Breathing-Related Sleep DisorderReSTechNCT06606691
Wearable Technology in the Detection and Evaluation of Sleep-Related Breathing Disorders
An observational study of Breathing-Related Sleep Disorder and Sleep Disorder (Disorder), run by Universidade da Coruña at 2 sites in Spain.
Trial summary
This project is an observational study that aims to evaluate the accuracy of wearable devices in detecting potential sleep-related breathing disorders (SRBD) in individuals visiting the Sleep-Related Breathing Disorders and Home Ventilation Unit. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Breathing-Related Sleep Disorder, Sleep Disorder (Disorder)
- What is being tested?
- Xiaomi Mi Smart Band 8
- Type of treatment
- Medical device
- How many people
- 300 participants
- Where
- 2 sitesSpain
- Study dates
- 18 Feb 2025to 18 Jan 2026
- 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
- Healthy volunteers accepted
- Adult, Older adult
Study population: Adult population with a potential sleep-related breathing disorder.
Who may be able to join
- Be at least 18 years of age or older.
- Attend the Sleep Respiratory Disorders and Home Ventilation Unit for the polygraphy test.
Who cannot join
- Have significant health complications that hinder active participation in the study.
- Present skin hypersensitivity or a known allergy to the material used in the covers or straps of the wearable devices that will be used as one of the measurement instruments in the study.
Trial locations and contacts
2 sites in 1 country.
Spain2 sites
Hospital Álvaro Cunqueiro
Vigo, Pontevedra, 36312
Hospital Álvaro Cunqueiro
Vigo, Pontevedra
About this study
This project is an observational study that aims to evaluate the accuracy of wearable devices in detecting potential sleep-related breathing disorders (SRBD) in individuals visiting the Sleep-Related Breathing Disorders and Home Ventilation Unit. The main goal of the study is to determine if wearable devices, like sleep and activity-tracking wristbands and watches, can effectively supplement the detection of these disorders.
The study will analyze various variables related to sleep quality and quantity. Participants will be asked to wear a Xiaomi Mi Band 8 device during an overnight hospital polygraphy test, which will be conducted for one day in their usual daily environment. Additionally, at the beginning of their participation, they will need to complete a questionnaire collecting information about sociodemographic variables, daily habits, routines, and their assessment using the Epworth Sleepiness Scale.
After completing the polygraphy test and using the Xiaomi device, participants will be required to answer another questionnaire addressing aspects related to their sleep quality and habits during this period.
Read the detailed description
In recent years, sleep disorders have gained importance due to their high prevalence and impact on daily life, affecting people\'s ability to perform daily tasks and reducing quality of life. These disorders include difficulties falling asleep, respiratory interruptions, and poor sleep quality, with sleep-related breathing disorders (SRBD), such as obstructive sleep apnea (OSA), being particularly significant. OSA, which involves repeated airway obstructions during sleep, is especially common in older adults, individuals with obesity, and men, but it remains frequently underdiagnosed.
SRBD not only disrupts sleep but also increases the risk of chronic conditions like diabetes, hypertension, and strokes while creating an economic burden due to higher demand for medical resources. Their effects on physical and mental health lead to fatigue, reduced productivity, workplace accidents, and even disability, highlighting the need for more efficient diagnostic and management tools.
While polysomnography (PSG) is the gold standard for diagnosing sleep disorders, its high cost and invasive nature limit its accessibility. Wearable devices, such as wristbands and watches, offer a more accessible and non-invasive alternative, providing real-time data on sleep, heart rate, and activity. Though promising, these devices still require further research to confirm their accuracy in detecting SRBD. This project aims to evaluate the effectiveness of wearables as complementary tools in diagnosing and managing these disorders. Specifically, it has the following specific objectives: (1) To assess the accuracy, specificity, and sensitivity of wearable devices, such as wristbands and watches, in measuring blood oxygen saturation, heart rate, and activity, compared to nocturnal polygraphy. (2) To analyze the effectiveness of these devices in identifying individuals with potential sleep-related breathing disorders (SRBD) using unsupervised learning techniques. (3) To evaluate the impact and performance of an Artificial Intelligence model for detecting and classifying potential SRBD.
