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      Low-Cost Tracking Systems Allow Fine Biomechanical Evaluation of Upper-Limb Daily-Life Gestures in Healthy People and Post-Stroke Patients

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          Abstract

          Since the release of the first Kinect in 2011, low-cost technologies for upper-limb evaluation has been employed frequently for rehabilitation purposes. However, a limited number of studies have assessed the potential of the Kinect V2 for motor evaluations. In this paper, a simple biomechanical protocol has been developed, in order to assess the performances of healthy people and patients, during daily-life reaching movements, with focus on some of the patients’ common compensatory strategies. The assessment considers shoulder range of motion, elbow range of motion, trunk compensatory strategies, and movement smoothness. Seventy-seven healthy people and twenty post-stroke patients participated to test the biomechanical assessment. The testing protocol included four different experimental conditions: (1) dominant limb and (2) non-dominant limb of 77 healthy people, and (3) the more impaired limb of 20 post-stroke hemiparetic patients, and (4) the less-impaired limb of 11 patients (subgroup of the original 20). Biomechanical performances of the four groups were compared. Results showed that the dominant and non-dominant limbs of healthy people had comparable performances ( p > 0.05). On the contrary, condition (3) showed statistically significant differences between the healthy dominant/non-dominant limb and the less-affected limb in hemiparetic patients, for all parameters of assessment ( p < 0.001). In some cases, the less-affected limb of the patients also showed statistical differences ( p < 0.05), with respect to the healthy people. Such results suggest that Kinect V2 has the potential for being employed at home, laboratory or clinical environment, for the evaluation of patients’ motor performances.

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          Most cited references53

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          A Kinect-based system for physical rehabilitation: a pilot study for young adults with motor disabilities.

          This study assessed the possibility of rehabilitating two young adults with motor impairments using a Kinect-based system in a public school setting. This study was carried out according to an ABAB sequence in which A represented the baseline and B represented intervention phases. Data showed that the two participants significantly increased their motivation for physical rehabilitation, thus improving exercise performance during the intervention phases. Practical and developmental implications of the findings are discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.
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            Training modalities in robot-mediated upper limb rehabilitation in stroke: a framework for classification based on a systematic review

            Robot-mediated post-stroke therapy for the upper-extremity dates back to the 1990s. Since then, a number of robotic devices have become commercially available. There is clear evidence that robotic interventions improve upper limb motor scores and strength, but these improvements are often not transferred to performance of activities of daily living. We wish to better understand why. Our systematic review of 74 papers focuses on the targeted stage of recovery, the part of the limb trained, the different modalities used, and the effectiveness of each. The review shows that most of the studies so far focus on training of the proximal arm for chronic stroke patients. About the training modalities, studies typically refer to active, active-assisted and passive interaction. Robot-therapy in active assisted mode was associated with consistent improvements in arm function. More specifically, the use of HRI features stressing active contribution by the patient, such as EMG-modulated forces or a pushing force in combination with spring-damper guidance, may be beneficial. Our work also highlights that current literature frequently lacks information regarding the mechanism about the physical human-robot interaction (HRI). It is often unclear how the different modalities are implemented by different research groups (using different robots and platforms). In order to have a better and more reliable evidence of usefulness for these technologies, it is recommended that the HRI is better described and documented so that work of various teams can be considered in the same group and categories, allowing to infer for more suitable approaches. We propose a framework for categorisation of HRI modalities and features that will allow comparing their therapeutic benefits.
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              Assessment scales in stroke: clinimetric and clinical considerations

              As stroke care has developed, there has been a need to robustly assess the efficacy of interventions both at the level of the individual stroke survivor and in the context of clinical trials. To describe stroke-survivor recovery meaningfully, more sophisticated measures are required than simple dichotomous end points, such as mortality or stroke recurrence. As stroke is an exemplar disabling long-term condition, measures of function are well suited as outcome assessment. In this review, we will describe functional assessment scales in stroke, concentrating on three of the more commonly used tools: the National Institutes of Health Stroke Scale, the modified Rankin Scale, and the Barthel Index. We will discuss the strengths, limitations, and application of these scales and use the scales to highlight important properties that are relevant to all assessment tools. We will frame much of this discussion in the context of “clinimetric” analysis. As they are increasingly used to inform stroke-survivor assessments, we will also discuss some of the commonly used quality-of-life measures. A recurring theme when considering functional assessment is that no tool suits all situations. Clinicians and researchers should chose their assessment tool based on the question of interest and the evidence base around clinimetric properties.
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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                11 March 2019
                March 2019
                : 19
                : 5
                : 1224
                Affiliations
                [1 ]Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (STIIMA), National Research Council of Italy (CNR), Via Alfonso Corti 12, 20133 Milan, Italy; lorenzo.molinaritosatti@ 123456stiima.cnr.it
                [2 ]Villa Beretta Rehabilitation Center, Valduce Hospital, Via Nazario Sauro 17, 23845 Costa Masnaga (LC), Italy; fmolteni@ 123456valduce.it
                Author notes
                [* ]Correspondence: alessandro.scano@ 123456stiima.cnr.it ; Tel.: +39-380-466-6915
                Author information
                https://orcid.org/0000-0002-1896-9325
                Article
                sensors-19-01224
                10.3390/s19051224
                6427560
                30862049
                3a0bedd9-190b-4512-82f6-a7082bac1a9e
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 08 February 2019
                : 06 March 2019
                Categories
                Article

                Biomedical engineering
                reaching,kinect v2,biomechanical evaluation,upper-limb,post-stroke patients
                Biomedical engineering
                reaching, kinect v2, biomechanical evaluation, upper-limb, post-stroke patients

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