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      Person-Generated Health Data in Simulated Rehabilitation Using Kinect for Stroke: Literature Review

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          Abstract

          Background

          Person- or patient-generated health data (PGHD) are health, wellness, and clinical data that people generate, record, and analyze for themselves. There is potential for PGHD to improve the efficiency and effectiveness of simulated rehabilitation technologies for stroke. Simulated rehabilitation is a type of telerehabilitation that uses computer technologies and interfaces to allow the real-time simulation of rehabilitation activities or a rehabilitation environment. A leading technology for simulated rehabilitation is Microsoft’s Kinect, a video-based technology that uses infrared to track a user’s body movements.

          Objective

          This review attempts to understand to what extent Kinect-based stroke rehabilitation systems (K-SRS) have used PGHD and to what benefit.

          Methods

          The review is conducted in two parts. In part 1, aspects of relevance for PGHD were searched for in existing systematic reviews on K-SRS. The following databases were searched: IEEE Xplore, Association of Computing Machinery Digital Library, PubMed, Biomed Central, Cochrane Library, and Campbell Collaboration. In part 2, original research papers that presented or used K-SRS were reviewed in terms of (1) types of PGHD, (2) patient access to PGHD, (3) PGHD use, and (4) effects of PGHD use. The search was conducted in the same databases as part 1 except Cochrane and Campbell Collaboration. Reference lists on K-SRS of the reviews found in part 1 were also included in the search for part 2. There was no date restriction. The search was closed in June 2017. The quality of the papers was not assessed, as it was not deemed critical to understanding PGHD access and use in studies that used K-SRS.

          Results

          In part 1, 192 papers were identified, and after assessment only 3 papers were included. Part 1 showed that previous reviews focused on technical effectiveness of K-SRS with some attention on clinical effectiveness. None of those reviews reported on home-based implementation or PGHD use. In part 2, 163 papers were identified and after assessment, 41 papers were included. Part 2 showed that there is a gap in understanding how PGHD use may affect patients using K-SRS and a lack of patient participation in the design of such systems.

          Conclusions

          This paper calls specifically for further studies of K-SRS—and for studies of technologies that allow patients to generate their own health data in general—to pay more attention to how patients’ own use of their data may influence their care processes and outcomes. Future studies that trial the effectiveness of K-SRS outside the clinic should also explore how patients and carers use PGHD in home rehabilitation programs.

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          Most cited references69

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          Virtual Reality Therapy for Adults Post-Stroke: A Systematic Review and Meta-Analysis Exploring Virtual Environments and Commercial Games in Therapy

          Background The objective of this analysis was to systematically review the evidence for virtual reality (VR) therapy in an adult post-stroke population in both custom built virtual environments (VE) and commercially available gaming systems (CG). Methods MEDLINE, CINAHL, EMBASE, ERIC, PSYCInfo, DARE, PEDro, Cochrane Central Register of Controlled Trials, and Cochrane Database of Systematic Reviews were systematically searched from the earliest available date until April 4, 2013. Controlled trials that compared VR to conventional therapy were included. Population criteria included adults (>18) post-stroke, excluding children, cerebral palsy, and other neurological disorders. Included studies were reported in English. Quality of studies was assessed with the Physiotherapy Evidence Database Scale (PEDro). Results Twenty-six studies met the inclusion criteria. For body function outcomes, there was a significant benefit of VR therapy compared to conventional therapy controls, G = 0.48, 95% CI = [0.27, 0.70], and no significant difference between VE and CG interventions (P = 0.38). For activity outcomes, there was a significant benefit of VR therapy, G = 0.58, 95% CI = [0.32, 0.85], and no significant difference between VE and CG interventions (P = 0.66). For participation outcomes, the overall effect size was G = 0.56, 95% CI = [0.02, 1.10]. All participation outcomes came from VE studies. Discussion VR rehabilitation moderately improves outcomes compared to conventional therapy in adults post-stroke. Current CG interventions have been too few and too small to assess potential benefits of CG. Future research in this area should aim to clearly define conventional therapy, report on participation measures, consider motivational components of therapy, and investigate commercially available systems in larger RCTs. Trial Registration Prospero CRD42013004338
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            Validity of the Microsoft Kinect for assessment of postural control.

