Literature DB >> 27827517

Using robot fully assisted functional movements in upper-limb rehabilitation of chronic stroke patients: preliminary results.

Marco Caimmi1, Andrea Chiavenna2, Alessandro Scano2, Giulio Gasperini3, Chiara Giovanzana3, Lorenzo Molinari Tosatti2, Franco Molteni3.   

Abstract

BACKGROUND: Robotic rehabilitation is promising to promote function in stroke patients. The assist as needed training paradigm has shown to stimulate neuroplasticity but often cannot be used because stroke patients are too impaired to actively control the robot against gravity. AIM: To verify whether a rehabilitation intervention based on robot fully assisted reaching against gravity (RCH) and hand-to-mouth (HTM) can promote upper-limb function in chronic stroke.
DESIGN: Cohort study.
SETTING: Chronic stroke outpatients referring to the robotic rehabilitation lab of a rehabilitation centre. POPULATION: Ten chronic stroke patients with mild to moderate upper-limb hemiparesis.
METHODS: Patients underwent 12 sessions (3 per week) of robotic treatment using an end-effector robot Every session consisted of 20 minutes each of RCH and HtM; movements were fully assisted, but patients were asked to try to actively participate. The Fugl-Meyer Assessment (FMA) was the primary outcome measure; Medical Research Council and Modified Ashworth Scale were the secondary outcome measures.
RESULTS: All patients, but one, show functional improvements (FMA section A-D, mean increment 7.2±3.9 points, P<0.008).
CONCLUSIONS: This preliminary study shows that a robotic intervention based on functional movements, fully assisted, can be effective in promoting function in chronic stroke patients. These results are promising considering the short time of the intervention (1 month) and the time from the stroke event, which was large (27±20 months). A larger study, comprehensive of objective instrumental measures, is necessary to confirm the results. CLINICAL REHABILITATION IMPACT: This intervention could be extended even to subacute stroke and other neurological disorders.

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Year:  2016        PMID: 27827517     DOI: 10.23736/S1973-9087.16.04407-5

Source DB:  PubMed          Journal:  Eur J Phys Rehabil Med        ISSN: 1973-9087            Impact factor:   2.874


  4 in total

Review 1.  Use of machine learning in geriatric clinical care for chronic diseases: a systematic literature review.

Authors:  Avishek Choudhury; Emily Renjilian; Onur Asan
Journal:  JAMIA Open       Date:  2020-10-08

2.  Error-Related Negativity-Based Robot-Assisted Stroke Rehabilitation System: Design and Proof-of-Concept.

Authors:  Akshay Kumar; Lin Gao; Jiaming Li; Jiaxin Ma; Jianming Fu; Xudong Gu; Seedahmed S Mahmoud; Qiang Fang
Journal:  Front Neurorobot       Date:  2022-04-25       Impact factor: 3.493

3.  Robot Fully Assisted Upper-Limb Functional Movements Against Gravity to Drive Recovery in Chronic Stroke: A Pilot Study.

Authors:  Marco Caimmi; Chiara Giovanzana; Giulio Gasperini; Franco Molteni; Lorenzo Molinari Tosatti
Journal:  Front Neurol       Date:  2022-03-08       Impact factor: 4.003

4.  Reaching exercise for chronic paretic upper extremity after stroke using a novel rehabilitation robot with arm-weight support and concomitant electrical stimulation and vibration: before-and-after feasibility trial.

Authors:  Yumeko Amano; Tomokazu Noma; Seiji Etoh; Ryuji Miyata; Kentaro Kawamura; Megumi Shimodozono
Journal:  Biomed Eng Online       Date:  2020-05-06       Impact factor: 2.819

  4 in total

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