- Being tested
- Xiaomi Mi Smart Band 8
- Keywords
- Participatory Health, Internet of Things, Sleep, Polygraphy, Wearable devices, Occupational Performance
- 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 Mi Smart Band 8Device
The wearable device, Xiaomi Mi Smart Band 8, will be used solely for observational purposes to assess its accuracy in measuring sleep parameters, oxygen saturation, and heart rate in comparison to nocturnal polygraphy. Participants are receiving routine care as prescribed by their clinicians, and the wearable device is not part of their medical treatment but is being observed alongside standard polygraphy tests.
| Study group | Role | What they receive |
|---|---|---|
| Nocturnal polygraphy study participants | This project aims to study approximately 263 individuals from different age groups and genders who are suspected of having sleep-related breathing disorders. The participants will be those referred for a nocturnal polygraphy study at the Sleep-Related Breathing Disorders and Home Ventilation Unit. During the polygraph test, participants will also wear the Xiaomi Mi Smart Band 8 wearable device to compare its accuracy in measuring sleep parameters, oxygen saturation, and heart rate against the polygraphy results. Receives: Device: Xiaomi Mi Smart Band 8 |
What is being measured
The primary outcome is the main question the study is designed to answer.
Recording of deep sleep stage
The Xiaomi Mi Smart Band 8 will record the duration of deep sleep, measured in minutes, to help estimate and identify potential sleep-related breathing disorders.
Measured: 1 year
Recording of light sleep stage
The Xiaomi Mi Smart Band 8 will record the duration of light sleep, measured in minutes, to assist in estimating and detecting potential sleep-related breathing disorders.
Measured: 1 year
Recording of REM sleep stage
The Xiaomi Mi Smart Band 8 will record the duration of the REM sleep stage, measured in minutes, to help estimate and detect potential sleep-related breathing disorders.
Measured: 1 year
Recording of time awake after sleep onset
The Xiaomi Mi Smart Band 8 will record the time spent awake after sleep onset, measured in minutes, to assist in estimating and detecting potential sleep-related breathing disorders.
Measured: 1 year
Secondary outcomes (8)
Tracking of step count
The Xiaomi Mi Smart Band 8 device will track the total number of steps taken by the participant throughout a 24-hour period. The data will be used to assess physical activity levels and will be recorded as the total step count during the monitoring period.
Measured: 1 year
Tracking of distance
The Xiaomi Mi Smart Band 8 device will measure the total distance covered by the participant, recorded in meters.
Measured: 1 year
Tracking of physical activity duration
The Xiaomi Mi Smart Band 8 device will track the total duration of physical activity, recorded in minutes.
Measured: 1 year
Monitoring of positional changes
The nocturnal polygraph will track changes in body position of participants. This data will help assess physical activity, rest patterns, and potential sleep-related issues. The changes in position will be recorded without a specific unit of measurement.
Measured: 1 year
Monitoring of body movements
The nocturnal polygraph will monitor and record body movements of the participants. These movements will be used to assess physical activity and rest patterns. The data will be recorded without a specific unit of measurement, focusing on the detection of movement occurrence and intensity.
Measured: 1 year
Recording of heart rate
Heart rate monitoring using the Xiaomi Mi Smart Band 8 device and nocturnal polygraph, to compare data from both devices. Both devices record the average heart rate, as well as the maximum and minimum (in BPM).
Measured: 1 year
Recording of oxygen saturation
Oxygen saturation using the Xiaomi Mi Smart Band 8 device and nocturnal polygraph, to compare data from both devices. Both devices record the average oxygen saturation, as well as the maximum and minimum (in percentage).
Measured: 1 year
Sleep quality and habits measured by a sleep questionnaire
This custom-designed questionnaire includes questions related to bedtime and wake-up time, time taken to fall asleep, number of nighttime awakenings, reasons for waking up, perceived sleep quality, pre-sleep activities, and perceived stress levels during the day. It also includes items assessing the quality and quantity of sleep using a 6-point Likert scale, ranging from 0 (strongly disagree) to 5 (strongly agree). The total score ranges from 0 to 45, with higher scores indicating a greater perception of sleep quality and quantity.
Measured: 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted23 Sep 2024
- Study start18 Feb 2025
- Primary completion18 Jan 2026
- Study completion18 Jan 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (18)Papers the sponsor has linked to this study.
