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      Use of wearable devices for post-discharge monitoring of ICU patients: a feasibility study

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          Abstract

          Background

          Wearable devices generate signals detecting activity, sleep, and heart rate, all of which could enable detailed and near-continuous characterization of recovery following critical illness.

          Methods

          To determine the feasibility of using a wrist-worn personal fitness tracker among patients recovering from critical illness, we conducted a prospective observational study of a convenience sample of 50 stable ICU patients. We assessed device wearability, the extent of data capture, sensitivity and specificity for detecting heart rate excursions, and correlations with questionnaire-derived sleep quality measures.

          Results

          Wearable devices were worn over a 24-h period, with excellent capture of data. While specificity for the detection of tachycardia was high (98.8%), sensitivity was low to moderate (69.5%). There was a moderate correlation between wearable-derived sleep duration and questionnaire-derived sleep quality ( r = 0.33, P = 0.03). Devices were well-tolerated and demonstrated no degradation in quality of data acquisition over time.

          Conclusions

          We found that wearable devices could be worn by patients recovering from critical illness and could generate useful data for the majority of patients with little adverse effect. Further development and study are needed to better define and enhance the role of wearables in the monitoring of post-ICU recovery.

          Trial registration

          Clinicaltrials.gov, NCT02527408

          Electronic supplementary material

          The online version of this article (10.1186/s40560-017-0261-9) contains supplementary material, which is available to authorized users.

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          Most cited references18

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          Early warning system scores for clinical deterioration in hospitalized patients: a systematic review.

          Early warning system (EWS) scores are used by hospital care teams to recognize early signs of clinical deterioration and trigger more intensive care.
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            Accuracy of Wrist-Worn Heart Rate Monitors.

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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
                9rrk2@queensu.ca
                emckenzie@qmed.ca
                boydj@KGH.KARI.NET
                ps70@queensu.ca
                howesd@KGH.KARI.NET
                14mdw@queensu.ca
                +1 613 549 6666 , david.maslove@queensu.ca
                Journal
                J Intensive Care
                J Intensive Care
                Journal of Intensive Care
                BioMed Central (London )
                2052-0492
                21 November 2017
                21 November 2017
                2017
                : 5
                : 64
                Affiliations
                [1 ]ISNI 0000 0004 1936 8331, GRID grid.410356.5, Department of Critical Care Medicine, , Queen’s University and Kingston Health Sciences Centre, ; Kingston, Ontario Canada
                [2 ]ISNI 0000 0004 1936 8331, GRID grid.410356.5, School of Medicine, , Queen’s University, ; Kingston, Ontario Canada
                [3 ]ISNI 0000 0004 1936 8331, GRID grid.410356.5, Department of Medicine, , Queen’s University and Kingston Health Sciences Centre, ; Kingston, Ontario Canada
                [4 ]ISNI 0000 0004 1936 8331, GRID grid.410356.5, Department of Pathology and Molecular Medicine, , Queen’s University and Health Sciences Centre, ; Kingston, Ontario Canada
                [5 ]ISNI 0000 0004 1936 8331, GRID grid.410356.5, Department of Emergency Medicine, , Queen’s University and Kingston Health Sciences Centre, ; Kingston, Ontario Canada
                [6 ]ISNI 0000 0004 1936 8331, GRID grid.410356.5, Department of Neuroscience, , Queen’s University, ; Kingston, Ontario Canada
                [7 ]ISNI 0000 0004 0633 727X, GRID grid.415354.2, Kingston Health Sciences Centre, , Kingston General Hospital, ; Davies 2, 76 Stuart St., Kingston, Ontario K7L 2V7 Canada
                Author information
                http://orcid.org/0000-0002-0765-7158
                Article
                261
                10.1186/s40560-017-0261-9
                5698959
                29201377
                d3b85111-e308-479a-aa1d-6da8b705c0d1
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 19 September 2017
                : 8 November 2017
                Funding
                Funded by: Southeastern Ontario Academic Medical Organization
                Award ID: AHSC AFP Innovation Fund
                Categories
                Research
                Custom metadata
                © The Author(s) 2017

                wearable devices,medical informatics,mobile health technologies,validation study,critical care,sleep quality,heart rate monitoring

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