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Journal articles on the topic 'Consumer Sleep Technology'

Author: Grafiati

Published: 7 June 2025

Last updated: 17 July 2025

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1

Klosterman, Grace, Emily Stekl, Guido Simonelli, Jacob Collen, and Tracy Jill Doty. "270 Sleep Enhancement Technology: A Survey of Devices." Sleep 44, Supplement_2 (2021): A108. http://dx.doi.org/10.1093/sleep/zsab072.269.

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Abstract Introduction Innovations in consumer sleep technologies have risen exponentially and providers struggle to keep up with patient expectations in this arena. Although there is high quality data on the validity on commercial sleep monitoring devices, there has been a rise in devices for the explicit purpose of sleep enhancement. We sought to identify existing consumer sleep devices that claim to enhance sleep, provide a comprehensive review of the main characteristics of these devices, and look into the types of evidence the developers offered to support their claims. Methods Using a sco

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Arjun, Puri, Gandhi Sanjana, and Goldstein Gary. "Technology-based gamification in sleep medicine: A useful tool for physicians?" World Journal of Advanced Research and Reviews 22, no. 3 (2024): 1759–68. https://doi.org/10.5281/zenodo.14760452.

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In recent years, individuals’ nightly sleep quality, hygiene and duration have declined significantly. Gamification, the addition of game-based elements to non-game contexts, is an emerging tool in medical education and may be readily applicable to sleep medicine. Initially developed for use in retail and education, gamification increases productivity and knowledge acquisition and retention. Between the dates of 12/16/2023 and 03/27/2024, we conducted a focused review of eleven recent studies investigating the effectiveness, feasibility, and acceptability of technology-based gamification

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Khosla, Seema, Maryann C. Deak, Dominic Gault, et al. "Consumer Sleep Technology: An American Academy of Sleep Medicine Position Statement." Journal of Clinical Sleep Medicine 14, no. 05 (2018): 877–80. http://dx.doi.org/10.5664/jcsm.7128.

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de Zambotti, Massimiliano, Nicola Cellini, Luca Menghini, Michela Sarlo, and Fiona C. Baker. "Sensors Capabilities, Performance, and Use of Consumer Sleep Technology." Sleep Medicine Clinics 15, no. 1 (2020): 1–30. http://dx.doi.org/10.1016/j.jsmc.2019.11.003.

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Gahan, Luke, Samantha Wilson, Nathaniel F. Watson, and Elie Gottlieb. "0952 A Long Winter’s Sleep: What Does Big Data From Consumer Sleep Technology Tell Us?" SLEEP 46, Supplement_1 (2023): A419—A420. http://dx.doi.org/10.1093/sleep/zsad077.0952.

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Abstract Introduction Light is the most powerful zeitgeber influencing sleep-wake patterns, and winter’s shorter days have profound effects on mood, energy, and metabolic function. Here, we leverage big data from consumer sleep technology to examine the relationship between objectively measured sleep in winter versus summer months in the United States. Methods The dataset included 21,101 users residing in the US across 1,255,518 nights (age range: 17-90, mean age: 46.6 ± 16.7 years, 59% female). Data were extracted from 01 January 2019 until 31 August 2022. Seasons were defined according to th

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Raymann, Roy, Nathaniel Watson, Luke Gahan, and Elie Gottlieb. "0352 Compliance to Sleep Recommendations: A Big Data Analysis In Users of a Consumer Sleep Technology." Sleep 45, Supplement_1 (2022): A158—A159. http://dx.doi.org/10.1093/sleep/zsac079.349.

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Abstract Introduction The National Sleep Foundation has published sleep time duration (Hirshkowitz et al., 2015) and sleep quality (Ohayon et al., 2017) recommendations across the lifespan based on expert panel input. These recommendations offer sleep guidance to millions of individuals. Many individuals are using commercially available sleep tracking devices to measure their sleep. We analyzed the data of two non-contact radiofrequency sleep measurement devices (SleepScore Max (SleepScore Labs) and S+ (ResMed), both validated against PSG) to determine how well the users of these devices are s

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Crișan, Cătălina Angela, Roland Stretea, Maria Bonea, et al. "Deciphering the Link: Correlating REM Sleep Patterns with Depressive Symptoms via Consumer Wearable Technology." Journal of Personalized Medicine 14, no. 5 (2024): 519. http://dx.doi.org/10.3390/jpm14050519.

