Sleep Measurement Study

Study Overview
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Brief Summary
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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
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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.

Official Title
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Validation of Automated Sleep Algorithms for Accelerometer Data in a Clinical and Healthy Adult Population: Sleep Measurement Study

Conditions
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Sleep

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Clinical population: Participants willing and able to give informed consent for participation in the study Male or Female Aged 18-65 years inclusive Patients on the waiting list for overnight PSG recording at Leicester General Hospital Healthy volunteers 1. Participants willing and able to give informed consent for participation in the study 2. Male or Female 3. Aged 18-65 years inclusive 4. No known sleep disorder (This will be self-reported by the participants) Exclusion Criteria: Participant is unwilling or unable to give informed consent Anyone without a good command of the English language Anyone <18 years of age and >65 years of age Patients suspected of having a movement disorder in sleep (e.g. Periodic Limb Movement in Sleep or REM-Sleep Behaviour Disorder).

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 65 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Sleep clinic patients<br>All adult patients, from 18 years and up to and including 65 years of age, on the waiting list for overnight polysomnography (PSG) recording at Leicester General Hospital. | |
| Healthy volunteers<br>All adults, from 18 and up to and including 65 years of age without a known sleep disorder. | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Total sleep time | minutes | 10 days | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Time in bed | minutes | 10 days | 
| Sleep efficiency | percentage | 10 days | 
| Sleep onset | hours | 10 days | 
| Waking time | hours | 10 days |