Sleep DisorderNCT04568408
Validation of the Quality of Sleep Data for Xiaomi Domestic Wristbands
An observational study of Sleep Disorder, run by Universidade da Coruña at 1 site in Spain.
Trial summary
Introduction: Polysomnography (PSG) is currently the accepted Gold Standard for sleep studies as it measures multiple variables that lead to a clear diagnosis of any sleep disorder. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Sleep Disorder
- What is being tested?
- Xiaomi MiBand 5
- Type of treatment
- Medical device
- How many people
- 43 participants
- Where
- 1 siteSpain
- Study dates
- 4 Aug 2020to 30 Dec 2021
- How long will I take part?
- 1 Day
- 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 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Adult population with a self-perception of sleep problems or poor quality of their sleep
Who may be able to join
- Attending to the Sleep Unit to be perfomed a Polysomnography study
- Declaring a chronological age that is equal or higher than 18 years old
Who cannot join
- Having significant health complications that hinder active participation in the study
- Suffering from skin hypersensitivity or an allergic reaction due to the materials the wristbands that will be used in the study as measuring instruments are made of
Trial locations and contacts
1 site in 1 country.
About this study
Introduction: Polysomnography (PSG) is currently the accepted Gold Standard for sleep studies as it measures multiple variables that lead to a clear diagnosis of any sleep disorder. However, it has some clear drawbacks as it can only be performed by qualified technicians, has a high cost and complexity and is very invasive. In the last years, Actigraphy has been used along with PSG for sleep studies. In this study, the investigators intend to assess the capability of the new Xiaomi Mi Band 5 to be used as a sleep self-assessment tool for patients.
Objective: Determine whether sleep stages recorded by the new Xiaomi Mi Band 5 can effectively replace PSG sleep stages classification in patients that undergo a sleep study.
Read more
Methods and analysis: the study will be carried out with patients in a hospital from A Coruña (Galicia, Spain) that are > 18 years old. Patients who are performed a polysomnography test will be given the wearables so the investigators can record sleep stages with both techniques in order to compare both recordings afterwards.
This is an observational, analytic and longitudinal study. In other words, in this study different variables from the population of interest will be observed and recorded without any direct intervention, so as to establish causality associations between these variables. It is considered as longitudinal since a six-months tracking of the variables will be performed, continually (and sometimes occasionally) recording and monitoring sleep quality (wearable wristbands).
The data obtained from PSG and Xiaomi Mi Band 5 will be preprocessed and explored before extracting the features of interest for the study. Then, Paired sample T-Test will be performed to compare the means among the different variables, Bland-Altman plots will be used to assess the concordance between both techniques and, finally, Epoch by Epoch analysis will be performed to compare the classification of the sleep stages carried out by both PSG and Xiaomi.
Read the detailed description
Introduction: Sleep disorders are becoming a widespread health problem within the general population. Beyond the tiredness itself, these disorders have been found to be related to physical and mental issues like cardiovascular pathologies, obesity, depression and anxiety. This makes clear the necessity of achieving a quality rest to prevent potential chronic diseases. On this issue, Polysomnography (PSG) is currently the accepted Gold Standard for sleep studies as it measures multiple variables that lead to a clear diagnosis of any sleep disorder. However, it has some clear drawbacks as it can only be performed by qualified technicians, has a high cost and complexity and is very invasive. In the last years, several studies that focus on validating wearable devices as useful sleep trackers have emerged. In this study, the investigators intend to assess the capability of the new Xiaomi Mi Band 5 to be used as a tool for sleep self-assessment for patients. The interest in studying this smartband is due to its low price and acceptance among the population. If this device proves to be a good sleep tracker, it would allow the population to assess their own sleep and consider if they need to visit their medical practitioner, which would improve the prognosis of any underlying condition they may be developing derived from their restlessness.
Objective: Determine whether sleep stages recorded by the new Xiaomi Mi Band 5 can effectively replace PSG sleep stages classification in patients that undergo a sleep study. The following features will be calculated for both devices: total sleep time, sleep efficiency, sleep latency and wake after sleep onset. Sleep stages will also be recorded.
Methods and analysis: the study will be carried out with patients in a hospital from A Coruña (Galicia, Spain) that are > 18 years old. Patients who are performed a polysomnography test will be given the wearables so the investigators can record sleep stages with both techniques in order to compare both recordings afterwards.