- Other trials for Breathing-Related 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
- Cross-sectional
- Enrolment
- 300 participants (actual)
Sponsor and investigators
- Lead sponsor
- Universidade da Coruña
- Sponsor type
- University, hospital or other
- Collaborators
- Center on Information and Communication Technologies, NeumoVigo I+i research group, Hospital Álvaro Cunqueiro, TALIONIS research group
- Responsible party
- Principal investigator, Patricia Concheiro Moscoso, Universidade da Coruña
- Investigators
- Patricia Concheiro-Moscoso, PhD, Principal investigator, CITIC-TALIONIS research group, Universidade da Coruña. Faculty of Health Sciences, Universidade da Coruña.Mar Mosteiro-Añon, Physician, Principal investigator, Hospital Álvaro CunqueiroJosé Alberto Fernández-Villar, PhD, Physician, Study chair, NeumoVigo I+i. Hospital Álvaro Cunqueiro.Javier Pereira, PhD, Study chair, CITIC-TALIONIS research group, Universidade da Coruña. Faculty of Health Sciences, Universidade da Coruña.María Luisa Torres-Durán, PhD, Physician, Study chair, NeumoVigo I+i. Hospital Álvaro Cunqueiro.Betania Groba, PhD, Study chair, CITIC-TALIONIS research group, Universidade da Coruña. Faculty of Health Sciences, Universidade da Coruña.Manuel Casal-Guisande, PhD, Study chair, NeumoVigo I+i. Hospital Álvaro Cunqueiro.
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06606691
- Sponsor's protocol ID
- 2024/260
- Acronym
- ReSTech
- Status last verified
- Jun 2025
- First submitted
- 16 Sep 2024
- Last updated
- 28 Apr 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Publications
Lujan MR, Perez-Pozuelo I, Grandner MA. Past, Present, and Future of Multisensory Wearable Technology to Monitor Sleep and Circadian Rhythms. Front Digit Health. 2021 Aug 16;3:721919. doi: 10.3389/fdgth.2021.721919. eCollection 2021.
PubMed 34713186de Zambotti M, Cellini N, Goldstone A, Colrain IM, Baker FC. Wearable Sleep Technology in Clinical and Research Settings. Med Sci Sports Exerc. 2019 Jul;51(7):1538-1557. doi: 10.1249/MSS.0000000000001947.
PubMed 30789439Gruwez A, Bruyneel AV, Bruyneel M. The validity of two commercially-available sleep trackers and actigraphy for assessment of sleep parameters in obstructive sleep apnea patients. PLoS One. 2019 Jan 9;14(1):e0210569. doi: 10.1371/journal.pone.0210569. eCollection 2019.
PubMed 30625225Perez-Pozuelo I, Zhai B, Palotti J, Mall R, Aupetit M, Garcia-Gomez JM, Taheri S, Guan Y, Fernandez-Luque L. The future of sleep health: a data-driven revolution in sleep science and medicine. NPJ Digit Med. 2020 Mar 23;3:42. doi: 10.1038/s41746-020-0244-4. eCollection 2020.
PubMed 32219183Espinosa MA, Ponce P, Molina A, Borja V, Torres MG, Rojas M. Advancements in Home-Based Devices for Detecting Obstructive Sleep Apnea: A Comprehensive Study. Sensors (Basel). 2023 Nov 30;23(23):9512. doi: 10.3390/s23239512.
PubMed 38067885Teplitzky TB, Zauher AJ, Isaiah A. Alternatives to Polysomnography for the Diagnosis of Pediatric Obstructive Sleep Apnea. Diagnostics (Basel). 2023 Jun 3;13(11):1956. doi: 10.3390/diagnostics13111956.
PubMed 37296808Concheiro-Moscoso P, Groba B, Alvarez-Estevez D, Miranda-Duro MDC, Pousada T, Nieto-Riveiro L, Mejuto-Muino FJ, Pereira J. Quality of Sleep Data Validation From the Xiaomi Mi Band 5 Against Polysomnography: Comparison Study. J Med Internet Res. 2023 May 19;25:e42073. doi: 10.2196/42073.
PubMed 37204853Hashimoto Y, Sakai R, Ikeda K, Fukui M. Association between sleep disorder and quality of life in patients with type 2 diabetes: a cross-sectional study. BMC Endocr Disord. 2020 Jun 30;20(1):98. doi: 10.1186/s12902-020-00579-4.
PubMed 32605640Lyons MM, Bhatt NY, Pack AI, Magalang UJ. Global burden of sleep-disordered breathing and its implications. Respirology. 2020 Jul;25(7):690-702. doi: 10.1111/resp.13838. Epub 2020 May 21.