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This study investigates the correlation between REM sleep patterns, as measured by the Apple Watch, and depressive symptoms in an undiagnosed population. Employing the Apple Watch for data collection, REM sleep duration and frequency were monitored over a specified period. Concurrently, participants’ depressive symptoms were evaluated using standardized questionnaires. The analysis, primarily using Spearman’s correlation, revealed noteworthy findings. A significant correlation was observed between an increased REM sleep proportion and higher depressive symptom scores, with a correlation coeffi

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Gahan, Luke, Elie Gottlieb, Aman Aman, Nathaniel Watson, and Roy Raymann. "0330 Self-Reported Exercise and Objectively Measured Sleep: A Big Data Analysis Using Consumer Sleep Technology." Sleep 45, Supplement_1 (2022): A148—A149. http://dx.doi.org/10.1093/sleep/zsac079.328.

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Abstract Introduction Exercise is bidirectionally associated with sleep, whereby exercise can be an efficacious element of behavioural therapy for sleep, and longer sleep duration has been associated with increased physical activity. Given poor sleep and physical inactivity are each widely recognized as critical public health priorities, further research into the relationship between objective sleep and indices of exercise using ecologically-valid sleep measurement tools is warranted. Here, we examined the association between self-reported exercise intensity and duration, and objectively measu

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Stekl, Emily, Grace Klosterman, Guido Simonelli, Jacob Collen, and Tracy Doty. "0095 Sleep Enhancement Technology in 2021: An Updated Survey of Apps." Sleep 45, Supplement_1 (2022): A43. http://dx.doi.org/10.1093/sleep/zsac079.093.

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Abstract Introduction Commercially available smartphone apps that claim to improve sleep quantity and/or quality represent an ever-evolving and fast-growing market. Although a large body of work has validated the performance of sleep tracking technologies, there is little information regarding potential sleep enhancement technologies. Our study systematically surveyed currently available commercial sleep enhancement smartphone apps to provide details to inform both providers and patients alike, in addition to the healthy consumer market. Methods We systematically searched the Google Play Store

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Chong, Kimberly P. L., Julia Z. Guo, Xiaomeng Deng, and Benjamin K. P. Woo. "Consumer Perceptions of Wearable Technology Devices: Retrospective Review and Analysis." JMIR mHealth and uHealth 8, no. 4 (2020): e17544. http://dx.doi.org/10.2196/17544.

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Background Individuals of all ages are becoming more health conscious, and wearable technology devices (eg, Fitbit and Apple Watch) are becoming increasingly popular in encouraging healthy lifestyles. Objective The aim of this paper was to explore how consumers use wearable devices. Methods A retrospective review was done on the top-rated verified purchase reviews of the Fitbit One posted on Amazon.com between January 2014 and August 2018. Relevant themes were identified by qualitatively analyzing open-ended reviews. Results On retrieval, there were 9369 reviews with 7706 positive reviews and

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Gottlieb, Elie, Luke Gahan, Samantha Wilson, Nathaniel F. Watson, and Roy Raymann. "0279 Sleep Hygiene for Sleep Health in the General Population: What Does Data From Consumer Sleep Technology Tell Us?" SLEEP 46, Supplement_1 (2023): A124. http://dx.doi.org/10.1093/sleep/zsad077.0279.

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Abstract Introduction Despite being used and widely recommended since the 1970s, few studies have examined whether adherence to sleep hygiene practices affect objectively measured sleep in non-clinical populations. While individual components of sleep hygiene such as limiting caffeine and alcohol consumption are clearly related to sleep by plausible physiological and psychosocial mechanisms, the real-world evidence of overall sleep hygiene practices on sleep is surprisingly inconsistent. Here, we examined the association between self-reported sleep hygiene practices and objectively measured sl

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Gahan, L., M. Ruder, A. Raj, B. O’Mullane, and R. J. Raymann. "0443 Intra Week Sleep Patterns Analyzed Using Consumer Sleep Tracker Data." Sleep 43, Supplement_1 (2020): A170. http://dx.doi.org/10.1093/sleep/zsaa056.440.

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Abstract Introduction Big data collected using consumer sleep technology can provide objectively measured insights on sleep behavior in the real-life environment. It has the advantage over self-report data of being less prone to bias. Here we used a non-contact bio-motion sensor to remotely capture objective sleep data. We analyzed 168432 nights of sleep data to test if differences between weekday versus weekend sleep behavior, known from self-report, would still hold using objective data in a large population. Methods Sleep data was acquired using the SleepScore Max remote sleep sensor and in

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Rosa, Talita D., Jennifer Zitser, and Robson Capasso. "Consumer Technology for Sleep-Disordered Breathing: a Review of the Landscape." Current Otorhinolaryngology Reports 7, no. 1 (2019): 18–26. http://dx.doi.org/10.1007/s40136-019-00222-4.

