Wearable Technology in the Detection and Evaluation of Sleep-Related Breathing Disorders

NCT ID: NCT06606691

Last Updated: 2025-07-03

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

263 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-02-18

Study Completion Date

2025-12-31

Brief Summary

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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

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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.

Conditions

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Breathing-Related Sleep Disorder Sleep Disorder (Disorder)

Study Design

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Observational Model Type

COHORT

Study Time Perspective

CROSS_SECTIONAL

Study Groups

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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.

Xiaomi Mi Smart Band 8

Intervention Type DEVICE

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.

Interventions

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Xiaomi Mi Smart Band 8

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.

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

* Be at least 18 years of age or older.
* Attend the Sleep Respiratory Disorders and Home Ventilation Unit for the polygraphy test.

Exclusion Criteria

* 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.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Center on Information and Communication Technologies

OTHER

Sponsor Role collaborator

NeumoVigo I+i research group

UNKNOWN

Sponsor Role collaborator

Hospital Álvaro Cunqueiro

OTHER

Sponsor Role collaborator

TALIONIS research group

UNKNOWN

Sponsor Role collaborator

Universidade da Coruña

OTHER

Sponsor Role lead

Responsible Party

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Patricia Concheiro Moscoso

Postdoctoral Research in CITIC-TALIONIS research group, Universidade da Coruña. Faculty of Health Sciences, Universidade da Coruña. PhD in Health Sciences.

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Patricia Concheiro-Moscoso, PhD

Role: PRINCIPAL_INVESTIGATOR

CITIC-TALIONIS research group, Universidade da Coruña. Faculty of Health Sciences, Universidade da Coruña.

Mar Mosteiro-Añon, Physician

Role: PRINCIPAL_INVESTIGATOR

Hospital Álvaro Cunqueiro

José Alberto Fernández-Villar, PhD, Physician

Role: STUDY_CHAIR

NeumoVigo I+i. Hospital Álvaro Cunqueiro.

Javier Pereira, PhD

Role: STUDY_CHAIR

CITIC-TALIONIS research group, Universidade da Coruña. Faculty of Health Sciences, Universidade da Coruña.

María Luisa Torres-Durán, PhD, Physician

Role: STUDY_CHAIR

NeumoVigo I+i. Hospital Álvaro Cunqueiro.

Betania Groba, PhD

Role: STUDY_CHAIR

CITIC-TALIONIS research group, Universidade da Coruña. Faculty of Health Sciences, Universidade da Coruña.

Manuel Casal-Guisande, PhD

Role: STUDY_CHAIR

NeumoVigo I+i. Hospital Álvaro Cunqueiro.

Locations

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Hospital Álvaro Cunqueiro

Vigo, Pontevedra, Spain

Site Status NOT_YET_RECRUITING

Hospital Álvaro Cunqueiro

Vigo, Pontevedra, Spain

Site Status RECRUITING

Countries

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Spain

Central Contacts

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Patricia Concheiro-Moscoso, PhD

Role: CONTACT

0034981167000 ext. 5870

Mar Mosteiro-Añón, Physician

Role: CONTACT

Facility Contacts

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Patricia Concheiro-Moscoso, PhD

Role: primary

0034881010000 ext. 5870

Mar Mosteiro-Añón, Physician

Role: backup

References

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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.

Reference Type BACKGROUND
PMID: 34713186 (View on PubMed)

de 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.

Reference Type BACKGROUND
PMID: 30789439 (View on PubMed)

Gruwez 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.

Reference Type BACKGROUND
PMID: 30625225 (View on PubMed)

Perez-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.

Reference Type BACKGROUND
PMID: 32219183 (View on PubMed)

Espinosa 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.

Reference Type BACKGROUND
PMID: 38067885 (View on PubMed)

Teplitzky 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.

Reference Type BACKGROUND
PMID: 37296808 (View on PubMed)

Concheiro-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.

Reference Type BACKGROUND
PMID: 37204853 (View on PubMed)

Hashimoto 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.

Reference Type BACKGROUND
PMID: 32605640 (View on PubMed)

Lyons 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.

Reference Type BACKGROUND
PMID: 32436658 (View on PubMed)

Kang 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.

Reference Type BACKGROUND
PMID: 27815846 (View on PubMed)

Chen 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.

Reference Type BACKGROUND
PMID: 35322331 (View on PubMed)

Morsy 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.

Reference Type BACKGROUND
PMID: 31085749 (View on PubMed)

Borsoi 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.

Reference Type BACKGROUND
PMID: 35594257 (View on PubMed)

Kaufmann 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.

Reference Type BACKGROUND
PMID: 28709510 (View on PubMed)

K 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.

Reference Type BACKGROUND
PMID: 30292731 (View on PubMed)

Van Ryswyk E, Mukherjee S, Chai-Coetzer CL, Vakulin A, McEvoy RD. Sleep Disorders, Including Sleep Apnea and Hypertension. Am J Hypertens. 2018 Jul 16;31(8):857-864. doi: 10.1093/ajh/hpy082.

Reference Type BACKGROUND
PMID: 29788034 (View on PubMed)

Tester NJ, Foss JJ. Sleep as an Occupational Need. Am J Occup Ther. 2018 Jan/Feb;72(1):7201347010p1-7201347010p4. doi: 10.5014/ajot.2018.020651.

Reference Type BACKGROUND
PMID: 29280728 (View on PubMed)

Concheiro-Moscoso P, Pereira J, Mosteiro-Anon M, Torres-Duran M, Casal-Guisande M, Groba B. ReSTech project on Xiaomi wearable devices for monitoring and detecting obstructive sleep apnoea: observational study protocol. BMJ Open. 2025 Aug 13;15(8):e101824. doi: 10.1136/bmjopen-2025-101824.

Reference Type DERIVED
PMID: 40812810 (View on PubMed)

Other Identifiers

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2024/260

Identifier Type: -

Identifier Source: org_study_id

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