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Volume 14 No. 05
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Accepted Papers

Special Articles

Consumer Sleep Technology: An American Academy of Sleep Medicine Position Statement

Seema Khosla, MD1; Maryann C. Deak, MD2; Dominic Gault, MD3; Cathy A. Goldstein, MD4; Dennis Hwang, MD5; Younghoon Kwon, MD6; Daniel O'Hearn, MD7; Sharon Schutte-Rodin, MD8; Michael Yurcheshen, MD9; Ilene M. Rosen, MD, MS8; Douglas B. Kirsch, MD10; Ronald D. Chervin, MD, MS4; Kelly A. Carden, MD11; Kannan Ramar, MD12; R. Nisha Aurora, MD13; David A. Kristo, MD14; Raman K. Malhotra, MD15; Jennifer L. Martin, PhD16,17; Eric J. Olson, MD12; Carol L. Rosen, MD18; James A. Rowley, MD19
1North Dakota Center for Sleep, Fargo, North Dakota; 2eviCore Healthcare, Bluffton, South Carolina; 3Greenville Health System, University of South Carolina, Greenville, South Carolina; 4University of Michigan Sleep Disorders Center, Ann Arbor, Michigan; 5Southern California Permanente Medical Group, Kaiser Permanente Fontana Sleep Disorders Center, Fontana, California; 6Cardiovascular Division, Department of Medicine, University of Virginia, Charlottesville, Virginia; 7Department of Medicine, University of Washington, Seattle, Washington; 8Division of Sleep Medicine, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania; 9UR Medicine Sleep Center, Department of Neurology, University of Rochester School of Medicine and Dentistry, Rochester, New York; 10Carolinas Healthcare Medical Group Sleep Services, Charlotte, North Carolina; 11Saint Thomas Medical Partners - Sleep Specialists, Nashville, Tennessee; 12 Division of Pulmonary and Critical Care Medicine, Center for Sleep Medicine, Mayo Clinic, Rochester, Minnesota; 13Johns Hopkins University, School of Medicine, Baltimore, Maryland; 14University of Pittsburgh, Pittsburgh, Pennsylvania; 15Washington University Sleep Center, Washington University, St. Louis, Missouri; 16Veteran Affairs Greater Los Angeles Health System, North Hills, California; 17David Geffen School of Medicine, UCLA, Los Angeles, California; 18Department of Pediatrics, Case Western Reserve University, University Hospitals - Cleveland Medical Center, Cleveland, Ohio; 19Wayne State University, Detroit, Michigan


Consumer sleep technologies (CSTs) are widespread applications and devices that purport to measure and even improve sleep. Sleep clinicians may frequently encounter CST in practice and, despite lack of validation against gold standard polysomnography, familiarity with these devices has become a patient expectation. This American Academy of Sleep Medicine position statement details the disadvantages and potential benefits of CSTs and provides guidance when approaching patient-generated health data from CSTs in a clinical setting. Given the lack of validation and United States Food and Drug Administration (FDA) clearance, CSTs cannot be utilized for the diagnosis and/or treatment of sleep disorders at this time. However, CSTs may be utilized to enhance the patient-clinician interaction when presented in the context of an appropriate clinical evaluation. The ubiquitous nature of CSTs may further sleep research and practice. However, future validation, access to raw data and algorithms, and FDA oversight are needed.


Khosla S, Deak MC, Gault D, Goldstein CA, Hwang D, Kwon Y, O'Hearn D, Schutte-Rodin S, Yurcheshen M, Rosen IM, Kirsch DB, Chervin RD, Carden KA, Ramar K, Aurora RN, Kristo DA, Malhotra RK, Martin JL, Olson EJ, Rosen CL, Rowley JA; American Academy of Sleep Medicine Board of Directors. Consumer sleep technology: an American Academy of Sleep Medicine position statement. J Clin Sleep Med. 2018;14(5):877–880.


The American Academy of Sleep Medicine (AASM) is the leading clinical professional society dedicated to promotion of sleep health. The AASM improves sleep health and fosters high-quality, patient-centered care through advocacy, education, strategic research, and practice standards. The AASM endeavors to advance sleep health policy that improves the health and well-being of the public.

The number of connected devices surpassed the number of people in the United States in 2011.1 Consumer sleep technology (CST) utilization continues to increase, and sleep apps remain among the most popular apps downloaded for Apple and Android devices.2 See definitions in Table 1.



