Device

Overview

Clinical investigation of a medical device (CAVA) for recording eye movements. Forty volunteers will sleep in a specially designed sleep lab for one or two nights, depending on whether they are enrolled onto phase 1 (two nights) or phase 2 (one night) of the study. Each volunteer will wear the CAVA device along with a Polysomnography (PSG) device, which is the gold standard for monitoring sleep. The twenty participants in phase 2 will simultaneously wear a commercially available consumer device for monitoring sleep. The eye movement data captured using CAVA will be processed by novel computer algorithms to classify the sleep stages in the data into Rapid Eye Movement (REM), non-REM and awake. The results will be compared with the ground-truth from the gold standard, and also compared to the results from the commercially available device. The aim of the study is to determine whether CAVA could be a viable and competitive home-monitoring device for analysing sleep.

The Centres for Disease Control and Prevention (CDC) in the US has declared insufficient sleep a 'public health problem' \[1\]. Over 35% of adults in the United Kingdom (UK) sleep less than 7 hours and 16% sleep less than 6 hours per night and the proportion of people getting less than the recommended hours of sleep is rising (Liu et al., 2014). This is alarming as insufficient sleep can lead to increased mortality, accidents, and mistakes at work and is also linked with many chronic conditions-such as obesity, type 2 diabetes, heart disease, depression and neurodegeneration -that threaten the wellbeing of an increasing number of people across the globe. On an annual basis, the UK loses an estimated 207,000 working days due to insufficient sleep (mainly related to absenteeism) and the estimated economic cost of insufficient sleep in the UK is over 50 billion dollars, that is 1.86 % of the national Gross Domestic Product (GDP) \[2\]. Early detection of sleep problems is imperative for prevention of this process, however it is hindered by current technology, where the gold standard is represented by a laborious and expensive method called polysomnography (PSG). Therefore, the need for innovative technologies allowing the reliable monitoring of sleep behaviour in the home-environment using non-invasive, user friendly and broadly accessible methods is immense. This study aims to assess the suitability of the CAVA device (Continuous Ambulatory Vestibular Assessment) that was originally developed by Norfolk and Norwich University Hospitals (NNUH) clinicians and University of East Anglia (UEA scientists to monitor dizziness, for the purpose of diagnosing sleep conditions. The CAVA device is designed to record head and eye-movements continuously over several weeks. Such signals are known to be useful for sleep state diagnosis, and the preliminary analyses show that the data collected by the CAVA device clearly delineate sleep and wake episodes so it is therefore plausible that the CAVA device can be used for home-based sleep monitoring. The investigators term this new application sCAVA. The objective of the proposed study is to re-purpose the CAVA device as a reliable and broadly accessible sleep monitoring tool by developing, testing and validating algorithms to interpret sCAVA data for sleep monitoring purposes.