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      The Effect of Applying Robot-Assisted Task-Oriented Training Using Human-Robot Collaborative Interaction Force Control Technology on Upper Limb Function in Stroke Patients: Preliminary Findings

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          Abstract

          Stroke is one of the leading causes of death and the primary cause of acquired disability worldwide. Many stroke survivors have difficulty using their upper limbs, which have important functional roles in the performance of daily life activities. Consequently, the independence and quality of life of most stroke patients are reduced. Robot-assisted therapy is an effective intervention for improving the upper limb function of individuals with stroke. Human-robot collaborative interaction force control technology is critical for improving the flexibility and followability of the robot's motion, thereby improving rehabilitation training outcomes. However, there are few reports on the effect of robot-assisted rehabilitative training on upper limb function. We applied this technology using a robot to assist patients with task-oriented training. Posttreatment changes in Fugl-Meyer and modified Barthel index (MBI) scores were assessed to determine whether this technology could improve the upper limb function of stroke patients. One healthy adult and five stroke patients, respectively, participated in functional and clinical experiments. The MBI and Fugl-Meyer scores of the five patients in the clinical experiments showed significant improvements after the intervention. The experimental results indicate that human-robot collaborative interaction force control technology is valuable for improving robots' properties and patients' recovery. This trial was registered in the Chinese clinical trial registry ( ChiCTR2000038676).

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          "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician.

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            Global, regional, and national burden of stroke, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

            Summary Background Stroke is a leading cause of mortality and disability worldwide and the economic costs of treatment and post-stroke care are substantial. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic, comparable method of quantifying health loss by disease, age, sex, year, and location to provide information to health systems and policy makers on more than 300 causes of disease and injury, including stroke. The results presented here are the estimates of burden due to overall stroke and ischaemic and haemorrhagic stroke from GBD 2016. Methods We report estimates and corresponding uncertainty intervals (UIs), from 1990 to 2016, for incidence, prevalence, deaths, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs). DALYs were generated by summing YLLs and YLDs. Cause-specific mortality was estimated using an ensemble modelling process with vital registration and verbal autopsy data as inputs. Non-fatal estimates were generated using Bayesian meta-regression incorporating data from registries, scientific literature, administrative records, and surveys. The Socio-demographic Index (SDI), a summary indicator generated using educational attainment, lagged distributed income, and total fertility rate, was used to group countries into quintiles. Findings In 2016, there were 5·5 million (95% UI 5·3 to 5·7) deaths and 116·4 million (111·4 to 121·4) DALYs due to stroke. The global age-standardised mortality rate decreased by 36·2% (−39·3 to −33·6) from 1990 to 2016, with decreases in all SDI quintiles. Over the same period, the global age-standardised DALY rate declined by 34·2% (−37·2 to −31·5), also with decreases in all SDI quintiles. There were 13·7 million (12·7 to 14·7) new stroke cases in 2016. Global age-standardised incidence declined by 8·1% (−10·7 to −5·5) from 1990 to 2016 and decreased in all SDI quintiles except the middle SDI group. There were 80·1 million (74·1 to 86·3) prevalent cases of stroke globally in 2016; 41·1 million (38·0 to 44·3) in women and 39·0 million (36·1 to 42·1) in men. Interpretation Although age-standardised mortality rates have decreased sharply from 1990 to 2016, the decrease in age-standardised incidence has been less steep, indicating that the burden of stroke is likely to remain high. Planned updates to future GBD iterations include generating separate estimates for subarachnoid haemorrhage and intracerebral haemorrhage, generating estimates of transient ischaemic attack, and including atrial fibrillation as a risk factor. Funding Bill & Melinda Gates Foundation
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              Ischaemic stroke

              Stroke is the second highest cause of death globally and a leading cause of disability, with an increasing incidence in developing countries. Ischaemic stroke caused by arterial occlusion is responsible for the majority of strokes. Management focuses on rapid reperfusion with intravenous thrombolysis and endovascular thrombectomy, which both reduce disability but are time-critical. Accordingly, improving the system of care to reduce treatment delays is key to maximizing the benefits of reperfusion therapies. Intravenous thrombolysis reduces disability when administered within 4.5 h of the onset of stroke. Thrombolysis also benefits selected patients with evidence from perfusion imaging of salvageable brain tissue for up to 9 h and in patients who awake with stroke symptoms. Endovascular thrombectomy reduces disability in a broad group of patients with large vessel occlusion when performed within 6 h of stroke onset and in patients selected by perfusion imaging up to 24 h following stroke onset. Secondary prevention of ischaemic stroke shares many common elements with cardiovascular risk management in other fields, including blood pressure control, cholesterol management and antithrombotic medications. Other preventative interventions are tailored to the mechanism of stroke, such as anticoagulation for atrial fibrillation and carotid endarterectomy for severe symptomatic carotid artery stenosis.
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                Author and article information

                Contributors
                Journal
                Biomed Res Int
                Biomed Res Int
                BMRI
                BioMed Research International
                Hindawi
                2314-6133
                2314-6141
                2021
                28 July 2021
                : 2021
                : 9916492
                Affiliations
                1Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, China
                2Shanghai Electric GeniKIT Medical Science and Technology Co. Ltd., Shanghai, China
                3National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, China
                Author notes

                Academic Editor: Dorota Formanowicz

                Author information
                https://orcid.org/0000-0002-7826-0844
                https://orcid.org/0000-0001-8434-7869
                https://orcid.org/0000-0002-3237-4539
                https://orcid.org/0000-0003-3982-3138
                https://orcid.org/0000-0003-0129-1498
                https://orcid.org/0000-0002-4516-4629
                Article
                10.1155/2021/9916492
                8342143
                34368358
                e9c55cb9-b5d0-4ee0-9fa6-eca3bf44da70
                Copyright © 2021 Qingming Qu et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 21 March 2021
                : 13 May 2021
                : 11 July 2021
                Funding
                Funded by: Medical Scientific Research Project of Jing'an District
                Award ID: 2016QN03
                Funded by: National Natural Science Foundation of China
                Award ID: 82021002
                Award ID: 9194830003
                Funded by: Ministry of Science and Technology of the People's Republic of China
                Award ID: 2018YFC2002301
                Award ID: 2018YFC2002300
                Categories
                Research Article

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