This is an observational, analytic and longitudinal study. In other words, in this study different variables from the population of interest will be observed and recorded without any direct intervention, so as to establish causality associations between these variables. It is considered as longitudinal since a six-months tracking of the variables will be performed, continually (and sometimes occasionally) recording and monitoring sleep quality (wearable wristbands).
The data obtained from PSG and Xiaomi Mi Band 5 will be preprocessed and explored before extracting the features of interest for the study. Then, Paired sample T-Test will be performed to compare the means among the different variables, Bland-Altman plots will be used to assess the concordance between both techniques and, finally, Epoch by Epoch analysis will be performed to compare the classification of the sleep stages carried out by both PSG and Xiaomi.
- Conditions
- Sleep Disorder
- Being tested
- Xiaomi MiBand 5
- Keywords
- Sleep, Polysomnography, Occupational Performance, Participatory Health, Internet of Things, Wearables
- Medical subject headings
- Sleep Wake Disorders
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Xiaomi MiBand 5Device
Comparison of sleep-monitoring device against polysomnography (PSG)
| Study group | Role | What they receive |
|---|---|---|
| Sleep study participants | Adults presenting sleep difficulties or poor sleep quality that are performed a Polisomnography study in a Sleep Unit at hospital. Receives: Device: Xiaomi MiBand 5 |
What is being measured
The primary outcome is the main question the study is designed to answer.
Sleep recording Reliability
Assessment of sleep measurement and sleep stages classification
Measured: 6 Months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Sep 2020
- Study start4 Aug 2020
- Primary completion16 Sep 2020
- Study completion30 Dec 2021
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (25)Papers the sponsor has linked to this study.
- Other trials for Sleep DisorderStudies 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
- Prospective
- Enrolment
- 43 participants (actual)
- Target duration
- 1 Day
Sponsor and investigators
- Lead sponsor
- Universidade da Coruña
- Sponsor type
- University, hospital or other
- Collaborators
- Center on Information and Communication Technologies, IMQ San Rafael
- Responsible party
- Principal investigator, Javier Pereira, Universidade da Coruña
- Investigators
- Javier Pereira, PhD, Principal investigator, Universidade da Coruña
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04568408
- Sponsor's protocol ID
- 2020/318
- Status last verified
- May 2022
- First submitted
- 16 Sep 2020
- Last updated
- 20 May 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Publications
Wade AG. The societal costs of insomnia. Neuropsychiatr Dis Treat. 2010 Dec 20;7:1-18. doi: 10.2147/NDT.S15123.
PubMed 21326650Chen JH, Waite L, Kurina LM, Thisted RA, McClintock M, Lauderdale DS. Insomnia symptoms and actigraph-estimated sleep characteristics in a nationally representative sample of older adults. J Gerontol A Biol Sci Med Sci. 2015 Feb;70(2):185-92. doi: 10.1093/gerona/glu144. Epub 2014 Sep 8.
PubMed 25199910Koffel E, McCurry SM, Smith MT, Vitiello MV. Improving pain and sleep in middle-aged and older adults: the promise of behavioral sleep interventions. Pain. 2019 Mar;160(3):529-534. doi: 10.1097/j.pain.0000000000001423. No abstract available.
PubMed 30562269Kurina LM, Thisted RA, Chen JH, McClintock MK, Waite LJ, Lauderdale DS. Actigraphic sleep characteristics among older Americans. Sleep Health. 2015 Dec;1(4):285-292. doi: 10.1016/j.sleh.2015.09.004.
PubMed 28815195Chamorro N, Sellares J, Millan G, Cano E, Soler N, Embid C, Montserrat JM. An integrated model involving sleep units and primary care for the diagnosis of sleep apnoea. Eur Respir J. 2013 Oct;42(4):1151-4. doi: 10.1183/09031936.00192812. No abstract available.
PubMed 24081767Merilahti J, Korhonen I. Association between Continuous Wearable Activity Monitoring and Self-Reported Functioning in Assisted Living Facility and Nursing Home Residents. J Frailty Aging. 2016;5(4):225-232. doi: 10.14283/jfa.2016.102.
PubMed 27883169Shelgikar AV, Anderson PF, Stephens MR. Sleep Tracking, Wearable Technology, and Opportunities for Research and Clinical Care. Chest. 2016 Sep;150(3):732-43. doi: 10.1016/j.chest.2016.04.016. Epub 2016 Apr 29.
