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Cited by 27Obstructive Sleep Apnea ResearchHealthcare RegulationHealthcare Technology and Patient Monitoring

FDA-Cleared Home Sleep Apnea Testing Devices

Open access
Park, Ji Hyeun, Wang, Changwon, Shin, Hangsik·2024·npj Digital Medicine
DOI 10.1038/s41746-024-01112-wPMC PMC11091199
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Abstract

The demand for home sleep apnea testing (HSAT) devices is escalating, particularly in the context of the coronavirus 2019 (COVID-19) pandemic. The absence of standardized development and verification procedures poses a significant challenge. This study meticulously analyzed the approval process characteristics of HSAT devices by the U.S. Food and Drug Administration (FDA) from September 1, 2003, to September 1, 2023, with a primary focus on ensuring safety and clinical effectiveness. We examined 58 reports out of 1046 that underwent FDA clearance via the 510(k) and de novo pathways. A substantial surge in certifications after the 2022 pandemic was observed. Type-3 devices dominated, signifying a growing trend for both home and clinical use. Key measurement items included respiration and sleep analysis, with the apnea–hypopnea index (AHI) and sleep stage emerging as pivotal indicators. The majority of FDA-cleared HSAT devices adhered to electrical safety and biocompatibility standards. Critical considerations encompass performance and function testing, usability, and cybersecurity. This study emphasized the nearly indispensable role of clinical trials in ensuring the clinical effectiveness of HSAT devices. Future studies should propose guidances that specify stringent requirements, robust clinical trial designs, and comprehensive performance criteria to guarantee the minimum safety and clinical effectiveness of HSATs.

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  • In HSAT devices, usability testing helps prevent errors such as incorrect sensor placement or failure to activate the device due to unclear displays or inadequate instructions.

    “In HSAT devices, usability testing helps prevent errors such as incorrect sensor placement or failure to activate the device due to unclear displays or inadequate instructions [328].”

    From Toward Safer Diagnoses: A SEIPS-Based Narrative Review of Diagnostic Errors (2026) · cites this paper as [328]

    The Discussion (page not specified) links usability-related specifications and interface design to minimizing usage errors in HSAT devices. It does not identify incorrect sensor placement, failure to activate a device, unclear displays, or inadequate instructions as examples, nor does it specifically assess whether usability testing prevents those errors. (LLM, conf=0.84)