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Table 1


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As CST use increases, the sleep clinician encounters these products with increasing frequency in a typical sleep clinic visit. Patients are eager to share patient-generated health data (PGHD) with their sleep clinician to gain a deeper understanding of their sleep. There is an implicit expectation that the sleep clinician will be able to provide guidance to the patient regarding the utility and accuracy of sleep apps and gadgets, including wearables. As CST matures, sleep clinicians need to understand the wide range of CST-generated data and have a plan for how to utilize these data in the context of a clinical visit.


The number of available CSTs is continually growing, and a multitude of them claim to track and define sleep-related metrics, improve sleep quality, and even screen for sleep disorders. Unfortunately, minimal validation data exist regarding the ability of CSTs to accurately perform these functions. Sleep apps infrequently utilize empirical evidence or national guidelines to support their purported function or the information they disseminate.6 Rather than being sold as medical devices or apps, most CSTs are self-described “lifestyle/entertainment” devices that are not subject to United States Food and Drug Administration (FDA) oversight. The FDA has published a position statement with accompanying documents explaining how (and when) they will regulate mobile applications,7 and to date almost no mobile sleep apps have undergone such review. The lack of validation data and absence of FDA clearance raises concerns about the accuracy of CST data. The CST-generated data is not standardized, and raw data and proprietary algorithms are typically unavailable to clinicians. Despite the lack of validation and evidence-based guidelines, the clinician may be asked to review and render an opinion on these CST-generated data.


It is the position of the AASM that CST must be FDA cleared and rigorously tested against current gold standards if it is intended to render a diagnosis and/or treatment. Given the unknown potential of CST to measure sleep or assess for sleep disorders, these tools are not substitutes for medical evaluation. However, CSTs may be utilized to enhance the patient-clinician interaction when presented in the context of an appropriate clinical evaluation.


Sleep professionals must acknowledge CSTs as patients are gathering information at home with the aid of these devices, and then seeking the opinion of the sleep professional. In today's reality of ever-changing technology, sleep practitioners should have a working knowledge of epistemology and methodology of these technologies, even if they are unfamiliar with the specific devices. See Table 2 for guiding principles for these encounters. An initial schema for categorization of CSTs has been suggested by Watson and colleagues.8 Many CSTs share common traits and may utilize similar technology and reflect similar data. In addition, sleep clinicians should have an approach to the patient that recognizes the limitations of CSTs, yet capitalizes on their popularity and public interest in them. Table 3 highlights possible advantages and disadvantages of CSTs in the clinical care setting. In addition, it is quite likely as these devices become increasingly sophisticated that some may undergo validation to have a role in clinical care and scientific inquiries. The uses could range from individual patient management to “big data” collection through bioinformatics tools.

General principles of CST engagement.


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Table 2

General principles of CST engagement.

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Advantages and disadvantages of consumer technologies.


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Table 3

Advantages and disadvantages of consumer technologies.

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Patients' engagement with CST allows sleep professionals to have a dialogue with them about their expectations of the CST as well as their underlying sleep concerns. For example, a patient utilizing a sleep time tracking CST may have insomnia concerns and may be an ideal candidate for cognitive behavioral therapy for insomnia. A patient tracking their snoring may be at risk for obstructive sleep apnea and may require validated testing.

The “internet of things” is ubiquitous. The challenge is to provide a succinct yet flexible clinical guide for sleep professionals who are presented with CST data by a patient during a visit. Clinicians require a practical approach to discuss CST data and related sleep concerns with patients. A suggested approach is outlined in Table 4.

Guidance for clinicians encountering data in a clinical setting.


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Table 4

Guidance for clinicians encountering data in a clinical setting.

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How should sleep professionals navigate this ever-changing technology? The initial framework for categorization that has been suggested by Watson will certainly evolve as technologies continue to progress. Why should sleep professionals familiarize themselves with technology without validation data? Watson points out that patients may not be as concerned about this lack of validation. Furthermore, as consumers gain experience with wearables, limitations in the attainment of valid and actionable information may result in a more pragmatic assessment of their utility. While wearable technology has become well entrenched, there has been some transition in the market from the more fixed fitness and health-related single use gadgets to smartwatches and other multifunctional platforms, focused on entertainment and connectivity. Recognizing some of the limitations of wearables, “equity funding plummeted to around $300 million last year [2016] from the more than $1.3 billion the industry raised in 2014, according to the Sports Innovation Lab.”9 Consumers seem to recognize some shortcomings of consumer health-related technology.