PubMed 27132701Griessenberger H, Heib DP, Kunz AB, Hoedlmoser K, Schabus M. Assessment of a wireless headband for automatic sleep scoring. Sleep Breath. 2013 May;17(2):747-52. doi: 10.1007/s11325-012-0757-4. Epub 2012 Sep 21.
PubMed 22996794Lee PH, Suen LK. The convergent validity of Actiwatch 2 and ActiGraph Link accelerometers in measuring total sleeping period, wake after sleep onset, and sleep efficiency in free-living condition. Sleep Breath. 2017 Mar;21(1):209-215. doi: 10.1007/s11325-016-1406-0. Epub 2016 Sep 10.
PubMed 27614441Smith MT, McCrae CS, Cheung J, Martin JL, Harrod CG, Heald JL, Carden KA. Use of Actigraphy for the Evaluation of Sleep Disorders and Circadian Rhythm Sleep-Wake Disorders: An American Academy of Sleep Medicine Clinical Practice Guideline. J Clin Sleep Med. 2018 Jul 15;14(7):1231-1237. doi: 10.5664/jcsm.7230.
PubMed 29991437Xie J, Wen D, Liang L, Jia Y, Gao L, Lei J. Evaluating the Validity of Current Mainstream Wearable Devices in Fitness Tracking Under Various Physical Activities: Comparative Study. JMIR Mhealth Uhealth. 2018 Apr 12;6(4):e94. doi: 10.2196/mhealth.9754.
PubMed 29650506Kubala AG, Barone Gibbs B, Buysse DJ, Patel SR, Hall MH, Kline CE. Field-based Measurement of Sleep: Agreement between Six Commercial Activity Monitors and a Validated Accelerometer. Behav Sleep Med. 2020 Sep-Oct;18(5):637-652. doi: 10.1080/15402002.2019.1651316. Epub 2019 Aug 27.
PubMed 31455144Gordt K, Gerhardy T, Najafi B, Schwenk M. Effects of Wearable Sensor-Based Balance and Gait Training on Balance, Gait, and Functional Performance in Healthy and Patient Populations: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Gerontology. 2018;64(1):74-89. doi: 10.1159/000481454. Epub 2017 Nov 1.
PubMed 29130977Kahawage P, Jumabhoy R, Hamill K, de Zambotti M, Drummond SPA. Validity, potential clinical utility, and comparison of consumer and research-grade activity trackers in Insomnia Disorder I: In-lab validation against polysomnography. J Sleep Res. 2020 Feb;29(1):e12931. doi: 10.1111/jsr.12931. Epub 2019 Oct 18.
PubMed 31626361de Zambotti M, Goldstone A, Claudatos S, Colrain IM, Baker FC. A validation study of Fitbit Charge 2 compared with polysomnography in adults. Chronobiol Int. 2018 Apr;35(4):465-476. doi: 10.1080/07420528.2017.1413578. Epub 2017 Dec 13.
PubMed 29235907
Study at a glance
From the registry record, last updated by the sponsor on 20 May 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Validation of the Quality of Sleep Data for Xiaomi Domestic Wristbands
- ClinicalTrials.gov ID
- NCT04568408
- Acronym / sponsor ID
- 2020/318
- Conditions
- Sleep Disorder
- Keywords
- Sleep, Polysomnography, Occupational Performance, Participatory Health, Internet of Things, Wearables
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 43 participants (actual)
- Lead sponsor
- Universidade da CoruñaUniversity, hospital or other
- Collaborators
- Center on Information and Communication Technologies, IMQ San Rafael
- Study start
- 4 Aug 2020 (actual)
- Primary completion
- 16 Sep 2020 (actual)
- Study completion
- 30 Dec 2021 (actual)
- First posted
- 29 Sep 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.
Introduction: Polysomnography (PSG) is currently the accepted Gold Standard for sleep studies as it measures multiple variables that lead to a clear diagnosis of any sleep disorder. However, it has some clear drawbacks as it can only be performed by qualified technicians, has a high cost and complexity and is very invasive. In the last years, Actigraphy has been used along with PSG for sleep studies. In this study, the investigators intend to assess the capability of the new Xiaomi Mi Band 5 to be used as a sleep self-assessment tool for patients.