PubMed 32436658Kang JM, Kang SG, Cho SJ, Lee YJ, Lee HJ, Kim JE, Shin SH, Park KH, Kim ST. The quality of life of suspected obstructive sleep apnea patients is related to their subjective sleep quality rather than the apnea-hypopnea index. Sleep Breath. 2017 May;21(2):369-375. doi: 10.1007/s11325-016-1427-8. Epub 2016 Nov 4.
PubMed 27815846Chen L, Bai C, Zheng Y, Wei L, Han C, Yuan N, Ji D. The association between sleep architecture, quality of life, and hypertension in patients with obstructive sleep apnea. Sleep Breath. 2023 Mar;27(1):191-203. doi: 10.1007/s11325-022-02589-z. Epub 2022 Mar 23.
PubMed 35322331Morsy NE, Farrag NS, Zaki NFW, Badawy AY, Abdelhafez SA, El-Gilany AH, El Shafey MM, Pandi-Perumal SR, Spence DW, BaHammam AS. Obstructive sleep apnea: personal, societal, public health, and legal implications. Rev Environ Health. 2019 Jun 26;34(2):153-169. doi: 10.1515/reveh-2018-0068.
PubMed 31085749Borsoi L, Armeni P, Donin G, Costa F, Ferini-Strambi L. The invisible costs of obstructive sleep apnea (OSA): Systematic review and cost-of-illness analysis. PLoS One. 2022 May 20;17(5):e0268677. doi: 10.1371/journal.pone.0268677. eCollection 2022.
PubMed 35594257Kaufmann CN, Susukida R, Depp CA. Sleep apnea, psychopathology, and mental health care. Sleep Health. 2017 Aug;3(4):244-249. doi: 10.1016/j.sleh.2017.04.003. Epub 2017 May 26.
PubMed 28709510K Pavlova M, Latreille V. Sleep Disorders. Am J Med. 2019 Mar;132(3):292-299. doi: 10.1016/j.amjmed.2018.09.021. Epub 2018 Oct 4.
PubMed 30292731
Study at a glance
From the registry record, last updated by the sponsor on 28 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Wearable Technology in the Detection and Evaluation of Sleep-Related Breathing Disorders
- ClinicalTrials.gov ID
- NCT06606691
- Acronym / sponsor ID
- ReSTech / 2024/260
- Keywords
- Participatory Health, Internet of Things, Sleep, Polygraphy, Wearable devices, Occupational Performance
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 300 participants (actual)
- Lead sponsor
- Universidade da CoruñaUniversity, hospital or other
- Collaborators
- Center on Information and Communication Technologies, NeumoVigo I+i research group, Hospital Álvaro Cunqueiro, TALIONIS research group
- Study start
- 18 Feb 2025 (actual)
- Primary completion
- 18 Jan 2026 (actual)
- Study completion
- 18 Jan 2026 (actual)
- First posted
- 23 Sep 2024 (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.
This project is an observational study that aims to evaluate the accuracy of wearable devices in detecting potential sleep-related breathing disorders (SRBD) in individuals visiting the Sleep-Related Breathing Disorders and Home Ventilation Unit. The main goal of the study is to determine if wearable devices, like sleep and activity-tracking wristbands and watches, can effectively supplement the detection of these disorders.
The study will analyze various variables related to sleep quality and quantity. Participants will be asked to wear a Xiaomi Mi Band 8 device during an overnight hospital polygraphy test, which will be conducted for one day in their usual daily environment. Additionally, at the beginning of their participation, they will need to complete a questionnaire collecting information about sociodemographic variables, daily habits, routines, and their assessment using the Epworth Sleepiness Scale.
After completing the polygraphy test and using the Xiaomi device, participants will be required to answer another questionnaire addressing aspects related to their sleep quality and habits during this period.
Detailed description
In recent years, sleep disorders have gained importance due to their high prevalence and impact on daily life, affecting people\'s ability to perform daily tasks and reducing quality of life. These disorders include difficulties falling asleep, respiratory interruptions, and poor sleep quality, with sleep-related breathing disorders (SRBD), such as obstructive sleep apnea (OSA), being particularly significant. OSA, which involves repeated airway obstructions during sleep, is especially common in older adults, individuals with obesity, and men, but it remains frequently underdiagnosed.
SRBD not only disrupts sleep but also increases the risk of chronic conditions like diabetes, hypertension, and strokes while creating an economic burden due to higher demand for medical resources. Their effects on physical and mental health lead to fatigue, reduced productivity, workplace accidents, and even disability, highlighting the need for more efficient diagnostic and management tools.
