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      A novel upper-limb function measure derived from finger-worn sensor data collected in a free-living setting

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          Abstract

          The use of wrist-worn accelerometers has recently gained tremendous interest among researchers and clinicians as an objective tool to quantify real-world use of the upper limbs during the performance of activities of daily living (ADLs). However, wrist-worn accelerometers have shown a number of limitations that hinder their adoption in the clinic. Among others, the inability of wrist-worn accelerometers to capture hand and finger movements is particularly relevant to monitoring the performance of ADLs. This study investigates the use of finger-worn accelerometers to capture both gross arm and fine hand movements for the assessment of real-world upper-limb use. A system of finger-worn accelerometers was utilized to monitor eighteen neurologically intact young adults while performing nine motor tasks in a laboratory setting. The system was also used to monitor eighteen subjects during the day time of a day in a free-living setting. A novel measure of real-world upper-limb function—comparing the duration of activities of the two limbs—was derived to identify which upper limb subjects predominantly used to perform ADLs. Two validated handedness self-reports, namely the Waterloo Handedness Questionnaire and the Fazio Laterality Inventory, were collected to assess convergent validity. The analysis of the data recorded in the laboratory showed that the proposed measure of upper-limb function is suitable to accurately detect unilateral vs. bilateral use of the upper limbs, including both gross arm movements and fine hand movements. When applied to recordings collected in a free-living setting, the proposed measure showed high correlation with self-reported handedness indices (i.e., ρ = 0.78 with the Waterloo Handedness Questionnaire scores and ρ = 0.77 with the Fazio Laterality Inventory scores). The results herein presented establish face and convergent validity of the proposed measure of real-world upper-limb function derived using data collected by means of finger-worn accelerometers.

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          Early prediction of outcome of activities of daily living after stroke: a systematic review.

          Knowledge about robust and unbiased factors that predict outcome of activities of daily living (ADL) is paramount in stroke management. This review investigates the methodological quality of prognostic studies in the early poststroke phase for final ADL to identify variables that are predictive or not predictive for outcome of ADL after stroke. PubMed, Ebsco/Cinahl and Embase were systematically searched for prognostic studies in which stroke patients were included ≤2 weeks after onset and final outcome of ADL was determined ≥3 months poststroke. Risk of bias scores were used to distinguish high- and low-quality studies and a qualitative synthesis was performed. Forty-eight of 8425 identified citations were included. The median risk of bias score was 17 out of 27 (range, 6-22) points. Most studies failed to report medical treatment applied, management of missing data, rationale for candidate determinants and outcome cut-offs, results of univariable analysis, and validation and performance of the model, making the predictive value of most determinants indistinct. Six high-quality studies showed strong evidence for baseline neurological status, upper limb paresis, and age as predictors for outcome of ADL. Gender and risk factors such as atrial fibrillation were unrelated to this outcome. Because of insufficient methodological quality of most prognostic studies, the predictive value of many clinical determinants for outcome of ADL remains unclear. Future cohort studies should focus on early prediction using simple models with good clinical performance to enhance application in stroke management and research.
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            Reliability and validity of the upper-extremity Motor Activity Log-14 for measuring real-world arm use.

            In research on Constraint-Induced Movement (CI) therapy, a structured interview, the Motor Activity Log (MAL), is used to assess how stroke survivors use their more-impaired arm outside the laboratory. This article examines the psychometrics of the 14-item version of this instrument in 2 chronic stroke samples with mild-to-moderate upper-extremity hemiparesis. Participants (n=41) in the first study completed MALs before and after CI therapy or a placebo control procedure. In addition, caregivers independently completed a MAL on the participants. Participants (n=27) in the second study completed MALs and wore accelerometers that monitored their arm movements for 3 days outside the laboratory before and after an automated form of CI therapy. Validity of the participant MAL Quality of Movement (QOM) scale was supported. Correlations between pretreatment-to-posttreatment change scores on the participant QOM scale and caregiver MAL QOM scale, caregiver MAL amount of use (AOU) scale, and accelerometer recordings were 0.70, 0.73, and 0.91 (P 0.81), test-retest reliability (r>0.91), stability, and responsiveness (ratio>3) of the participant QOM scale were also supported. The participant AOU and caregiver QOM and AOU scales were internally consistent, stable, and sensitive, but were not reliable. The participant MAL QOM scale can be used exclusively to reliably and validly measure real-world, upper-extremity rehabilitation outcome and functional status in chronic stroke patients with mild-to-moderate hemiparesis.
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              Forced use of hemiplegic upper extremities to reverse the effect of learned nonuse among chronic stroke and head-injured patients.

