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      Clinical Applications of Mobile Health Wearable–Based Sleep Monitoring: Systematic Review

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          Abstract

          Background

          Sleep disorders are a major public health issue. Nearly 1 in 2 people experience sleep disturbances during their lifetime, with a potential harmful impact on well-being and physical and mental health.

          Objective

          The aim of this study was to better understand the clinical applications of wearable-based sleep monitoring; therefore, we conducted a review of the literature, including feasibility studies and clinical trials on this topic.

          Methods

          We searched PubMed, PsycINFO, ScienceDirect, the Cochrane Library, Scopus, and the Web of Science through June 2019. We created the list of keywords based on 2 domains: wearables and sleep. The primary selection criterion was the reporting of clinical trials using wearable devices for sleep recording in adults.

          Results

          The initial search identified 645 articles; 19 articles meeting the inclusion criteria were included in the final analysis. In all, 4 categories of the selected articles appeared. Of the 19 studies in this review, 58 % (11/19) were comparison studies with the gold standard, 21% (4/19) were feasibility studies, 15% (3/19) were population comparison studies, and 5% (1/19) assessed the impact of sleep disorders in the clinic. The samples were heterogeneous in size, ranging from 1 to 15,839 patients. Our review shows that mobile-health (mHealth) wearable–based sleep monitoring is feasible. However, we identified some major limitations to the reliability of wearable-based monitoring methods compared with polysomnography.

          Conclusions

          This review showed that wearables provide acceptable sleep monitoring but with poor reliability. However, wearable mHealth devices appear to be promising tools for ecological monitoring.

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          Most cited references40

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          Sleep and mental disorders: A meta-analysis of polysomnographic research.

          Investigating sleep in mental disorders has the potential to reveal both disorder-specific and transdiagnostic psychophysiological mechanisms. This meta-analysis aimed at determining the polysomnographic (PSG) characteristics of several mental disorders. Relevant studies were searched through standard strategies. Controlled PSG studies evaluating sleep in affective, anxiety, eating, pervasive developmental, borderline and antisocial personality disorders, attention-deficit-hyperactivity disorder (ADHD), and schizophrenia were included. PSG variables of sleep continuity, depth, and architecture, as well as rapid-eye movement (REM) sleep were considered. Calculations were performed with the "Comprehensive Meta-Analysis" and "R" software. Using random effects modeling, for each disorder and each variable, a separate meta-analysis was conducted if at least 3 studies were available for calculation of effect sizes as standardized means (Hedges' g). Sources of variability, that is, sex, age, and mental disorders comorbidity, were evaluated in subgroup analyses. Sleep alterations were evidenced in all disorders, with the exception of ADHD and seasonal affective disorders. Sleep continuity problems were observed in most mental disorders. Sleep depth and REM pressure alterations were associated with affective, anxiety, autism and schizophrenia disorders. Comorbidity was associated with enhanced REM sleep pressure and more inhibition of sleep depth. No sleep parameter was exclusively altered in 1 condition; however, no 2 conditions shared the same PSG profile. Sleep continuity disturbances imply a transdiagnostic imbalance in the arousal system likely representing a basic dimension of mental health. Sleep depth and REM variables might play a key role in psychiatric comorbidity processes. Constellations of sleep alterations may define distinct disorders better than alterations in 1 single variable. (PsycINFO Database Record
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            Practice parameters for the indications for polysomnography and related procedures: an update for 2005.

            These practice parameters are an update of the previously-published recommendations regarding the indications for polysomnography and related procedures in the diagnosis of sleep disorders. Diagnostic categories include the following: sleep related breathing disorders, other respiratory disorders, narcolepsy, parasomnias, sleep related seizure disorders, restless legs syndrome, periodic limb movement sleep disorder, depression with insomnia, and circadian rhythm sleep disorders. Polysomnography is routinely indicated for the diagnosis of sleep related breathing disorders; for continuous positive airway pressure (CPAP) titration in patients with sleep related breathing disorders; for the assessment of treatment results in some cases; with a multiple sleep latency test in the evaluation of suspected narcolepsy; in evaluating sleep related behaviors that are violent or otherwise potentially injurious to the patient or others; and in certain atypical or unusual parasomnias. Polysomnography may be indicated in patients with neuromuscular disorders and sleep related symptoms; to assist in the diagnosis of paroxysmal arousals or other sleep disruptions thought to be seizure related; in a presumed parasomnia or sleep related seizure disorder that does not respond to conventional therapy; or when there is a strong clinical suspicion of periodic limb movement sleep disorder. Polysomnography is not routinely indicated to diagnose chronic lung disease; in cases of typical, uncomplicated, and noninjurious parasomnias when the diagnosis is clearly delineated; for patients with seizures who have no specific complaints consistent with a sleep disorder; to diagnose or treat restless legs syndrome; for the diagnosis of circadian rhythm sleep disorders; or to establish a diagnosis of depression.
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              Reliability of Sleep Measures from Four Personal Health Monitoring Devices Compared to Research-Based Actigraphy and Polysomnography

