Consumer Sleep Research Articles

Sleep Monitoring in Athletes: Motivation, Methods, Miscalculations and Why it Matters.

It is increasingly recognised that many athletes have poor sleep quantity and/or quality despite the advances in knowledge regarding the importance of sleep for an athletic population. The majority of research in sleep assessment and treatment (within the general population) focuses on the medical disorder insomnia, and therefore may not be specifically relevant for athletes. Further, there are currently no guidelines for the standardisation of assessment, intervention, feedback and behaviour change strategies in athletes. This review outlines potential reasons for sleep disturbances in athletes, advantages and disadvantages of a range of methods to assess sleep (polysomnography, activity monitoring, consumer sleep technology, sleep diaries and questionnaires), considerations for the provision of feedback, a description of potential interventions and behaviour change challenges and strategies. The objective of this review is to provide practitioners with the latest scientific evidence in an area rapidly progressing in awareness, consumerism and athlete engagement.

The Importance of Evidence-Based Medicine and Clinical Guidelines: Meaningful and Clinically Actionable Information Cannot be Compromised for the Convenience of Consumer Sleep Data.

The Importance of Evidence-Based Medicine and Clinical Guidelines: Meaningful and Clinically Actionable Information Cannot be Compromised for the Convenience of Consumer Sleep Data.

Not All Errors Are Created Equal: Influence of User Characteristics on Measurement Errors of Consumer Wearable Devices for Sleep Tracking

Consumer sleep tracking devices are known to be inaccurate, but there is a lack of understanding of how user characteristics may affect the accuracy of these devices. This study aims to examine the effect of age, gender, subjective sleep quality, sleep hygiene and sleep structure on the accuracy of two consumer sleep trackers, i.e. Fitbit Charge 2 and Neuroon. Sleep data were collected from 27 healthy participants using consumer devices and a medical device concurrently. Analysis found that age, sleep hygiene and sleep structure were significantly associated to the accuracy of consumer sleep trackers, whereas no association was found on gender and subjective sleep quality. Both consumer devices had improved accuracy on total sleep time and sleep efficiency for participants who had longer, deeper and less interrupted sleep. Our findings suggest that consumer devices may not be suited for young adults and for people with short and fragmented sleep.

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

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.

Validity of Consumer Activity Wristbands and Wearable EEG for Measuring Overall Sleep Parameters and Sleep Structure in Free-Living Conditions.

Consumer sleep tracking technologies offer an unobtrusive and cost-efficient way to monitor sleep in free-living conditions. Technological advances in hardware and software have significantly improved the functionality of the new gadgets that recently appeared in the market. However, whether the latest gadgets can provide valid measurements on overall sleep parameters and sleep structure such as deep and REM sleep has not been examined. In this study, we aimed to investigate the validity of the latest consumer sleep tracking devices including an activity wristband Fitbit Charge 2 and a wearable EEG-based eye mask Neuroon in comparison to a medical sleep monitor. First, we confirmed that Fitbit Charge 2 can automatically detect the onset and offset of sleep with reasonable accuracy. Second, analysis found that both consumer devices produced comparable results in measuring total sleep duration and sleep efficiency compared to the medical device. In addition, Fitbit accurately measured the number of awakenings, while Neuroon with good signal quality had satisfactory performance on total awake time and sleep onset latency. However, measuring sleep structure including light, deep, and REM sleep remains to be challenging for both consumer devices. Third, greater discrepancies were observed between Neuroon and the medical device in nights with more disrupted sleep and when the signal quality was poor, but no trend was observed in Fitbit Charge 2. This study suggests that current consumer sleep tracking technologies may be immature for diagnosing sleep disorders, but they are reasonably satisfactory for general purpose and non-clinical use.

Sleep apps: what role do they play in clinical medicine?

