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Bliwise DL. Something old, something new: a brief history of body movement measurement in sleep. Sleep 2023; 46:zsad146. [PMID: 37210667 DOI: 10.1093/sleep/zsad146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Indexed: 05/22/2023] Open
Affiliation(s)
- Donald L Bliwise
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
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Zhai H, Yan Y, He S, Zhao P, Zhang B. Evaluation of the Accuracy of Contactless Consumer Sleep-Tracking Devices Application in Human Experiment: A Systematic Review and Meta-Analysis. SENSORS (BASEL, SWITZERLAND) 2023; 23:4842. [PMID: 37430756 DOI: 10.3390/s23104842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 05/12/2023] [Accepted: 05/15/2023] [Indexed: 07/12/2023]
Abstract
Compared with the gold standard, polysomnography (PSG), and silver standard, actigraphy, contactless consumer sleep-tracking devices (CCSTDs) are more advantageous for implementing large-sample and long-period experiments in the field and out of the laboratory due to their low price, convenience, and unobtrusiveness. This review aimed to examine the effectiveness of CCSTDs application in human experiments. A systematic review and meta-analysis (PRISMA) of their performance in monitoring sleep parameters were conducted (PROSPERO: CRD42022342378). PubMed, EMBASE, Cochrane CENTRALE, and Web of Science were searched, and 26 articles were qualified for systematic review, of which 22 provided quantitative data for meta-analysis. The findings show that CCSTDs had a better accuracy in the experimental group of healthy participants who wore mattress-based devices with piezoelectric sensors. CCSTDs' performance in distinguishing waking from sleeping epochs is as good as that of actigraphy. Moreover, CCSTDs provide data on sleep stages that are not available when actigraphy is used. Therefore, CCSTDs could be an effective alternative tool to PSG and actigraphy in human experiments.
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Affiliation(s)
- Huifang Zhai
- Faculty of Architecture and Urban Planning, Chongqing University, Chongqing 400044, China
- Key Laboratory of New Technology for Construction of Cities in Mountain Area, Chongqing University, Chongqing 400044, China
| | - Yonghong Yan
- Faculty of Architecture and Urban Planning, Chongqing University, Chongqing 400044, China
- Key Laboratory of New Technology for Construction of Cities in Mountain Area, Chongqing University, Chongqing 400044, China
| | - Siqi He
- College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China
| | - Pinyong Zhao
- College of Mathematics and Statistics, Chongqing University, Chongqing 400044, China
| | - Bohan Zhang
- Faculty of Engineering, The University of Sydney, Camperdown, NSW 2006, Australia
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Heglum HSA, Drews HJ, Kallestad H, Vethe D, Langsrud K, Sand T, Engstrøm M. Contact-free radar recordings of body movement can reflect ultradian dynamics of sleep. J Sleep Res 2022; 31:e13687. [PMID: 35794011 PMCID: PMC9786343 DOI: 10.1111/jsr.13687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 06/17/2022] [Accepted: 06/17/2022] [Indexed: 12/30/2022]
Abstract
This work aimed to evaluate if a contact-free radar sensor can be used to observe ultradian patterns in sleep physiology, by way of a data processing tool known as Locomotor Inactivity During Sleep (LIDS). LIDS was designed as a simple transformation of actigraphy recordings of wrist movement, meant to emphasise and enhance the contrast between movement and non-movement and to reveal patterns of low residual activity during sleep that correlate with ultradian REM/NREM cycles. We adapted the LIDS transformation for a radar that detects body movements without direct contact with the subject and applied it to a dataset of simultaneous recordings with polysomnography, actigraphy, and radar from healthy young adults (n = 12, four nights of polysomnography per participant). Radar and actigraphy-derived LIDS signals were highly correlated with each other (r > 0.84), and the LIDS signals were highly correlated with reduced-resolution polysomnographic hypnograms (rradars >0.80, ractigraph >0.76). Single-harmonic cosine models were fitted to LIDS signals and hypnograms; significant differences were not found between their amplitude, period, and phase parameters. Mixed model analysis revealed similar slopes of decline per cycle for radar-LIDS, actigraphy-LIDS, and hypnograms. Our results indicate that the LIDS technique can be adapted to work with contact-free radar measurements of body movement; it may also be generalisable to data from other body movement sensors. This novel metric could aid in improving sleep monitoring in clinical and real-life settings, by providing a simple and transparent way to study ultradian dynamics of sleep using nothing more than easily obtainable movement data.