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Khosla, Seema, and Emerson M. Wickwire. "Consumer sleep technology: accuracy and impact on behavior among healthy individuals." Journal of Clinical Sleep Medicine 16, no. 5 (2020): 665–66. http://dx.doi.org/10.5664/jcsm.8450.

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Raymann, Roy, Nyayabrata Nayak, Nathaniel Watson, Luke Gahan, and Elie Gottlieb. "0351 Towards Interpreting Consumer Sleep Data: Distributions of Sleep Scores." Sleep 45, Supplement_1 (2022): A158. http://dx.doi.org/10.1093/sleep/zsac079.348.

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Abstract Introduction With the rise of sleep measurement technology becoming widely available to the public, it has become apparent that traditional sleep metrics might not be best suited for a lay audience. Most consumer industry has started including a metric that would capture sleep quality, although the exact calculations of these scores remain proprietary. These novel outcome metrics require a set of reference values in order to become interpretable. Here, we provide reference values for the parameters SleepScore, BodyScore and MindScore as included in the SleepScore Labs non-contact radi

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Vallejo-Riveros, Sofia, Maria Jose Velasco-Burgos, Ana Sanchez-Birkhead, et al. "0382 A Community-Engaged Qualitative Study of Factors Affecting Sleep Among Hispanic/Latinos with Short Sleep Duration." SLEEP 48, Supplement_1 (2025): A166. https://doi.org/10.1093/sleep/zsaf090.0382.

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Abstract Introduction Despite having high prevalence of short sleep duration, poor sleep quality, and sleep disorders in adult Hispanics living in the US, there is limited understanding of the underlying barriers to sleep and effective interventions in these groups. This study aimed to increase understanding of sleep duration and attitudes toward sleep interventions among Hispanic adults. Methods We conducted 5 online focus group discussions with male and female participants aged 18-65 recruited from the Hispanic community who reported sleeping &lt; 7 hours per night. Interviewers utilized

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Kaufman, Matthew W., Maya Shetty, Chantal Nguyen, Jaden Abas, Michael Fredericson, and Jamie Zeitzer. "Focused Review of Sleep Wearable Technology and Its Application in Sports Performance." Current Sports Medicine Reports 24, no. 6 (2025): 171–76. https://doi.org/10.1249/jsr.0000000000001258.

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Abstract Sleep is a critical component of quality of life, recovery, and performance both physically and cognitively. Tracking sleep with wearables is increasingly prevalent among individuals; the data that are retrieved from these wearables, however, is of unclear relevance. To update this space, literature was reviewed to examine the implications for good and bad sleepers, the current shortcomings of wearables, their current status usage and literature reports in sports medicine, and the future benefits that these devices may have for athletes and nonathletes alike. Wearables have good perfo

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Devine, Jaime, Jake Choynowski, Steven Hursh, and Amany Farag. "0299 Sleep Hygiene in Nurses Using Data Collected from Consumer Sleep Technology (CST) with the SleepTank™ mobile app." SLEEP 46, Supplement_1 (2023): A132—A133. http://dx.doi.org/10.1093/sleep/zsad077.0299.

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Abstract Introduction Nurses are prone to fatigue and sleep disturbances due to extended hour or shiftwork schedules. Fatigue in nurses not only compromises their own health and safety, but jeopardizes patient care as well. Nurses' work hours and overtime are currently not federally regulated. Fatigue risk mitigation strategies for nurses would benefit from understanding the relationship between sleep duration and work patterns in order to develop tools and regulations to protect against fatigue in the nursing profession. Methods Thirteen (N=13) nurses wore a Fitbit Versa 2 and used the SleepT

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Cheng, Philip, Olivia Walch, Kevin Hannay, Thomas Roth, and Christopher Drake. "0004 Using Apple Watch to predict circadian phase in night shift workers." SLEEP 46, Supplement_1 (2023): A2. http://dx.doi.org/10.1093/sleep/zsad077.0004.

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Abstract Introduction A critical obstacle for circadian medicine is the lack of feasibility in measuring circadian phase in the clinic. Existing tools such as assessment of dim light melatonin onset (DLMO) are too resource intensive, especially in populations with extreme circadian disruption such as night shift workers. Recent studies have demonstrated the validity and feasibility of estimating circadian phase via mathematical modeling data collected with wearable technology. However, these studies have mostly relied on research grade devices (e.g., actigraphs) that have limited scalability.

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Devine, Jaime, Lindsay Schwartz, Jake Choynowski, and Steven Hursh. "0084 Consumer Sleep Technologies (CSTs) for Use in Real-World Sleep Research Environments: A Survey of Experts." Sleep 45, Supplement_1 (2022): A38. http://dx.doi.org/10.1093/sleep/zsac079.082.