While polysomnography (PSG) is the gold standard for diagnosing sleep disorders, its high cost and invasive nature limit its accessibility. Wearable devices, such as wristbands and watches, offer a more accessible and non-invasive alternative, providing real-time data on sleep, heart rate, and activity. Though promising, these devices still require further research to confirm their accuracy in detecting SRBD. This project aims to evaluate the effectiveness of wearables as complementary tools in diagnosing and managing these disorders. Specifically, it has the following specific objectives: (1) To assess the accuracy, specificity, and sensitivity of wearable devices, such as wristbands and watches, in measuring blood oxygen saturation, heart rate, and activity, compared to nocturnal polygraphy. (2) To analyze the effectiveness of these devices in identifying individuals with potential sleep-related breathing disorders (SRBD) using unsupervised learning techniques. (3) To evaluate the impact and performance of an Artificial Intelligence model for detecting and classifying potential SRBD.
Study design
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Nocturnal polygraphy study participants | – | Device: Xiaomi Mi Smart Band 8This project aims to study approximately 263 individuals from different age groups and genders who are suspected of having sleep-related breathing disorders. The participants will be those referred for a nocturnal polygraphy study at the Sleep-Related Breathing Disorders and Home Ventilation Unit. During the polygraph test, participants will also wear the Xiaomi Mi Smart Band 8 wearable device to compare its accuracy in measuring sleep parameters, oxygen saturation, and heart rate against the polygraphy results. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Adult population with a potential sleep-related breathing disorder.
Key inclusion criteria (2 listed)
- Be at least 18 years of age or older.
- Attend the Sleep Respiratory Disorders and Home Ventilation Unit for the polygraphy test.
Key exclusion criteria (2 listed)
- Have significant health complications that hinder active participation in the study.
- Present skin hypersensitivity or a known allergy to the material used in the covers or straps of the wearable devices that will be used as one of the measurement instruments in the study.
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 Mi Smart Band 8The wearable device, Xiaomi Mi Smart Band 8, will be used solely for observational purposes to assess its accuracy in measuring sleep parameters, oxygen saturation, and heart rate in comparison to nocturnal polygraphy. Participants are receiving routine care as prescribed by their clinicians, and the wearable device is not part of their medical treatment but is being observed alongside standard polygraphy tests. | Device | Nocturnal polygraphy study participants |
Primary outcome
Recording of deep sleep stage
Time frame: 1 year
The Xiaomi Mi Smart Band 8 will record the duration of deep sleep, measured in minutes, to help estimate and identify potential sleep-related breathing disorders.
Recording of light sleep stage
Time frame: 1 year
The Xiaomi Mi Smart Band 8 will record the duration of light sleep, measured in minutes, to assist in estimating and detecting potential sleep-related breathing disorders.
Recording of REM sleep stage
Time frame: 1 year
The Xiaomi Mi Smart Band 8 will record the duration of the REM sleep stage, measured in minutes, to help estimate and detect potential sleep-related breathing disorders.
Recording of time awake after sleep onset
Time frame: 1 year
The Xiaomi Mi Smart Band 8 will record the time spent awake after sleep onset, measured in minutes, to assist in estimating and detecting potential sleep-related breathing disorders.
8 secondary outcomes
Tracking of step count
Time frame: 1 year
Tracking of distance
Time frame: 1 year
Tracking of physical activity duration
Time frame: 1 year
Monitoring of positional changes
Time frame: 1 year
Monitoring of body movements
Time frame: 1 year
Recording of heart rate
Time frame: 1 year
Recording of oxygen saturation
Time frame: 1 year
Sleep quality and habits measured by a sleep questionnaire
Time frame: 1 year
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 28 Apr 2026.
- Background: PubMed 34713186Lujan MR, Perez-Pozuelo I, Grandner MA. Past, Present, and Future of Multisensory Wearable Technology to Monitor Sleep and Circadian Rhythms. Front Digit Health. 2021 Aug 16;3:721919. doi: 10.3389/fdgth.2021.721919. eCollection 2021.
- Background: PubMed 30789439de Zambotti M, Cellini N, Goldstone A, Colrain IM, Baker FC. Wearable Sleep Technology in Clinical and Research Settings. Med Sci Sports Exerc. 2019 Jul;51(7):1538-1557. doi: 10.1249/MSS.0000000000001947.