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Affiliation(s)
- Hanne Siri Amdahl Heglum
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health SciencesNorwegian University of Science and Technology (NTNU)TrondheimNorway,Novelda ASTrondheimNorway
| | - Henning Johannes Drews
- Department of Mental HealthNorwegian University of Science and TechnologyTrondheimNorway,Department of Public HealthUniversity of CopenhagenCopenhagenDenmark
| | - Håvard Kallestad
- Department of Mental HealthNorwegian University of Science and TechnologyTrondheimNorway,Division of Mental Health CareSt Olavs University HospitalTrondheimNorway
| | - Daniel Vethe
- Department of Mental HealthNorwegian University of Science and TechnologyTrondheimNorway,Division of Mental Health CareSt Olavs University HospitalTrondheimNorway
| | - Knut Langsrud
- Department of Mental HealthNorwegian University of Science and TechnologyTrondheimNorway,Division of Mental Health CareSt Olavs University HospitalTrondheimNorway
| | - Trond Sand
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health SciencesNorwegian University of Science and Technology (NTNU)TrondheimNorway,Department of Neurology and Clinical NeurophysiologySt Olavs University HospitalTrondheimNorway
| | - Morten Engstrøm
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health SciencesNorwegian University of Science and Technology (NTNU)TrondheimNorway,Department of Neurology and Clinical NeurophysiologySt Olavs University HospitalTrondheimNorway
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Kallestad H, Scott J. Time to put a spotlight on out-patient chronotherapy for depression. BJPsych Open 2021; 7:e219. [PMID: 34814971 PMCID: PMC8693906 DOI: 10.1192/bjo.2021.1056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 10/20/2021] [Accepted: 10/24/2021] [Indexed: 11/24/2022] Open
Abstract
The challenge of identifying efficacious out-patient treatments for depression is amplified by the increasing desire to find interventions that reduce the time to sustained improvement. One potential but underexplored option is triple chronotherapy (TCT). To date, use of TCT has been largely restricted to specialist units or in-patients. Recent research demonstrates that it may be possible to undertake sleep deprivation in out-patient settings, raising the possibility of delivering TCT to broader populations of individuals with depression. Emerging evidence suggests that out-patient TCT is a high-benefit, low-risk intervention but questions remain about how to target TCT and its mechanisms of action. Like traditional antidepressants, TCT probably acts through several pathways, especially the synchronisation of the 'master clock'. Availability of reliable and valid methods of out-patient measurement of intra-individual circadian rhythmicity and light exposure are rate-limiting steps in the wider dissemination of TCT.
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Affiliation(s)
- Havard Kallestad
- Division of Mental Health Care, St Olavs University Hospital, Trondheim, Norway; and Division of Mental Health Care, Department of Research and Development, Norwegian University of Science and Technology, Trondheim, Norway
| | - Jan Scott
- Department of Academic Psychiatry, Newcastle University, UK; and Division of Mental Health Care, Department of Research and Development, Norwegian University of Science and Technology, Trondheim, Norway
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Schmidt MH, Dekkers MPJ, Baillieul S, Jendoubi J, Wulf MA, Wenz E, Fregolente L, Vorster A, Gnarra O, Bassetti CLA. Measuring Sleep, Wakefulness, and Circadian Functions in Neurologic Disorders. Sleep Med Clin 2021; 16:661-671. [PMID: 34711389 DOI: 10.1016/j.jsmc.2021.08.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Neurologic disorders impact the ability of the brain to regulate sleep, wake, and circadian functions, including state generation, components of state (such as rapid eye movement sleep muscle atonia, state transitions) and electroencephalographic microarchitecture. At its most extreme, extensive brain damage may even prevent differentiation of sleep stages from wakefulness (eg, status dissociatus). Given that comorbid sleep-wake-circadian disorders are common and can adversely impact the occurrence, evolution, and management of underlying neurologic conditions, new technologies for long-term monitoring of neurologic patients may potentially usher in new diagnostic strategies and optimization of clinical management.