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Abstract Introduction Consumer sleep technologies (CSTs) have been designed for the everyday consumer rather than as a reliable scientific tool, but are becoming sufficiently accurate for use in the research landscape. Despite the growing conversation about the viability of CSTs for research, manufacturers may not be interested in increasing scientific accuracy in their devices unless doing so is expected to result in greater consumer sales. To establish concensus opinion about important device features and economic demand for CSTs for sleep research, professional opinions from sleep medicine

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Stretea, R., Z. Milhem, M. Bonea, and C. A. Crișan. "Deciphering the link: correlating REM sleep patterns with depressive symptoms via consumer wearable technology." Neuroscience Applied 3 (2024): 104574. https://doi.org/10.1016/j.nsa.2024.104574.

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Wright, Stephen P., Tyish S. Hall Brown, Scott R. Collier, and Kathryn Sandberg. "How consumer physical activity monitors could transform human physiology research." American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 312, no. 3 (2017): R358—R367. http://dx.doi.org/10.1152/ajpregu.00349.2016.

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A sedentary lifestyle and lack of physical activity are well-established risk factors for chronic disease and adverse health outcomes. Thus, there is enormous interest in measuring physical activity in biomedical research. Many consumer physical activity monitors, including Basis Health Tracker, BodyMedia Fit, DirectLife, Fitbit Flex, Fitbit One, Fitbit Zip, Garmin Vivofit, Jawbone UP, MisFit Shine, Nike FuelBand, Polar Loop, Withings Pulse O2, and others have accuracies similar to that of research-grade physical activity monitors for measuring steps. This review focuses on the unprecedented o

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Atcherson, Samuel R. "Assistive Technology for Adults with Hearing Aids." Seminars in Hearing 43, no. 02 (2022): 079–84. http://dx.doi.org/10.1055/s-0042-1748873.

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AbstractAlthough there is a strong trend of satisfaction with hearing aids, recent consumer surveys indicate that there are still challenges with understanding speech in background noise and low penetration of wireless technologies using many modern-day communication and audio devices, such as smartphones, tablets, and computers. For some listening and communication settings, many patients could benefit from assistive technology that exceeds the capabilities of their hearing aids. When patients are not wearing their hearing aids, such as during sleep, concerns about environmental awareness and

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Kim, Ben, Sandra M. McKay, and Joon Lee. "Consumer-Grade Wearable Device for Predicting Frailty in Canadian Home Care Service Clients: Prospective Observational Proof-of-Concept Study." Journal of Medical Internet Research 22, no. 9 (2020): e19732. http://dx.doi.org/10.2196/19732.

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Background Frailty has detrimental health impacts on older home care clients and is associated with increased hospitalization and long-term care admission. The prevalence of frailty among home care clients is poorly understood and ranges from 4.0% to 59.1%. Although frailty screening tools exist, their inconsistent use in practice calls for more innovative and easier-to-use tools. Owing to increases in the capacity of wearable devices, as well as in technology literacy and adoption in Canadian older adults, wearable devices are emerging as a viable tool to assess frailty in this population. Ob

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Manea, Vlad, and Katarzyna Wac. "Co-Calibrating Physical and Psychological Outcomes and Consumer Wearable Activity Outcomes in Older Adults: An Evaluation of the coQoL Method." Journal of Personalized Medicine 10, no. 4 (2020): 203. http://dx.doi.org/10.3390/jpm10040203.

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Inactivity, lack of sleep, and poor nutrition predispose individuals to health risks. Patient-Reported Outcomes (PROs) assess physical behaviours and psychological states but are subject of self-reporting biases. Conversely, wearables are an increasingly accurate source of behavioural Technology-Reported Outcomes (TechROs). However, the extent to which PROs and TechROs provide convergent information is unknown. We propose the coQoL PRO-TechRO co-calibration method and report its feasibility, reliability, and human factors influencing data quality. Thirty-nine seniors provided 7.4 ± 4.4 PROs fo

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Olsen, M., H. Sorensen, P. Jennum, and E. Mignot. "1208 Sleep Stage Prediction And Sleep Disordered Breathing Detection Using Raw Actigraphy And Photoplethysmography From Wearable Consumer Device." Sleep 43, Supplement_1 (2020): A461—A462. http://dx.doi.org/10.1093/sleep/zsaa056.1202.