- Background: PubMed 30625225Gruwez A, Bruyneel AV, Bruyneel M. The validity of two commercially-available sleep trackers and actigraphy for assessment of sleep parameters in obstructive sleep apnea patients. PLoS One. 2019 Jan 9;14(1):e0210569. doi: 10.1371/journal.pone.0210569. eCollection 2019.
- Background: PubMed 32219183Perez-Pozuelo I, Zhai B, Palotti J, Mall R, Aupetit M, Garcia-Gomez JM, Taheri S, Guan Y, Fernandez-Luque L. The future of sleep health: a data-driven revolution in sleep science and medicine. NPJ Digit Med. 2020 Mar 23;3:42. doi: 10.1038/s41746-020-0244-4. eCollection 2020.
- Background: PubMed 38067885Espinosa MA, Ponce P, Molina A, Borja V, Torres MG, Rojas M. Advancements in Home-Based Devices for Detecting Obstructive Sleep Apnea: A Comprehensive Study. Sensors (Basel). 2023 Nov 30;23(23):9512. doi: 10.3390/s23239512.
- Background: PubMed 37296808Teplitzky TB, Zauher AJ, Isaiah A. Alternatives to Polysomnography for the Diagnosis of Pediatric Obstructive Sleep Apnea. Diagnostics (Basel). 2023 Jun 3;13(11):1956. doi: 10.3390/diagnostics13111956.
- Background: PubMed 37204853Concheiro-Moscoso P, Groba B, Alvarez-Estevez D, Miranda-Duro MDC, Pousada T, Nieto-Riveiro L, Mejuto-Muino FJ, Pereira J. Quality of Sleep Data Validation From the Xiaomi Mi Band 5 Against Polysomnography: Comparison Study. J Med Internet Res. 2023 May 19;25:e42073. doi: 10.2196/42073.
- Background: PubMed 32605640Hashimoto Y, Sakai R, Ikeda K, Fukui M. Association between sleep disorder and quality of life in patients with type 2 diabetes: a cross-sectional study. BMC Endocr Disord. 2020 Jun 30;20(1):98. doi: 10.1186/s12902-020-00579-4.
- Background: PubMed 32436658Lyons MM, Bhatt NY, Pack AI, Magalang UJ. Global burden of sleep-disordered breathing and its implications. Respirology. 2020 Jul;25(7):690-702. doi: 10.1111/resp.13838. Epub 2020 May 21.
- Background: PubMed 27815846Kang JM, Kang SG, Cho SJ, Lee YJ, Lee HJ, Kim JE, Shin SH, Park KH, Kim ST. The quality of life of suspected obstructive sleep apnea patients is related to their subjective sleep quality rather than the apnea-hypopnea index. Sleep Breath. 2017 May;21(2):369-375. doi: 10.1007/s11325-016-1427-8. Epub 2016 Nov 4.
- Background: PubMed 35322331Chen L, Bai C, Zheng Y, Wei L, Han C, Yuan N, Ji D. The association between sleep architecture, quality of life, and hypertension in patients with obstructive sleep apnea. Sleep Breath. 2023 Mar;27(1):191-203. doi: 10.1007/s11325-022-02589-z. Epub 2022 Mar 23.
- Background: PubMed 31085749Morsy NE, Farrag NS, Zaki NFW, Badawy AY, Abdelhafez SA, El-Gilany AH, El Shafey MM, Pandi-Perumal SR, Spence DW, BaHammam AS. Obstructive sleep apnea: personal, societal, public health, and legal implications. Rev Environ Health. 2019 Jun 26;34(2):153-169. doi: 10.1515/reveh-2018-0068.
- 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.
Patricia Concheiro-Moscoso, PhD principal investigator
CITIC-TALIONIS research group, Universidade da Coruña. Faculty of Health Sciences, Universidade da Coruña.
Mar Mosteiro-Añon, Physician principal investigator
Hospital Álvaro Cunqueiro
José Alberto Fernández-Villar, PhD, Physician study chair
NeumoVigo I+i. Hospital Álvaro Cunqueiro.
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Breathing-Related Sleep Disorder and Sleep Disorder (Disorder), run by Universidade da Coruña at 2 sites 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 28 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites 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?
Recording of deep sleep stage (time frame: 1 year). The study lists 4 primary outcomes in all. 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 NCT06606691, which also lists 18 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 28 Apr 2026.