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Affiliation(s)
- Markus H Schmidt
- Department of Neurology, Bern University Hospital (Inselspital) and University Bern, Switzerland; Ohio Sleep Medicine Institute, 4975 Bradenton Avenue, Dublin, OH 43017, USA.
| | - Martijn P J Dekkers
- Department of Neurology, Bern University Hospital (Inselspital) and University Bern, Switzerland
| | - Sébastien Baillieul
- Department of Neurology, Bern University Hospital (Inselspital) and University Bern, Switzerland; Univ. Grenoble Alpes, Inserm, U1300, CHU Grenoble Alpes, Service Universitaire de Pneumologie Physiologie, Grenoble 38000, France
| | - Jasmine Jendoubi
- Department of Neurology, Bern University Hospital (Inselspital) and University Bern, Switzerland
| | - Marie-Angela Wulf
- Department of Neurology, Bern University Hospital (Inselspital) and University Bern, Switzerland
| | - Elena Wenz
- Department of Neurology, Bern University Hospital (Inselspital) and University Bern, Switzerland
| | - Livia Fregolente
- Department of Neurology, Bern University Hospital (Inselspital) and University Bern, Switzerland
| | - Albrecht Vorster
- Department of Neurology, Bern University Hospital (Inselspital) and University Bern, Switzerland
| | - Oriella Gnarra
- Department of Neurology, Bern University Hospital (Inselspital) and University Bern, Switzerland; Sensory-Motor System Lab, IRIS, ETH Zurich, Switzerland
| | - Claudio L A Bassetti
- Department of Neurology, Bern University Hospital (Inselspital) and University Bern, Switzerland; Department of Neurology, University of Sechenow, Moscow, Russia
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Schutte-Rodin S, Deak M, Khosla S, Goldstein CA, Yurcheshen M, Chiang A, Gault D, Kern J, O'Hearn D, Ryals S, Verma N, Kirsch DB, Baron K, Holfinger S, Miller J, Patel R, Bhargava S, Ramar K. Evaluating consumer and clinical sleep technologies: an American Academy of Sleep Medicine update. J Clin Sleep Med 2021; 17:2275-2282. [PMID: 34314344 DOI: 10.5664/jcsm.9580] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Affiliation(s)
- Sharon Schutte-Rodin
- University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | | | - Seema Khosla
- North Dakota Center for Sleep, Fargo, North Dakota
| | | | | | - Ambrose Chiang
- Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland, Ohio
| | - Dominic Gault
- Greenville Health System, University of South Carolina, Greenville, South Carolina
| | - Joseph Kern
- New Mexico VA Health Care System, Albuquerque, New Mexico
| | - Daniel O'Hearn
- Department of Medicine, University of Washington, Seattle, Washington
| | - Scott Ryals
- University of Florida Health Sleep Center, Gainesville, Florida
| | | | - Douglas B Kirsch
- Carolinas Healthcare Medical Group Sleep Services, Charlotte, North Carolina
| | - Kelly Baron
- Univeristy of Utah Sleep-Wake Center, Salt Lake City, Utah
| | | | | | - Ruchir Patel
- The Insomnia and Sleep Institute of Arizona, Scottsdale, Arizona
| | - Sumit Bhargava
- Lucille Packard Children's Hospital at Stanford, Palo Alto, California
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