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Abstract Introduction Wearable, multisensory consumer devices that estimate sleep are prevalent and hold great potential. Most validated actigraphic prediction studies of sleep stages (SS) have only used low resolution (30 sec) data and the Cole-Kripke algorithm. Other algorithms are often proprietary and not accessible or validated. We present an automatic, data-driven deep learning algorithm that process raw actigraphy (ACC) and photoplethysmography (PPG) using a low-cost consumer device at high (25Hz) and low resolution to predict SS and to detect sleep disordered breathing (SDB) events. Me

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Richards, Kathy, Brian Cox, Vanessa Aguilar, et al. "SLEEP MEASUREMENT TECHNOLOGY IN THE 40 WINKS PRAGMATIC CLINICAL TRIAL: CHALLENGES AND SOLUTIONS." Innovation in Aging 8, Supplement_1 (2024): 421. https://doi.org/10.1093/geroni/igae098.1371.

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Abstract This presentation describes examples, challenges, and solutions for using technology as part of a pragmatic trial to both deliver a sleep promotion intervention and measure its outcomes. In this trial, target nursing home residents wear an actigraph on their wrist for one week. Actigraphs are a non-invasive way of monitoring activity and rest cycles. One effective and novel application of this technology is use of the actigraphy clinical report. As part of the intervention, the clinical report of the resident’s nighttime sleep, daytime napping, light exposure, and physical activity is

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Reithe, H., A. Erdal, JC Torrado, BS Husebo, and M. Patrascu. "P64: Wearable sensing technology for Parkinson’s disease: preliminary results from the DIGI.PARK pilot." International Psychogeriatrics 35, S1 (2023): 117–18. http://dx.doi.org/10.1017/s1041610223002454.

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Background:Assessment scales for motor symptoms in Parkinson’s disease (PD) lack the sensitivity and resolution to monitor symptoms over time. Wearable sensors in people with PD have shown potential to assess motor symptoms. The DIGI.PARK study explores the use of consumer- and research-grade wearables such as Fitbit Sense (FS), Oura ring (OR) and Empatica E4 (EM) to track behavioral patterns and symptoms of PD over time.Method:The DIGI.PARK pilot study (12.2021 to 12.2022) included N = 30 participants living in Bergen, Norway (N=15 persons with PD and N=15 controls). Outcome measures: self-re

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Frodi, Diana My, Vlad Manea, Søren Zöga Diederichsen, Jesper Hastrup Svendsen, Katarzyna Wac, and Tariq Osman Andersen. "Using Consumer-Wearable Activity Trackers for Risk Prediction of Life-Threatening Heart Arrhythmia in Patients with an Implantable Cardioverter-Defibrillator: An Exploratory Observational Study." Journal of Personalized Medicine 12, no. 6 (2022): 942. http://dx.doi.org/10.3390/jpm12060942.

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Ventricular arrhythmia (VA) is a leading cause of sudden death and health deterioration. Recent advances in predictive analytics and wearable technology for behavior assessment show promise but require further investigation. Yet, previous studies have only assessed other health outcomes and monitored patients for short durations (7–14 days). This study explores how behaviors reported by a consumer wearable can assist VA risk prediction. An exploratory observational study was conducted with participants who had an implantable cardioverter-defibrillator (ICD) and wore a Fitbit Alta HR consumer w

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Mathunjwa, Bhekumuzi M., Randy Yan Jie Kor, Wanida Ngarnkuekool, and Yeh-Liang Hsu. "A Comprehensive Review of Home Sleep Monitoring Technologies: Smartphone Apps, Smartwatches, and Smart Mattresses." Sensors 25, no. 6 (2025): 1771. https://doi.org/10.3390/s25061771.

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The home is an ideal setting for long-term sleep monitoring. This review explores a range of home-based sleep monitoring technologies, including smartphone apps, smartwatches, and smart mattresses, to assess their accuracy, usability, limitations, and how well they integrate with existing healthcare systems. This review evaluates 21 smartphone apps, 16 smartwatches, and nine smart mattresses through systematic data collection from academic literature, manufacturer specifications, and independent studies. Devices were assessed based on sleep-tracking capabilities, physiological data collection,

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Devine, Jaime K., Lindsay P. Schwartz, and Steven R. Hursh. "Technical, Regulatory, Economic, and Trust Issues Preventing Successful Integration of Sensors into the Mainstream Consumer Wearables Market." Sensors 22, no. 7 (2022): 2731. http://dx.doi.org/10.3390/s22072731.

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Sensors that track physiological biomarkers of health must be successfully incorporated into a fieldable, wearable device if they are to revolutionize the management of remote patient care and preventative medicine. This perspective article discusses logistical considerations that may impede the process of adapting a body-worn laboratory sensor into a commercial-integrated health monitoring system with a focus on examples from sleep tracking technology.

