• Login
    View Item 
    •   Home
    • UMass Chan Faculty and Staff Research and Publications
    • UMass Chan Faculty and Researcher Publications
    • View Item
    •   Home
    • UMass Chan Faculty and Staff Research and Publications
    • UMass Chan Faculty and Researcher Publications
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of eScholarship@UMassChanCommunitiesPublication DateAuthorsUMass Chan AffiliationsTitlesDocument TypesKeywordsThis CollectionPublication DateAuthorsUMass Chan AffiliationsTitlesDocument TypesKeywords

    My Account

    LoginRegister

    Help

    AboutSubmission GuidelinesData Deposit PolicySearchingAccessibilityTerms of UseWebsite Migration FAQ

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Classification and prediction of post-trauma outcomes related to PTSD using circadian rhythm changes measured via wrist-worn research watch in a large longitudinal cohort

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Authors
    Cakmak, Ayse Selin
    Haran, John P.
    Clifford, Gari D.
    UMass Chan Affiliations
    Department of Emergency Medicine
    Document Type
    Journal Article
    Publication Date
    2021-01-22
    Keywords
    Actigraphy
    Circadian rhythms
    mHealth
    Photoplethysmography
    Post-traumatic stress disorder
    Wearables
    Biomedical Devices and Instrumentation
    Emergency Medicine
    Mental Disorders
    Musculoskeletal, Neural, and Ocular Physiology
    Neuroscience and Neurobiology
    Telemedicine
    Show allShow less
    
    Metadata
    Show full item record
    Link to Full Text
    https://doi.org/10.1109/jbhi.2021.3053909
    Abstract
    Post-Traumatic Stress Disorder (PTSD) is a psychiatric condition resulting from threatening or horrifying events. We hypothesized that circadian rhythm changes, measured by a wrist-worn research watch are predictive of post-trauma outcomes. APPROACH: 1618 post-trauma patients were enrolled after admission to emergency departments (ED). Three standardized questionnaires were administered at week eight to measure post-trauma outcomes related to PTSD, sleep disturbance, and pain interference with daily life. Pulse activity and movement data were captured from a research watch for eight weeks. Standard and novel movement and cardiovascular metrics that reflect circadian rhythms were derived using this data. These features were used to train different classifiers to predict the three outcomes derived from week-eight surveys. Clinical surveys administered at ED were also used as features in the baseline models. RESULTS: The highest cross-validated performance of research watch-based features was achieved for classifying participants with pain interference by a logistic regression model, with an area under the receiver operating characteristic curve (AUC) of 0.70. The ED survey-based model achieved an AUC of 0.77, and the fusion of research watch and ED survey metrics improved the AUC to 0.79. SIGNIFICANCE: This work represents the first attempt to predict and classify post-trauma symptoms from passive wearable data using machine learning approaches that leverage the circadian desynchrony in a potential PTSD population.
    Source

    Cakmak AS, Perez Alday EA, Da Poian G, Bahrami Rad A, Metzler TJ, Neylan TC, House SL, Beaudoin FL, An X, Stevens J, Zeng D, Linnstaedt SD, Jovanovic T, Germine LT, Bollen KA, Rauch SL, Lewandowski C, Hendry PL, Sheikh S, Storrow AB, Musey PI, Haran JP, Jones CW, Punches BE, Swor RA, Gentile NT, Mcgrath ME, Seamon MJ, Mohiuddin K, Chang AM, Pearson C, Domeier RM, Bruce SE, O'Neil BJ, Rathlev NK, Sanchez LD, Pietrzak RH, Joormann J, Barch DM, Pizzagalli D, Harte SE, Elliott JM, Koenen KC, Ressler KJ, Kessler R, Li Q, Mclean SA, Clifford GD. Classification and prediction of post-trauma outcomes related to PTSD using circadian rhythm changes measured via wrist-worn research watch in a large longitudinal cohort. IEEE J Biomed Health Inform. 2021 Jan 22;PP. doi: 10.1109/JBHI.2021.3053909. Epub ahead of print. PMID: 33481725. Link to article on publisher's site

    DOI
    10.1109/JBHI.2021.3053909
    Permanent Link to this Item
    http://hdl.handle.net/20.500.14038/29704
    PubMed ID
    33481725
    Notes

    Full author list omitted for brevity. For the full list of authors, see article.

    Related Resources

    Link to Article in PubMed

    ae974a485f413a2113503eed53cd6c53
    10.1109/JBHI.2021.3053909
    Scopus Count
    Collections
    UMass Chan Faculty and Researcher Publications
    Emergency Medicine Publications

    entitlement

    DSpace software (copyright © 2002 - 2023)  DuraSpace
    Lamar Soutter Library, UMass Chan Medical School | 55 Lake Avenue North | Worcester, MA 01655 USA
    Quick Guide | escholarship@umassmed.edu
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.