              Polysomnography (PSG) is the “gold standard” for monitoring sleep. Alternatives to PSG are of interest for clinical, research, and personal use. Wrist-worn actigraph devices have been utilized in research settings for measures of sleep for over two decades. Whether sleep measures from commercially available devices are similarly valid is unknown. We sought to determine the validity of five wearable devices: Basis Health Tracker, Misfit Shine, Fitbit Flex, Withings Pulse O2, and a research-based actigraph, Actiwatch Spectrum. We used Wilcoxon Signed Rank tests to assess differences between devices relative to PSG and correlational analysis to assess the strength of the relationship. Data loss was greatest for Fitbit and Misfit. For all devices, we found no difference and strong correlation of total sleep time with PSG. Sleep efficiency differed from PSG for Withings, Misfit, Fitbit, and Basis, while Actiwatch mean values did not differ from that of PSG. Only mean values of sleep efficiency (time asleep/time in bed) from Actiwatch correlated with PSG, yet this correlation was weak. Light sleep time differed from PSG (nREM1 + nREM2) for all devices. Measures of Deep sleep time did not differ from PSG (SWS + REM) for Basis. These results reveal the current strengths and limitations in sleep estimates produced by personal health monitoring devices and point to a need for future development.
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                Author and article information

                Contributors
                Journal
                JMIR Mhealth Uhealth
                JMIR Mhealth Uhealth
                JMU
                JMIR mHealth and uHealth
                JMIR Publications (Toronto, Canada )
                2291-5222
                April 2020
                1 April 2020
                : 8
                : 4
                : e10733
                Affiliations
                [1 ] Urci Mental Health Department Brest France
                [2 ] IMT Atlantique Lab-STICC F-29238 Brest Brest France
                [3 ] EA 7479 SPURRBO Université de Bretagne Occidentale Brest France
                [4 ] Fundacion Jimenez Diaz Madrid Spain
                [5 ] Clinea Psychiatry France Paris France
                [6 ] IMT Atlantique Brest France
                [7 ] Black Dog Institute University of New South Wales Sydney Australia
                [8 ] Please see Acknowledgements for list of collaborators
                [9 ] Laboratoire de Traitement de l'Information Médicale INSERM UMR 1101 Brest France
                [10 ] Department of Child Neurology University Hospital of Brest Brest France
                Author notes
                Corresponding Author: Elise Guillodo elise.guillodo@ 123456chu-brest.fr
                Author information
                https://orcid.org/0000-0003-1406-2627
                https://orcid.org/0000-0002-7308-7958
                https://orcid.org/0000-0001-7228-8961
                https://orcid.org/0000-0002-3071-7673
                https://orcid.org/0000-0002-6963-6555
                https://orcid.org/0000-0002-8830-5153
                https://orcid.org/0000-0003-0968-785X
                https://orcid.org/0000-0002-0272-2053
                https://orcid.org/0000-0001-7467-759X
                https://orcid.org/0000-0001-9148-6218
                Article
                v8i4e10733
                10.2196/10733
                7160700
                32234707
                17995d7c-7e68-4be5-9bb9-5da58843c007
                ©Elise Guillodo, Christophe Lemey, Mathieu Simonnet, Michel Walter, Enrique Baca-García, Vincent Masetti, Sorin Moga, Mark Larsen, HUGOPSY Network, Juliette Ropars, Sofian Berrouiguet. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 01.04.2020.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.

                History
                : 20 June 2019
                : 30 July 2019
                : 4 October 2019
                : 22 October 2019
                Categories
                Review
                Review

                sleep,ehealth,telemedicine,review,medicine,wearable electronic devices

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