SleepNCT04288557
Sleep Measurement Study
An observational study of Sleep, run by University of Leicester at 1 site in United Kingdom.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 65 years
- Conditions the study is for
- Sleep
- How many people
- 31 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 23 Jan 2020to 28 Feb 2021
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 65 years
- All sexes
- No healthy volunteers
- Adult, Older adult
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
Who may be able to join
- 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)
Who cannot join
- 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).
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Validation of Automated Sleep Algorithms for Accelerometer Data in a Clinical and Healthy Adult Population: Sleep Measurement Study
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.
Read the 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.
- Conditions
- Sleep
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Sleep clinic patients | 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 | All adults, from 18 and up to and including 65 years of age without a known sleep disorder. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Total sleep time
minutes
Measured: 10 days
Secondary outcomes (4)
Time in bed
minutes
Measured: 10 days
Sleep efficiency
percentage
Measured: 10 days
Sleep onset
hours
Measured: 10 days
Waking time
hours
Measured: 10 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Feb 2020
- Study start23 Jan 2020
- Primary completion28 Feb 2021
- Study completion28 Feb 2021
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for SleepStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Enrolment
- 31 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Leicester
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Charlotte Edwardson, Study director, University of LeicesterAndrew Hall, Principal investigator, University Hospitals, Leicester
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04288557
- Sponsor's protocol ID
- 0713
- Status last verified
- Apr 2021
- First submitted
- 29 Jan 2020
- Last updated
- 5 May 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 5 May 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Validation of Automated Sleep Algorithms for Accelerometer Data in a Clinical and Healthy Adult Population: Sleep Measurement Study
- ClinicalTrials.gov ID
- NCT04288557
- Acronym / sponsor ID
- 0713
- Conditions
- Sleep
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 31 participants (actual)
- Lead sponsor
- University of LeicesterUniversity, hospital or other
- Study start
- 23 Jan 2020 (actual)
- Primary completion
- 28 Feb 2021 (actual)
- Study completion
- 28 Feb 2021 (actual)
- First posted
- 28 Feb 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Sleep clinic patients | – | –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 | – | –All adults, from 18 and up to and including 65 years of age without a known sleep disorder. |
Who may qualify
- Ages
- 18 to 65 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- 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
Key inclusion criteria (6 listed)
- 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)
Key exclusion criteria (4 listed)
- 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).
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Total sleep time
Time frame: 10 days
minutes
4 secondary outcomes
Time in bed
Time frame: 10 days
Sleep efficiency
Time frame: 10 days
Sleep onset
Time frame: 10 days
Waking time
Time frame: 10 days
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 5 May 2021.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Charlotte Edwardson study director
University of Leicester
Andrew Hall principal investigator
University Hospitals, Leicester
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Sleep, run by University of Leicester at 1 site in United Kingdom.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 5 May 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United Kingdom. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Total sleep time (time frame: 10 days). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 5 May 2021.