              To test the clinical counterpart of the learned nonuse theory, 25 chronic hemiplegic stroke and head-injured patients with minimal to moderate upper extremity extensor muscle function were required to keep their uninvolved upper extremities within a hand-enclosed sling during waking hours over a 2-week interval. During this forced use period and for 1 year thereafter, changes in force or time-based measures among 21 functional tasks were compared to values at the sixth baseline session, a preintervention time when relearning had plateaued. Significant (P less than 0.05, Friedman's repeated measures followed by Tukey multiple comparison tests) changes were seen in 19 of the 21 tasks with most persisting at the 1-year follow-up. There were no apparent differences between right- and left-sided involvement or between stroke versus head injury clients (Mann-Whitney procedure). Ratings for quality of movement scored from videotapes presented in random order showed no change over time. These data suggest that learned nonuse does occur in select neurological patients and that this behavior can be reversed through application of a forced use paradigm.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: Writing – review & editing
                Role: InvestigationRole: Project administrationRole: ResourcesRole: Writing – review & editing
                Role: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: Writing – review & editing
                Role: ConceptualizationRole: SupervisionRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: SupervisionRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2019
                20 March 2019
                : 14
                : 3
                : e0212484
                Affiliations
                [1 ] College of Information and Computer Sciences, University of Massachusetts, Amherst, MA, United States of America
                [2 ] ArcSecond Inc., San Diego, CA, United States of America
                [3 ] College of Information Studies, University of Maryland, College Park, MD, United States of America
                [4 ] Department of Physical Medicine and Rehabilitation, Harvard Medical School, Spaulding Rehabilitation Hospital, Charlestown, MA, United States of America
                Washington University in Saint Louis School of Medicine, UNITED STATES
                Author notes

                Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: NR is affiliated with ArcSecond Inc., San Diego, CA, USA. NR utilized the Industry Outreach Seed Grant Fund jointly received by SIL and NR from the Institute of Applied Life Sciences at the University of Massachusetts Amherst in order to implement and provide the device that were described in the manuscript. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

                Author information
                http://orcid.org/0000-0001-5935-125X
                http://orcid.org/0000-0003-1185-360X
                Article
                PONE-D-18-28807
                10.1371/journal.pone.0212484
                6426183
                30893308
                52df34b1-8cfb-41c7-8b55-0784c841537b
                © 2019 Lee et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 9 October 2018
                : 3 February 2019
                Page count
                Figures: 5, Tables: 4, Pages: 18
                Funding
                Funded by: Institute of Applied Life Sciences at the University of Massachusetts, Amherst
                Award Recipient :
                Funded by: North Carolina Translational and Clinical Sciences Institute, University of North Carolina at Chapel Hill (US)
                Award Recipient :
                This material is partially supported by the Industry Outreach Seed Grant Fund, entitled "Development of a Body Area Networked System with Novel Finger-Worn Sensors", that was received by SIL and NR from the Institute of Applied Life Sciences at the University of Massachusetts, Amherst. Due to the nature of the internal university fund, there is no grant number associated with it. This work was also supported by North Carolina Translational and Clinical Sciences Institute, University of North Carolina at Chapel Hill (US). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The funding organizations did not play a role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript and only provided financial support in the form of authors’ salaries and/or research materials.
                Categories
                Research Article
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Body Limbs
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Body Limbs
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Body Limbs
                Arms
                Hands
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Body Limbs
                Arms
                Hands
                Engineering and Technology
                Electronics
                Accelerometers
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Body Limbs
                Arms
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Body Limbs
                Arms
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Body Limbs
                Arms
                Wrist
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Body Limbs
                Arms
                Wrist
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Body Limbs
                Arms
                Hands
                Fingers
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Body Limbs
                Arms
                Hands
                Fingers
                Research and Analysis Methods
                Research Design
                Survey Research
                Questionnaires
                Medicine and Health Sciences
                Neurology
                Cerebrovascular Diseases
                Stroke
                Medicine and Health Sciences
                Vascular Medicine
                Stroke
                Custom metadata
                The data can be found at https://doi.org/10.7910/DVN/BVPUSD.

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