Today's smartphones boast more computing power than the Apollo Guidance Computer. Given the ubiquity and popularity of smartphones, are we already carrying around miniaturized sleep labs in our pockets? There is still a lack of validation studies for consumer sleep technologies in general and apps for monitoring sleep in particular. To overcome this gap, multidisciplinary teams are needed that focus on feasibility work at the intersection of software engineering, data science and clinical sleep medicine. To date, no smartphone app for monitoring sleep through movement sensors has been successfully validated against polysomnography, despite the role and validity of actigraphy in sleep medicine having been well established. Missing separation of concerns, not methodology, poses the key limiting factor: The two essential steps in the monitoring process, data collection and scoring, are chained together inside a black box due to the closed nature of consumer devices. This leaves researchers with little room for influence nor can they access raw data. Multidisciplinary teams that wield complete power over the sleep monitoring process are sorely needed.

Statistical sleep pattern modelling for sleep quality assessment based on sound events.

A good sleep is important for a healthy life. Recently, several consumer sleep devices have emerged on the market claiming that they can provide personal sleep monitoring; however, many of them require additional hardware or there is a lack of scientific evidence regarding their reliability. In this paper we proposed a novel method to assess the sleep quality through sound events recorded in the bedroom. We used subjective sleep quality as training label, combined several machine learning approaches including kernelized self organizing map, hierarchical clustering and hidden Markov model, obtained the models to indicate the sleep pattern of specific quality level. The proposed method is different from traditional sleep stage based method, provides a new aspect of sleep monitoring that sound events are directly correlated with the sleep of a person.

The Past Is Prologue: The Future of Sleep Medicine.

The field of sleep medicine has gone through tremendous growth and development over a short period of time, culminating in recognition of the field as an independent medical subspecialty by the Accreditation Council for Graduate Medical Education (ACGME) and the American Board of Medical Specialties (ABMS). However, the fellowship training requirement that is now mandatory for sleep medicine board certification eligibility has had the unintended consequence of restricting the influx of young physicians to the field. In response to the potential workforce shortage confronting the field of sleep medicine, the American Academy of Sleep Medicine (AASM) board of directors has developed a comprehensive plan to strengthen the field by growing sleep fellowship programs, exploring novel sleep medicine training opportunities, creating and fostering the sleep team (with special emphasis on engagement of primary care providers), embracing the role of consumer sleep technologies, and expanding the reach of sleep specialists through telemedicine. The AASM plans summarized in this special article represent efforts to confront serious workforce challenges and turn them into opportunities that will improve the health of both our patients and our field.

Consumer Sleep Technologies: A Review of the Landscape.

To review sleep related consumer technologies, including mobile electronic device "apps," wearable devices, and other technologies. Validation and methodological transparency, the effect on clinical sleep medicine, and various social, legal, and ethical issues are discussed. We reviewed publications from the digital libraries of the Association for Computing Machinery, Institute of Electrical and Electronics Engineers, and PubMed; publications from consumer technology websites; and mobile device app marketplaces. Search terms included "sleep technology," "sleep app," and "sleep monitoring." Consumer sleep technologies are categorized by delivery platform including mobile device apps (integrated with a mobile operating system and utilizing mobile device functions such as the camera or microphone), wearable devices (on the body or attached to clothing), embedded devices (integrated into furniture or other fixtures in the native sleep environment), accessory appliances, and conventional desktop/website resources. Their primary goals include facilitation of sleep induction or wakening, self-guided sleep assessment, entertainment, social connection, information sharing, and sleep education. Consumer sleep technologies are changing the landscape of sleep health and clinical sleep medicine. These technologies have the potential to both improve and impair collective and individual sleep health depending on method of implementation.

Consumer sleep monitors: is there a baby in the bathwater?

The rapid expansion of consumer sleep devices is outpacing the validation data necessary to assess the potential use of these devices in clinical and research settings. Common sleep monitoring devices utilize a variety of sensors to track movement as well as cardiac and respiratory physiology. The variety of sensors and user-specific factors offer the potential, at least theoretically, for clinically relevant information. We describe the current challenges for interpretation of consumer sleep monitoring data, since the devices are mainly used in non-medical contexts (consumer use) although medically-definable sleep disorders may commonly occur in this setting. A framework for addressing questions of how certain devices might be useful is offered. We suggest that multistage validation efforts are crucially needed, from the level of sensor data and algorithm output, to extrapolations beyond healthy adults and into other populations and real-world environments.

Consumer Sleep Apps: When it Comes to the Big Picture, it's All About the Frame.

Consumer Sleep Apps: When it Comes to the Big Picture, it's All About the Frame.