Further CST data validation regarding device accuracy and application within clinical practice is necessary if these devices are to be considered part of medical evaluation and treatment. There is an evolving trend that blurs the lines between CSTs that are utilized for entertainment and those that are intended to render a diagnosis or treatment. How this new technology will affect the important outcomes of patient health, health care delivery and health care costs has yet to be determined. CSTs that intend to be diagnostic devices must fall under FDA regulations and must be rigorously tested against the current gold standards, while also understanding the availability and the limitations of current gold standards. The overwhelming amount of CST-derived PGHD available to clinicians and researchers has vast implications. In the clinical setting, mechanisms may be required for electronic health record integration, billing, and quality measurement. PGHD may transcend the one-on-one clinic visit and inform occupational health and safety programs as well as public policy. From a research standpoint, CST can generate exponentially larger data sets than traditional protocols, which may further the understanding of the role of sleep in health and disease. Due to CST popularity, future CSTs that are evidence based have wide-reaching potential to positively impact sleep.6 Recent Fitbit data exemplifies a potentially powerful CST to generate significantly larger scope of sleep data that would not otherwise be obtainable using conventional methods.10

With rapid advances in technology, medical professionals should have more open-mindedness and preparedness as we anticipate forthcoming changes in how we manage sleep disorders. Best practice would maintain an evidence-based, patient-centric approach while being receptive to changes brought by advances in technology.


CST is widespread and may improve patient engagement.14 Benefits of CST include increased awareness of the importance of sleep and the need for evaluation and treatment of sleep disorders. CSTs may enhance the patient-provider interaction and as such, are adjuncts to clinical practice. Therefore, an understanding of the capabilities and limitations of CST is crucial. Analysis of CST data requires consideration of manufacturer claims in the context of the biometrics assessed and thoughtful interpretation of the output. PGHD derived from CST should be considered in the context of a comprehensive sleep evaluation and should not replace validated diagnostic instruments. CST delivered interventions are not substitutes for treatments that have undergone rigorous scientific investigation. Despite their limitations, CSTs may allow for meaningful conversations with patients and increase active participation in their health care.


This position statement was developed by the AASM Presidential Technology Committee for the board of directors. It is published as an advisory that is to be used for educational and informational purposes only.


The board of directors and the committee thank AASM staff members who assisted with the development of this position statement.



Van Camp J. It's official: mobile devices outnumber people in the U.S. Digital Trends website. Published October 13, 2011. Accessed April 10, 2018.


Mobile App Ranking. SimilarWeb website. Accessed April 10, 2018.


App. website. Accessed April 10, 2018.


Beal V. Wearable technology. Webopedia website. Accessed April 10, 2018.


Office of the National Coordinator for Health Information Technology. Patient-generated health data. website. Accessed April 10, 2018.


Lee-Tobin PA, Ogeil RP, Savic M, Lubman DI. Rate my sleep: examining the information, function, and basis in empirical evidence within sleep applications for mobile devices. J Clin Sleep Med. 2017;13(11):1349–1354. [PubMed]


Mobile medical applications. U.S. Food & Drug Administration website. Updated March 26, 2018. Accessed April 10, 2018.


Ko PR, Kientz JA, Choe EK, Kay M, Landis CA, Watson NF. Consumer sleep technologies: a review of the landscape. J Clin Sleep Med. 2015;11(12):1455–1461. [PubMed Central][PubMed]


Tracy M. Technology Used to Track Players' Steps Now Charts Their Sleep, Too. New York Times website. Published September 22, 2017. Accessed April 10, 2018.


Pogue D. Exclusive: What Fitbit's 6 billion nights of sleep data reveals about us. Yahoo! Finance website: Published January 4, 2018. Accessed April 10, 2018.


Collop NA, Anderson WM, Boehlecke B, et al. Clinical guidelines for the use of unattended portable monitors in the diagnosis of obstructive sleep apnea in adult patients. J Clin Sleep Med. 2007;3(7):737–747. [PubMed Central][PubMed]


Patel P, Kim JY, Brooks LJ. Accuracy of a smartphone application in estimating sleep in children. Sleep Breath. 2017;21(2):505–511. [PubMed]


Examining Oversight of the Privacy & Security of Health Data Collected by Entities Not Regulated by HIPAA [pdf]. website. Published June 17, 2016. Accessed April 10, 2018.


Groshek MR, Oldenburg J, Sarasohn-Kahn J, Sitler B. mHealth App Essentials: Patient Engagement, Considerations, and Implementation. HiMSS website. Published February 20, 2015. Accessed April 10, 2018.