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Manalo, NC, J. Duffecy, M. Berendsen, I. Cheung, E. Lattie, and KG Baron. "1199 FEELING VALIDATED YET? A SCOPING REVIEW OF CONSUMER-TARGETED WEARABLE AND MOBILE TECHNOLOGY TO MEASURE AND IMPROVE SLEEP." Sleep 40, suppl_1 (2017): A447. http://dx.doi.org/10.1093/sleepj/zsx050.1198.

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Zambelli, Zoe, Cecilia E. Jakobsson, Laura Threadgold, Antonio R. Fidalgo, Elizabeth J. Halstead, and Dagmara Dimitriou. "Exploring the feasibility and acceptability of a sleep wearable headband among a community sample of chronic pain individuals: An at-home observational study." DIGITAL HEALTH 8 (January 2022): 205520762210975. http://dx.doi.org/10.1177/20552076221097504.

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Background Chronic pain conditions affect up to one third of the adult population in the United Kingdom. Sleep problems are prevalent and negatively impact quality of life. Lack of standardised tools for routine screening and assessment of sleep changes have been a barrier for sleep management. Novel sleep wearables offer an exciting and accessible way to measure sleep but have not been tested outside of the consumer-led landscape and are not commonly used in research and clinical settings. Aims The study aimed to explore the feasibility and acceptability of a sleep monitoring headband (Dreem

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Fanson, Freya, Devon Hansen, Elie Gottlieb, et al. "0375 Increased Engagement with a Tailored Sleep Guide is Associated with Reduced Variability in Sleep Efficiency in Chronic Insomnia." SLEEP 46, Supplement_1 (2023): A166—A167. http://dx.doi.org/10.1093/sleep/zsad077.0375.

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Abstract Introduction Insomnia is highly prevalent, but difficult to diagnose due to night-to-night sleep variability, and difficult to treat in part due to the lack of trained providers. Consumer sleep technology (CST) allows for longitudinal sleep monitoring in a natural environment. One such device, the Sleep Score Max (SleepScore Labs) combines longitudinal non-contact sleep tracking via radio-frequency biomotion sensor technology with an individualized sleep guide function, which provides tailored recommendations to improve sleep based on the user’s objectively measured sleep, bedroom env

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Watson, Nathaniel, Chris Fernandez, Sam Rusk, Yoav Nygate, Fred Turkington, and Justin Mortara. "426 Clinical Validation of A.I. Analysis of Photoplethysmogram (PPG) Based Sleep-Wake Staging, Total Sleep Time, and Respiratory Rate." Sleep 44, Supplement_2 (2021): A168—A169. http://dx.doi.org/10.1093/sleep/zsab072.425.

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Abstract Introduction The Photoplesthymogram (PPG) raw waveform is the basis for both the pulse rate and oximetry during polysomnography (PSG) and Home Sleep Apnea Tests (HSAT). The PPG has also recently become ubiquitous as a basis of continuous measurement for the most widely adopted consumer sleep technologies, particularly smart watches. In this study, we clinically validate AI performance for interoperable, PPG-based epoch-by-epoch Sleep-Wake staging (PPG-SW), Total Sleep Time (PPG-TST), and Respiratory Rate (PPG-RR), when compared to 1) PSG-based panel scoring by technologists (RPSGTs) a

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Khosla, Seema, Maryann C. Deak, Dominic Gault, et al. "Consumer Sleep Technologies: How to Balance the Promises of New Technology with Evidence-Based Medicine and Clinical Guidelines." Journal of Clinical Sleep Medicine 15, no. 01 (2019): 163–65. http://dx.doi.org/10.5664/jcsm.7598.

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Hassan, Lamiece, Alyssa Milton, Chelsea Sawyer, et al. "Utility of Consumer-Grade Wearable Devices for Inferring Physical and Mental Health Outcomes in Severe Mental Illness: Systematic Review." JMIR Mental Health 12 (January 7, 2025): e65143. https://doi.org/10.2196/65143.

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Background Digital wearable devices, worn on or close to the body, have potential for passively detecting mental and physical health symptoms among people with severe mental illness (SMI); however, the roles of consumer-grade devices are not well understood. Objective This study aims to examine the utility of data from consumer-grade, digital, wearable devices (including smartphones or wrist-worn devices) for remotely monitoring or predicting changes in mental or physical health among adults with schizophrenia or bipolar disorder. Studies were included that passively collected physiological da

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James, Peter. "Abstract IA05: Incorporating mobile health technology into a prospective cohort study to measure environment, physical activity, and sleep." Cancer Epidemiology, Biomarkers & Prevention 29, no. 9_Supplement (2020): IA05. http://dx.doi.org/10.1158/1538-7755.modpop19-ia05.