Objective: Determine whether sleep stages recorded by the new Xiaomi Mi Band 5 can effectively replace PSG sleep stages classification in patients that undergo a sleep study.
Methods and analysis: the study will be carried out with patients in a hospital from A Coruña (Galicia, Spain) that are > 18 years old. Patients who are performed a polysomnography test will be given the wearables so the investigators can record sleep stages with both techniques in order to compare both recordings afterwards.
This is an observational, analytic and longitudinal study. In other words, in this study different variables from the population of interest will be observed and recorded without any direct intervention, so as to establish causality associations between these variables. It is considered as longitudinal since a six-months tracking of the variables will be performed, continually (and sometimes occasionally) recording and monitoring sleep quality (wearable wristbands).
The data obtained from PSG and Xiaomi Mi Band 5 will be preprocessed and explored before extracting the features of interest for the study. Then, Paired sample T-Test will be performed to compare the means among the different variables, Bland-Altman plots will be used to assess the concordance between both techniques and, finally, Epoch by Epoch analysis will be performed to compare the classification of the sleep stages carried out by both PSG and Xiaomi.
Detailed description
Introduction: Sleep disorders are becoming a widespread health problem within the general population. Beyond the tiredness itself, these disorders have been found to be related to physical and mental issues like cardiovascular pathologies, obesity, depression and anxiety. This makes clear the necessity of achieving a quality rest to prevent potential chronic diseases. On this issue, Polysomnography (PSG) is currently the accepted Gold Standard for sleep studies as it measures multiple variables that lead to a clear diagnosis of any sleep disorder. However, it has some clear drawbacks as it can only be performed by qualified technicians, has a high cost and complexity and is very invasive. In the last years, several studies that focus on validating wearable devices as useful sleep trackers have emerged. In this study, the investigators intend to assess the capability of the new Xiaomi Mi Band 5 to be used as a tool for sleep self-assessment for patients. The interest in studying this smartband is due to its low price and acceptance among the population. If this device proves to be a good sleep tracker, it would allow the population to assess their own sleep and consider if they need to visit their medical practitioner, which would improve the prognosis of any underlying condition they may be developing derived from their restlessness.
Objective: Determine whether sleep stages recorded by the new Xiaomi Mi Band 5 can effectively replace PSG sleep stages classification in patients that undergo a sleep study. The following features will be calculated for both devices: total sleep time, sleep efficiency, sleep latency and wake after sleep onset. Sleep stages will also be recorded.
Methods and analysis: the study will be carried out with patients in a hospital from A Coruña (Galicia, Spain) that are > 18 years old. Patients who are performed a polysomnography test will be given the wearables so the investigators can record sleep stages with both techniques in order to compare both recordings afterwards.
This is an observational, analytic and longitudinal study. In other words, in this study different variables from the population of interest will be observed and recorded without any direct intervention, so as to establish causality associations between these variables. It is considered as longitudinal since a six-months tracking of the variables will be performed, continually (and sometimes occasionally) recording and monitoring sleep quality (wearable wristbands).
The data obtained from PSG and Xiaomi Mi Band 5 will be preprocessed and explored before extracting the features of interest for the study. Then, Paired sample T-Test will be performed to compare the means among the different variables, Bland-Altman plots will be used to assess the concordance between both techniques and, finally, Epoch by Epoch analysis will be performed to compare the classification of the sleep stages carried out by both PSG and Xiaomi.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 1 Day
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Sleep study participants | – | Device: Xiaomi MiBand 5Adults presenting sleep difficulties or poor sleep quality that are performed a Polisomnography study in a Sleep Unit at hospital. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Adult population with a self-perception of sleep problems or poor quality of their sleep
Key inclusion criteria (2 listed)
- Attending to the Sleep Unit to be perfomed a Polysomnography study
- Declaring a chronological age that is equal or higher than 18 years old
Key exclusion criteria (2 listed)
- Having significant health complications that hinder active participation in the study
- Suffering from skin hypersensitivity or an allergic reaction due to the materials the wristbands that will be used in the study as measuring instruments are made of
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Xiaomi MiBand 5Comparison of sleep-monitoring device against polysomnography (PSG) | Device | Sleep study participants |
Primary outcome
Sleep recording Reliability
Time frame: 6 Months
Assessment of sleep measurement and sleep stages classification
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 20 May 2022.