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References 31 · Cited by 27

Research works printed but not linked: 28

  1. [2]Chervin RD Sleepiness, fatigue, tiredness, and lack of energy in obstructive sleep apnea Chest 2000 118 372 379 10.1378/chest.118.2.372 10936127 · DOI · Paper page
  2. [3]Chokroverty S Overview of sleep & sleep disorders Indian J. Med. Res. 2010 131 126 140 20308738
  3. [4]Franklin KA Lindberg E Obstructive sleep apnea is a common disorder in the population—a review on the epidemiology of sleep apnea J. Thorac. Dis. 2015 7 1311 26380759 PMC4561280
  4. [5]Reichmuth KJ Austin D Skatrud JB Young T Association of sleep apnea and type II diabetes: a population-based study Am. J. Respiratory Crit. care Med. 2005 172 1590 1595 10.1164/rccm.200504-637OC PMC2718458 16192452 · DOI
  5. [6]Reutrakul S Mokhlesi B Obstructive sleep apnea and diabetes: a state of the art review Chest 2017 152 1070 1086 10.1016/j.chest.2017.05.009 28527878 PMC5812754 · DOI · Paper page
  6. [7]Senaratna CV Prevalence of obstructive sleep apnea in the general population: a systematic review Sleep. Med. Rev. 2017 34 70 81 10.1016/j.smrv.2016.07.002 27568340 · DOI · Paper page
  7. [8]Van Ryswyk E Mukherjee S Chai-Coetzer CL Vakulin A McEvoy RD Sleep disorders, including sleep apnea and hypertension Am. J. Hypertens. 2018 31 857 864 29788034
  8. [10]Lehrer HM Comparing polysomnography, actigraphy, and sleep diary in the home environment: The Study of Women’s Health Across the Nation (SWAN) Sleep Study Sleep. Adv. 2022 3 zpac001 10.1093/sleepadvances/zpac001 35296109 PMC8918428 · DOI
  9. [11]Dredla BK Castillo PR Out of the laboratory and into the home: home testing for sleep apnea and other sleep disorders J. Clin. Neurophysiol. 2023 40 198 202 10.1097/WNP.0000000000000776 36872498 · DOI
  10. [12]Massie F An evaluation of the NightOwl home sleep apnea testing system J. Clin. Sleep. Med. 2018 14 1791 1796 10.5664/jcsm.7398 30353811 PMC6175785 · DOI
  11. [13]Van Pee B A multicentric validation study of a novel home sleep apnea test based on peripheral arterial tonometry Sleep 2022 45 zsac028 10.1093/sleep/zsac028 35554589 PMC9113027 · DOI
  12. [14]Zhang XL Xiao Y Sleep health service in China during the coronavirus disease outbreak J. Clin. Sleep. Med. 2020 16 1221 1222 10.5664/jcsm.8472 32248894 PMC7954045 · DOI
  13. [15]Hug M Screening for obstructive sleep apnea among hospital outpatients PloS one 2018 13 e0198315 10.1371/journal.pone.0198315 29847582 PMC5976202 · DOI
  14. [16]Goldstein CA Karnib H Williams K Virk Z Shamim-Uzzaman A The utility of home sleep apnea tests in patients with low versus high pre-test probability for moderate to severe OSA Sleep. Breath. 2018 22 641 651 10.1007/s11325-017-1594-2 29168040 · DOI
  15. [17]Patel N A modified definition for obstructive sleep apnea in home sleep apnea testing after stroke or transient ischemic attack J. Stroke Cerebrovasc. Dis. 2018 27 1524 1532 10.1016/j.jstrokecerebrovasdis.2017.12.052 29428326 · DOI
  16. [18]Ichikawa M Diagnostic accuracy of home sleep apnea testing using peripheral arterial tonometry for sleep apnea: A systematic review and meta‐analysis J. Sleep. Res. 2022 31 e13682 10.1111/jsr.13682 35793907 · DOI
  17. [19]Ho V Crainiceanu CM Punjabi NM Redline S Gottlieb DJ Calibration model for apnea-hypopnea indices: impact of alternative criteria for hypopneas Sleep 2015 38 1887 1892 10.5665/sleep.5234 26564122 PMC4667391 · DOI · Paper page
  18. [20]Rosenberg RS Van Hout S The American Academy of Sleep Medicine inter-scorer reliability program: sleep stage scoring J. Clin. sleep. Med. 2013 9 81 87 10.5664/jcsm.2350 23319910 PMC3525994 · DOI · Paper page
  19. [21]Zhang X Process and outcome for international reliability in sleep scoring Sleep. Breath. 2015 19 191 195 10.1007/s11325-014-0990-0 24801137 · DOI
  20. [22]Qaseem A Diagnosis of obstructive sleep apnea in adults: a clinical practice guideline from the American College of Physicians Ann. Intern. Med. 2014 161 210 220 10.7326/M12-3187 25089864 · DOI
  21. [23]Kole A Home sleep apnea testing in the era of COVID-19: a community perspective J. Clin. Sleep. Med. 2020 16 1633 1633 10.5664/jcsm.8614 32501209 PMC7970616 · DOI
  22. [24]Chesson AL Jr. Berry RB Pack A Practice parameters for the use of portable monitoring devices in the investigation of suspected obstructive sleep apnea in adults Sleep 2003 26 907 913 10.1093/sleep/26.7.907 14655928 · DOI
  23. [25]Arcaini, P., Bonfanti, S., Gargantini, A., Mashkoor, A. & Riccobene, E. in 2015 ACM/IEEE International Conference on Formal Methods and Models for Codesign (MEMOCODE). 80-89 (IEEE)
  24. [26]Vockley M All charged up: The many challenges of battery maintenance Biomed. Instrum. Technol. 2014 48 86 96 10.2345/0899-8205-48.2.86 24712356 · DOI
  25. [28]Malhotra A Metrics of sleep apnea severity: beyond the apnea-hypopnea index Sleep 2021 44 zsab030 10.1093/sleep/zsab030 33693939 PMC8271129 · DOI · Paper page
  26. [29]Lipatov K Predictors of obstructive sleep apnea on a home sleep apnea test after a negative attended polysomnography J. Clin. Sleep. Med. 2018 14 1889 1894 10.5664/jcsm.7486 30373689 PMC6223554 · DOI
  27. [30]Collop NA Obstructive sleep apnea devices for out-of-center (OOC) testing: technology evaluation J. Clin. Sleep. Med. 2011 7 531 548 10.5664/JCSM.1328 22003351 PMC3190855 · DOI · Paper page
  28. [34]Standards of Practice Committee of the American Sleep Disorders Association. Practice parameters for the use of portable recording in the assessment of obstructive sleep apnea Sleep 1994 17 372 377 7973322

Authors
Park, J. H., Wang, C., & Shin, H.
Affiliations
Asan Medical Center (KR)
ORCID
Venue
npj Digital Medicine
Publisher
Springer Science and Business Media LLC
Published
2024-05-13
Volume
7
Issue
1
Pages
123-123
ISSN
2398-6352 (ISSN-L)
DOI
10.1038/s41746-024-01112-w
PMC
PMC11091199
OpenAlex
W4396852687
Cited by
27
References
31
Citations by year
2026: 13 · 2025: 14
FWCI
7.68
Type
journal article
Language
en
Open access
Licence
Locations
  • npj Digital Medicine (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
Ministry of Food and Drug Safety (RS-2023-00215716)
Topics
  • Health Sciences › Medicine › Physiology › Obstructive Sleep Apnea Research
  • Health Sciences › Health Professions › Health Information Management › Healthcare Regulation
  • Health Sciences › Medicine › Surgery › Healthcare Technology and Patient Monitoring
Keywords
home sleep apnea testing, FDA clearance, de novo pathway, apnea-hypopnea index, device safety, clinical effectiveness, clinical trials, COVID-19 pandemic, device regulation, cybersecurity, usability, biocompatibility

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