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Abstract Obesity is an established driver of cancer risk, and substantial evidence has identified inadequate physical activity and sleep as common risk factors. Inadequate physical activity contributes to over 12% of breast and colon cancers each year in the U.S. Furthermore, 10-20% of the general population experiences curtailed sleep and/or sleep disturbances, which have been associated with higher risk of breast, colon, prostate, and endometrial cancers. Geographic contextual measures, including neighborhood walkability and access to green space, have been demonstrated to affect physical ac

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Basingab, Mohammed Salem, Hatim Bukhari, Suhail H. Serbaya, et al. "AI-Based Decision Support System Optimizing Wireless Sensor Networks for Consumer Electronics in E-Commerce." Applied Sciences 14, no. 12 (2024): 4960. http://dx.doi.org/10.3390/app14124960.

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The purpose of this study is to investigate the potential of AI technology in developing a decision support system that can improve the effectiveness of wireless sensor networks (WSNs) in e-commerce, specifically in enhancing the features of consumer electronics. This research project is focused on optimizing wireless sensor networks for e-commerce consumer electronics by incorporating AI-based decision support systems. The primary objective of this study is to enhance energy efficiency and performance in online shopping platforms. Various algorithms and methodologies are proposed and assessed

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Ruder, M., H. M. Rus, A. Raj, et al. "0412 Parents Sleep Longer When School is Out for the Summer: Associations Among Parenthood, Gender, and Season." Sleep 43, Supplement_1 (2020): A157—A158. http://dx.doi.org/10.1093/sleep/zsaa056.409.

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Abstract Introduction Seasonal effects in sleep are often attributed to day length; however, change in obligatory daily activities might also have an impact on sleep behavior. Longitudinal measurement using consumer sleep technology enables the observation of patterns in sleep behavior in the home environment. We analyzed the impact of parenthood and gender on total sleep time (TST) over the summer break period using data collected in the home. Methods Sleep data were collected using the SleepScore mobile application from October 2018 through October 2019, with the summer break period defined

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Fonseka, Lakshan N., and Benjamin K. P. Woo. "Wearables in Schizophrenia: Update on Current and Future Clinical Applications." JMIR mHealth and uHealth 10, no. 4 (2022): e35600. http://dx.doi.org/10.2196/35600.

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Schizophrenia affects 1% of the world population and is associated with a reduction in life expectancy of 20 years. The increasing prevalence of both consumer technology and clinical-grade wearable technology offers new metrics to guide clinical decision-making remotely and in real time. Herein, recent literature is reviewed to determine the potential utility of wearables in schizophrenia, including their utility in diagnosis, first-episode psychosis, and relapse prevention and their acceptability to patients. Several studies have further confirmed the validity of various devices in their abil

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Wright, Stephen P., and Kathryn Sandberg. "2253." Journal of Clinical and Translational Science 1, S1 (2017): 40–41. http://dx.doi.org/10.1017/cts.2017.148.

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OBJECTIVES/SPECIFIC AIMS: To analyze how consumer physical activity monitors are currently used in biomedical research. METHODS/STUDY POPULATION: Searches were conducted in Ovid Medline, PubMed Medline, clinicaltrials.gov, and NIH RePORTER using search terms including Fitbit, Jawbone, Apple watch, Garmin, Polar, Microsoft band, Misfit, Nike, Withings, and Xiaomi. Results were quantitated by category: condition/topic, intervention, enrollment status, study type and design, age, grant mechanism, and primary outcome. RESULTS/ANTICIPATED RESULTS: Fitbit is used >80%. There are 127 clinical stud

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Barteit, Sandra, Valentin Boudo, Aristide Ouedraogo, et al. "Feasibility, acceptability and validation of wearable devices for climate change and health research in the low-resource contexts of Burkina Faso and Kenya: Study protocol." PLOS ONE 16, no. 9 (2021): e0257170. http://dx.doi.org/10.1371/journal.pone.0257170.

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As the epidemiological transition progresses throughout sub-Saharan Africa, life lived with diseases is an increasingly important part of a population’s burden of disease. The burden of disease of climate-sensitive health outcomes is projected to increase considerably within the next decades. Objectively measured, reliable population health data is still limited and is primarily based on perceived illness from recall. Technological advances like non-invasive, consumer-grade wearable devices may play a vital role in alleviating this data gap and in obtaining insights on the disease burden in vu

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Baron, Kelly Glazer, Jennifer Duffecy, Mark A. Berendsen, Ivy Cheung Mason, Emily G. Lattie, and Natalie C. Manalo. "Feeling validated yet? A scoping review of the use of consumer-targeted wearable and mobile technology to measure and improve sleep." Sleep Medicine Reviews 40 (August 2018): 151–59. http://dx.doi.org/10.1016/j.smrv.2017.12.002.

