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      Remote Physical Activity Monitoring in Neurological Disease: A Systematic Review

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          Abstract

          Objective

          To perform a systematic review of studies using remote physical activity monitoring in neurological diseases, highlighting advances and determining gaps.

          Methods

          Studies were systematically identified in PubMed/MEDLINE, CINAHL and SCOPUS from January 2004 to December 2014 that monitored physical activity for ≥24 hours in adults with neurological diseases. Studies that measured only involuntary motor activity (tremor, seizures), energy expenditure or sleep were excluded. Feasibility, findings, and protocols were examined.

          Results

          137 studies met inclusion criteria in multiple sclerosis (MS) (61 studies); stroke (41); Parkinson's Disease (PD) (20); dementia (11); traumatic brain injury (2) and ataxia (1). Physical activity levels measured by remote monitoring are consistently low in people with MS, stroke and dementia, and patterns of physical activity are altered in PD. In MS, decreased ambulatory activity assessed via remote monitoring is associated with greater disability and lower quality of life. In stroke, remote measures of upper limb function and ambulation are associated with functional recovery following rehabilitation and goal-directed interventions. In PD, remote monitoring may help to predict falls. In dementia, remote physical activity measures correlate with disease severity and can detect wandering.

          Conclusions

          These studies show that remote physical activity monitoring is feasible in neurological diseases, including in people with moderate to severe neurological disability. Remote monitoring can be a psychometrically sound and responsive way to assess physical activity in neurological disease. Further research is needed to ensure these tools provide meaningful information in the context of specific neurological disorders and patterns of neurological disability.

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          Most cited references143

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          Randomized Trial of a Fitbit-Based Physical Activity Intervention for Women.

          Direct-to-consumer mHealth devices are a potential asset to behavioral research but rarely tested as intervention tools. This trial examined the accelerometer-based Fitbit tracker and website as a low-touch physical activity intervention. The purpose of this study is to evaluate, within an RCT, the feasibility and preliminary efficacy of integrating the Fitbit tracker and website into a physical activity intervention for postmenopausal women.
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            Smartphone Applications for Patients' Health and Fitness.

            Healthcare providers are often looking for ways to objectively monitor and improve their patients' health and fitness, especially in between patient visits. Some insurance companies are using applications data as incentives to improve health and lower premiums. As more and more people start to use smartphones, they may provide a tool to help improve a patient's health and fitness. Specifically, fitness applications or "apps" on smartphones are programs that use data collected from a smartphone's inbuilt tools, such as the Global Positioning System, accelerometer, microphone, speaker, and camera, to measure health and fitness parameters. The apps then analyze these data and summarize them, as well as devise individualized plans based on users' goals, provide frequent feedback, personalized coaching, and additional motivation by allowing milestones to be shared on social media. This article introduces evidence that apps can better help patients reach their health and fitness goals. It then discusses what features to look for in an app, followed by an overview of popular health and fitness apps. Last, patient scenarios with app recommendations, limitations of apps, and future research are discussed.
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              ActiGraph and Actical physical activity monitors: a peek under the hood.

              Since the 1980s, accelerometer-based activity monitors have been used by researchers to quantify physical activity. The technology of these monitors has continuously evolved. For example, changes have been made to monitor hardware (type of sensor (e.g., piezoelectric, piezoresistive, capacitive)) and output format (counts vs raw signal). Commonly used activity monitors belong to the ActiGraph and the Actical families. This article presents information on several electromechanical aspects of these commonly used activity monitors. The majority of the article focuses on the evolution of the ActiGraph activity monitor by describing the differences among the 7164, the GT1M, and the GT3X models. This is followed by brief descriptions of the influences of device firmware and monitor calibration status. We also describe the Actical, but the discussion is short because this device has not undergone any major changes since it was first introduced. This article may help researchers gain a better understanding of the functioning of activity monitors. For example, a common misconception among physical activity researchers is that the ActiGraph GT1M and GT3X are piezoelectric sensor-based monitors. Thus, this information may also help researchers to describe these monitors more accurately in scientific publications.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                28 April 2016
                2016
                : 11
                : 4
                : e0154335
                Affiliations
                [1 ]Graduate Program in Physical Therapy, University of California San Francisco/ San Francisco State University, San Francisco, California, United States of America
                [2 ]Department of Physical Therapy and Rehabilitation Science, University of California San Francisco, San Francisco, California, United States of America
                [3 ]University of California San Francisco Library, San Francisco, California, United States of America
                [4 ]Multiple Sclerosis and Neuroinflammation Center, Department of Neurology, University of California San Francisco, San Francisco, California, United States of America
                Xuanwu Hospital, Capital Medical Universty, CHINA
                Author notes