            Clinically feasible methods of assessing postural control such as timed standing balance and functional reach tests provide important information, however, they cannot accurately quantify specific postural control mechanisms. The Microsoft Kinect™ system provides real-time anatomical landmark position data in three dimensions (3D), and given that it is inexpensive, portable and simple to setup it may bridge this gap. This study assessed the concurrent validity of the Microsoft Kinect™ against a benchmark reference, a multiple-camera 3D motion analysis system, in 20 healthy subjects during three postural control tests: (i) forward reach, (ii) lateral reach, and (iii) single-leg eyes-closed standing balance. For the reach tests, the outcome measures consisted of distance reached and trunk flexion angle in the sagittal (forward reach) and coronal (lateral reach) planes. For the standing balance test the range and deviation of movement in the anatomical landmark positions for the sternum, pelvis, knee and ankle and the lateral and anterior trunk flexion angle were assessed. The Microsoft Kinect™ and 3D motion analysis systems had comparable inter-trial reliability (ICC difference=0.06±0.05; range, 0.00-0.16) and excellent concurrent validity, with Pearson's r-values >0.90 for the majority of measurements (r=0.96±0.04; range, 0.84-0.99). However, ordinary least products analyses demonstrated proportional biases for some outcome measures associated with the pelvis and sternum. These findings suggest that the Microsoft Kinect™ can validly assess kinematic strategies of postural control. Given the potential benefits it could therefore become a useful tool for assessing postural control in the clinical setting. Copyright © 2012 Elsevier B.V. All rights reserved.
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              Systematic review of Kinect applications in elderly care and stroke rehabilitation

              In this paper we present a review of the most current avenues of research into Kinect-based elderly care and stroke rehabilitation systems to provide an overview of the state of the art, limitations, and issues of concern as well as suggestions for future work in this direction. The central purpose of this review was to collect all relevant study information into one place in order to support and guide current research as well as inform researchers planning to embark on similar studies or applications. The paper is structured into three main sections, each one presenting a review of the literature for a specific topic. Elderly Care section is comprised of two subsections: Fall detection and Fall risk reduction. Stroke Rehabilitation section contains studies grouped under Evaluation of Kinect’s spatial accuracy, and Kinect-based rehabilitation methods. The third section, Serious and exercise games, contains studies that are indirectly related to the first two sections and present a complete system for elderly care or stroke rehabilitation in a Kinect-based game format. Each of the three main sections conclude with a discussion of limitations of Kinect in its respective applications. The paper concludes with overall remarks regarding use of Kinect in elderly care and stroke rehabilitation applications and suggestions for future work. A concise summary with significant findings and subject demographics (when applicable) of each study included in the review is also provided in table format.
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                Author and article information

                Contributors
                Journal
                JMIR Rehabil Assist Technol
                JMIR Rehabil Assist Technol
                JRAT
                JMIR Rehabilitation and Assistive Technologies
                JMIR Publications (Toronto, Canada )
                2369-2529
                Jan-Jun 2018
                08 May 2018
                : 5
                : 1
                : e11
                Affiliations
                [1] 1 Health and Biomedical Informatics Centre University of Melbourne Melbourne Australia
                [2] 2 Department of Health and Medical Sciences School of Health Sciences Swinburne University of Technology Melbourne Australia
                Author notes
                Corresponding Author: Gerardo Luis Dimaguila dgl@ 123456student.unimelb.edu.au
                Author information
                http://orcid.org/0000-0002-3498-6256
                http://orcid.org/0000-0003-1616-2170
                http://orcid.org/0000-0003-4273-1816
                Article
                v5i1e11
                10.2196/rehab.9123
                5964303
                29739739
                c2db444d-f1a4-47e0-af35-fefb98dfd76d
                ©Gerardo Luis Dimaguila, Kathleen Gray, Mark Merolli. Originally published in JMIR Rehabilitation and Assistive Technology (http://rehab.jmir.org), 08.05.2018.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Rehabilitation and Assistive Technology, is properly cited. The complete bibliographic information, a link to the original publication on http://rehab.jmir.org/, as well as this copyright and license information must be included.

                History
                : 13 October 2017
                : 30 November 2017
                : 14 February 2018
                : 15 February 2018
                Categories
                Review
                Review

                health care information systems,kinect,patient-generated health data,person-generated health data,review,simulated rehabilitation,stroke,stroke rehabilitation,video games,virtual rehabilitation

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