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Nicholas, J., K. Boydell, and H. Christensen. "Beyond symptom monitoring: Consumer needs for bipolar disorder self-management using smartphones." European Psychiatry 44 (July 2017): 210–16. http://dx.doi.org/10.1016/j.eurpsy.2017.05.023.

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AbstractObjectives:To investigate the potential use of smartphone apps to support self-management in young adults with bipolar disorder.Methods:We recruited 89 young adults (18–30 years) with bipolar disorder to complete a cross-sectional online survey. The survey contained quantitative and qualitative questions regarding technology use, current use of disorder-management apps, types of apps desired for disorder management, and app features that users would consider important when selecting apps. Results were analysed using descriptive statistics and thematic analysis.Results:Almost all partic

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Kutana, Samlau, and Sheila Garland. "0884 User Needs and Preferences for a Smartphone App to Treat Insomnia in Cancer Survivors." SLEEP 46, Supplement_1 (2023): A389—A390. http://dx.doi.org/10.1093/sleep/zsad077.0884.

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Abstract Introduction Cancer patients with insomnia have unique needs and require tailored healthcare interventions. iCANSleep is a mobile health intervention aimed at providing evidence-based insomnia treatment via a smartphone app. As part of a user-centered development process, virtual needs assessment interviews were conducted with cancer survivors who report insomnia to determine the needs and preferences of this patient group for insomnia treatment. Methods 22 cancer survivors from 5 Canadian provinces completed an online survey and participated in a needs assessment interview. Surveys w

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Caputo, Dominick, Philip Cheng, Olivia Walch, et al. "0269 No More Actiwatches: Can Apple Watches be a More Scalable Alternative?" SLEEP 46, Supplement_1 (2023): A120. http://dx.doi.org/10.1093/sleep/zsad077.0269.

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Abstract Introduction The Philips Respironics Actiwatch has become a gold standard for actigraphy data collection. With the announcement of their discontinuation, there has been increased momentum to identify an alternative, particularly with consumer-based devices. One promising solution is the Apple Watch because it allows user access to raw accelerometer data, thus eliminating the long-standing problem of the “black box algorithm” with wearable technology. This study compared the activity counts derived from Apple Watch data with that from the Actiwatch. Methods Adults wore an Actiwatch and

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Mulijono, Dasaad. "Wake Up Call: While We Sleep, China's Healthcare AI Revolution Quietly Overtakes the World—Leaving Indonesia in the Dark." Archives of Epidemiology & Public Health Research 4, no. 2 (2025): 01–04. https://doi.org/10.33140/aephr.04.02.05.

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Artificial Intelligence (AI) and robotics are no longer optional enhancements in healthcare—they are seismic forces redefining the future of medicine, reshaping clinical decision-making, surgical precision, patient outcomes, and economic structures. While the United States struggles with entrenched bureaucracy, fractured systems, and policy paralysis, China has launched a strategic, coordinated offensive that is fast elevating it as the new global epicentre of medical technology. With government-backed research and development (R&D), streamlined regulations, and aggressive AI implementatio

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Hajduczok, Alexander G., Kara M. DiJoseph, Brinnae Bent, et al. "Physiologic Response to the Pfizer-BioNTech COVID-19 Vaccine Measured Using Wearable Devices: Prospective Observational Study." JMIR Formative Research 5, no. 8 (2021): e28568. http://dx.doi.org/10.2196/28568.

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Background The Pfizer-BioNTech COVID-19 vaccine uses a novel messenger RNA technology to elicit a protective immune response. Short-term physiologic responses to the vaccine have not been studied using wearable devices. Objective We aim to characterize physiologic changes in response to COVID-19 vaccination in a small cohort of participants using a wearable device (WHOOP Strap 3.0). This is a proof of concept for using consumer-grade wearable devices to monitor response to COVID-19 vaccines. Methods In this prospective observational study, physiologic data from 19 internal medicine residents a

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Emish, Mohamed, and Sean D. Young. "Remote Wearable Neuroimaging Devices for Health Monitoring and Neurophenotyping: A Scoping Review." Biomimetics 9, no. 4 (2024): 237. http://dx.doi.org/10.3390/biomimetics9040237.

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Digital health tracking is a source of valuable insights for public health research and consumer health technology. The brain is the most complex organ, containing information about psychophysical and physiological biomarkers that correlate with health. Specifically, recent developments in electroencephalogram (EEG), functional near-infra-red spectroscopy (fNIRS), and photoplethysmography (PPG) technologies have allowed the development of devices that can remotely monitor changes in brain activity. The inclusion criteria for the papers in this review encompassed studies on self-applied, remote

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