- Background: PubMed 21326650Wade AG. The societal costs of insomnia. Neuropsychiatr Dis Treat. 2010 Dec 20;7:1-18. doi: 10.2147/NDT.S15123.
- Background: PubMed 25199910Chen JH, Waite L, Kurina LM, Thisted RA, McClintock M, Lauderdale DS. Insomnia symptoms and actigraph-estimated sleep characteristics in a nationally representative sample of older adults. J Gerontol A Biol Sci Med Sci. 2015 Feb;70(2):185-92. doi: 10.1093/gerona/glu144. Epub 2014 Sep 8.
- Background: PubMed 30562269Koffel E, McCurry SM, Smith MT, Vitiello MV. Improving pain and sleep in middle-aged and older adults: the promise of behavioral sleep interventions. Pain. 2019 Mar;160(3):529-534. doi: 10.1097/j.pain.0000000000001423. No abstract available.
- Background: PubMed 28815195Kurina LM, Thisted RA, Chen JH, McClintock MK, Waite LJ, Lauderdale DS. Actigraphic sleep characteristics among older Americans. Sleep Health. 2015 Dec;1(4):285-292. doi: 10.1016/j.sleh.2015.09.004.
- Background: PubMed 24081767Chamorro N, Sellares J, Millan G, Cano E, Soler N, Embid C, Montserrat JM. An integrated model involving sleep units and primary care for the diagnosis of sleep apnoea. Eur Respir J. 2013 Oct;42(4):1151-4. doi: 10.1183/09031936.00192812. No abstract available.
- Background: PubMed 27883169Merilahti J, Korhonen I. Association between Continuous Wearable Activity Monitoring and Self-Reported Functioning in Assisted Living Facility and Nursing Home Residents. J Frailty Aging. 2016;5(4):225-232. doi: 10.14283/jfa.2016.102.
- Background: PubMed 27132701Shelgikar AV, Anderson PF, Stephens MR. Sleep Tracking, Wearable Technology, and Opportunities for Research and Clinical Care. Chest. 2016 Sep;150(3):732-43. doi: 10.1016/j.chest.2016.04.016. Epub 2016 Apr 29.
- Background: PubMed 22996794Griessenberger H, Heib DP, Kunz AB, Hoedlmoser K, Schabus M. Assessment of a wireless headband for automatic sleep scoring. Sleep Breath. 2013 May;17(2):747-52. doi: 10.1007/s11325-012-0757-4. Epub 2012 Sep 21.
- Background: PubMed 27614441Lee PH, Suen LK. The convergent validity of Actiwatch 2 and ActiGraph Link accelerometers in measuring total sleeping period, wake after sleep onset, and sleep efficiency in free-living condition. Sleep Breath. 2017 Mar;21(1):209-215. doi: 10.1007/s11325-016-1406-0. Epub 2016 Sep 10.
- Background: PubMed 29991437Smith MT, McCrae CS, Cheung J, Martin JL, Harrod CG, Heald JL, Carden KA. Use of Actigraphy for the Evaluation of Sleep Disorders and Circadian Rhythm Sleep-Wake Disorders: An American Academy of Sleep Medicine Clinical Practice Guideline. J Clin Sleep Med. 2018 Jul 15;14(7):1231-1237. doi: 10.5664/jcsm.7230.
- Background: PubMed 29650506Xie J, Wen D, Liang L, Jia Y, Gao L, Lei J. Evaluating the Validity of Current Mainstream Wearable Devices in Fitness Tracking Under Various Physical Activities: Comparative Study. JMIR Mhealth Uhealth. 2018 Apr 12;6(4):e94. doi: 10.2196/mhealth.9754.
- Background: PubMed 31455144Kubala AG, Barone Gibbs B, Buysse DJ, Patel SR, Hall MH, Kline CE. Field-based Measurement of Sleep: Agreement between Six Commercial Activity Monitors and a Validated Accelerometer. Behav Sleep Med. 2020 Sep-Oct;18(5):637-652. doi: 10.1080/15402002.2019.1651316. Epub 2019 Aug 27.
- 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.
Javier Pereira, PhD principal investigator
Universidade da Coruña
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 Disorder, run by Universidade da Coruña at 1 site in Spain.
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 2 inclusion and 2 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 20 May 2022. 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 Spain. 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?
Sleep recording Reliability (time frame: 6 Months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04568408, which also lists 25 linked publications.
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 20 May 2022.