Sleep Measurement Study
Condition: Sleep
Study type: Observational

Summary: 
      Sleep behaviour has critical importance to health and wellbeing. A large body of evidence has
      implicated poor sleep in all-cause mortality, and in cardiovascular and cardiometabolic risk
      factors. Given the importance of sleep to health, the importance of accurately monitoring
      sleep duration and quality is becoming more evident. Polysomnography (PSG) is considered the
      gold standard for sleep assessment. Nevertheless, PSG is impractical, expensive and
      labour-intensive. Another method to quantify indices of sleep is based on actigraphic
      measures. Wrist worn actigraphy devices provide an indirect measure of sleep parameters e.g.
      total sleep time, sleep onset latency and waking time. However, the data is in the form of
      manufacturer-specific activity 'counts', making it difficult to compare the data with
      different accelerometer brands. Recently wrist-worn accelerometers have become increasingly
      used for objective measurement of physical activity in large population studies where
      participants are often asked to wear them for 24 hours continuously. These devices therefore
      collect data that could be used to estimate sleep parameters, and now there is a sleep
      algorithm that can be applied to raw data from accelerometers. The three widely used raw-data
      accelerometer brands are the Axivity, ActiGraph and GENEActiv and ActivPAL which is a
      thigh-worn accelerometer that provides a measure of posture. Studies that examined accuracy
      of estimating sleep parameters from different brands of accelerometers compared to PSG have
      reported conflicting results which could be due to the use of different sleep algorithms and
      accelerometer placement (dominant vs. non-dominant wrist vs. hip). Therefore this study will
      aim to validate automated sleep algorithms for research grade accelerometers against PSG in a
      clinical and healthy adult population.
    

Detailed description: 
      Sleep behaviour has critical importance to health and wellbeing. Insufficient sleep duration
      and poor sleep quality are independent contributors to high blood pressure and cardiovascular
      disease, depression, obesity and diabetes. Given the importance of sleep duration and quality
      to health, the importance of accurately monitoring sleep duration and quality in everyday
      clinical practice is becoming more evident.

      The 'gold standard' physiological measure of sleep is sleep polysomnography (PSG). PSG is
      used to quantify measures of sleep, including length of sleep, time taken to fall asleep,
      sleep efficiency. The disadvantages of sleep PSG include the need to attend a laboratory, use
      of expensive equipment, specialised staff to administer PSG, and to score and interpret the
      PSG outputs, which limit its use in larger, or free-living studies.

      Another method to quantify indices of sleep is based on actigraphy, demonstrating 90%
      agreement with polysomnography. Wrist actigraphy allows sleep assessment over several days
      and measures daily sleep-wake cycles. However, the data is in the form of
      manufacturer-specific activity 'counts' over a specific time window, making it difficult to
      compare the data with different accelerometer brands. Recently wrist-worn accelerometers have
      become increasingly used for objective measurement of physical activity in large population
      studies where participants are often asked to wear them for 24 hours continuously, to
      maximise compliance. These devices therefore collect data that could be used to estimate
      sleep parameters, however to be able to use, pool or compare these data there is a need for
      sleep algorithms that can be applied to datasets from different accelerometer brands. The
      latest generation of accelerometers measure acceleration in universal units improving
      comparability among different brands of accelerometers and allowing more control in the data
      processing. Moreover, now there is a sleep detection algorithm that can applied to data from
      different raw-data accelerometer brands and is freely available as a part of GGIR package in
      R (software environment for statistical computing and graphics). The three widely used
      raw-data accelerometer brands are the Axivity, ActiGraph and GENEActiv and ActivPAL which is
      a thigh-worn accelerometer that provides a measure of posture using proprietary algorithms;
      however, raw data are now available.

      Studies that have validated the accelerometers with the PSG produced mixed results which can
      be attributed to use of manufacturer specific sleep algorithms and different accelerometer
      placement (dominant vs. non-dominant wrist vs. hip). Therefore validation of a sleep
      algorithm that can be applied to different accelerometer brands against PSG warrants
      investigation.
    

Observational model: Cohort
Time perspective: Cross-Sectional
Sampling method: Non-Probability Sample
Study population: 
        Clinical population: Patients on the waiting list for overnight PSG recording at Leicester
        General Hospital aged 18-65 Healthy volunteers: adults without known sleep disorder aged
        18-65