                Competing Interests: The authors have read the journal's policy and have the following competing interests: VAJB and PT have no disclosures. EP has received compensation for teaching continuing education for Summit Professional Education. BACC has received personal compensation for consulting from Abbvie, Biogen, EMD Serono, MedImmune, Novartis, Genzyme/sanofi aventis, Teva and has received contracted research support (including clinical trials) from Acorda, Biogen, EMD Serono, Hoffman La Roche, MedImmune, Novartis and Teva. DDA has received compensation as an instructor for the Neurologic Physical Therapy Residency Program at Kaiser Redwood City. She has also received compensation for co-developing an online continuing education course in rehabilitation for people with multiple sclerosis for Western Schools. JMG has served as a consultant on a scientific advisory board for MedImmune; has received research support from Quest Diagnostics through UCSF on a dementia care pathway; and has received compensation for medical legal consulting related to CNS inflammatory disorders. This does not alter the authors' adherence to PLOS ONE policies on sharing data and materials.

                Conceived and designed the experiments: VAJB DDA JMG. Analyzed the data: VJAB EP. Wrote the paper: VAJB BACC DDA JMG. Advised on search strategy: PT. Supervision of search strategy and checked data extraction: DDA JMG. Study Design: VAJB DDA JMG. Independently performed the systematic search: VAJB EP. Critical revision of the manuscript: VAJB DDA JMG PT BACC.

                [¤a]

                Current address: Department of Physical Therapy & Rehabilitation Science. University of California San Francisco. San Francisco, California, United States of America

                [¤b]

                Current address: Department of Neurology, University of California San Francisco, San Francisco, California, United States of America

                ‡ DDA and JMG are Joint Senior Authors on this work.

                Article
                PONE-D-15-55629
                10.1371/journal.pone.0154335
                4849800
                27124611
                4d83b884-97a6-4c0f-8842-3c05486cdb4a
                © 2016 Block 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
                : 23 December 2015
                : 11 April 2016
                Page count
                Figures: 2, Tables: 6, Pages: 41
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100000009, National Center for Advancing Translational Sciences of NIH;
                Award ID: KL2TR000143
                Award Recipient :
                This work was supported by the National Center for Advancing Translational Sciences of National Institute of Health - under award KL2TR000143 (JMG). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Public and Occupational Health
                Physical Activity
                Engineering and Technology
                Equipment
                Measurement Equipment
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Dementia
                Alzheimer Disease
                Medicine and Health Sciences
                Neurology
                Dementia
                Alzheimer Disease
                Medicine and Health Sciences
                Neurology
                Neurodegenerative Diseases
                Alzheimer Disease
                Medicine and Health Sciences
                Clinical Medicine
                Clinical Immunology
                Autoimmune Diseases
                Multiple Sclerosis
                Biology and Life Sciences
                Immunology
                Clinical Immunology
                Autoimmune Diseases
                Multiple Sclerosis
                Medicine and Health Sciences
                Immunology
                Clinical Immunology
                Autoimmune Diseases
                Multiple Sclerosis
                Medicine and Health Sciences
                Neurology
                Demyelinating Disorders
                Multiple Sclerosis
                Medicine and Health Sciences
                Neurology
                Neurodegenerative Diseases
                Multiple Sclerosis
                Biology and Life Sciences
                Biotechnology
                Medical Devices and Equipment
                Medicine and Health Sciences
                Medical Devices and Equipment
                Engineering and Technology
                Electronics
                Accelerometers
                Medicine and Health Sciences
                Neurology
                Neurodegenerative Diseases
                Movement Disorders
                Parkinson Disease
                Medicine and Health Sciences
                Neurology
                Cerebrovascular Diseases
                Stroke
                Medicine and Health Sciences
                Vascular Medicine
                Stroke
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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