Literature DB >> 22773253

Effects of robot-assisted therapy on stroke rehabilitation in upper limbs: systematic review and meta-analysis of the literature.

Nahid Norouzi-Gheidari1, Philippe S Archambault, Joyce Fung.   

Abstract

We systematically reviewed and analyzed the literature to find randomized controlled trials (RCTs) that employed robotic devices in upper-limb rehabilitation of people with stroke. Out of 574 studies, 12 matching the selection criteria were found. The Fugl-Meyer, Functional Independence Measure, Motor Power Scale, and Motor Status Scale outcome measures from the selected RCTs were pooled together, and the corresponding effect sizes were estimated. We found that when the duration/intensity of conventional therapy (CT) is matched with that of the robot-assisted therapy (RT), no difference exists between the intensive CT and RT groups in terms of motor recovery, activities of daily living, strength, and motor control. However, depending on the stage of recovery, extra sessions of RT in addition to regular CT are more beneficial than regular CT alone in motor recovery of the hemiparetic shoulder and elbow of patients with stroke; gains are similar to those that have been observed in intensive CT.

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Year:  2012        PMID: 22773253     DOI: 10.1682/jrrd.2010.10.0210

Source DB:  PubMed          Journal:  J Rehabil Res Dev        ISSN: 0748-7711


  72 in total

1.  Robotic measurement of arm movements after stroke establishes biomarkers of motor recovery.

Authors:  Hermano I Krebs; Michael Krams; Dimitris K Agrafiotis; Allitia DiBernardo; Juan C Chavez; Gary S Littman; Eric Yang; Geert Byttebier; Laura Dipietro; Avrielle Rykman; Kate McArthur; Karim Hajjar; Kennedy R Lees; Bruce T Volpe
Journal:  Stroke       Date:  2013-12-12       Impact factor: 7.914

2.  Robot Training With Vector Fields Based on Stroke Survivors' Individual Movement Statistics.

Authors:  Zachary A Wright; Emily Lazzaro; Kelly O Thielbar; James L Patton; Felix C Huang
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2017-10-16       Impact factor: 3.802

Review 3.  Robot-assisted Therapy in Stroke Rehabilitation.

Authors:  Won Hyuk Chang; Yun-Hee Kim
Journal:  J Stroke       Date:  2013-09-27       Impact factor: 6.967

Review 4.  Interventions for improving upper limb function after stroke.

Authors:  Alex Pollock; Sybil E Farmer; Marian C Brady; Peter Langhorne; Gillian E Mead; Jan Mehrholz; Frederike van Wijck
Journal:  Cochrane Database Syst Rev       Date:  2014-11-12

5.  Upper-limb kinematic reconstruction during stroke robot-aided therapy.

Authors:  E Papaleo; L Zollo; N Garcia-Aracil; F J Badesa; R Morales; S Mazzoleni; S Sterzi; E Guglielmelli
Journal:  Med Biol Eng Comput       Date:  2015-04-11       Impact factor: 2.602

Review 6.  Robot-assisted distal training improves upper limb dexterity and function after stroke: a systematic review and meta-regression.

Authors:  Menglu Zhao; Guangning Wang; Aimin Wang; Ling Jie Cheng; Ying Lau
Journal:  Neurol Sci       Date:  2022-01-28       Impact factor: 3.307

Review 7.  Brain repair after stroke--a novel neurological model.

Authors:  Steven L Small; Giovanni Buccino; Ana Solodkin
Journal:  Nat Rev Neurol       Date:  2013-11-12       Impact factor: 42.937

Review 8.  Robotic Therapy and the Paradox of the Diminishing Number of Degrees of Freedom.

Authors:  Hermano Igo Krebs; Eiichi Saitoh; Neville Hogan
Journal:  Phys Med Rehabil Clin N Am       Date:  2015-08-21       Impact factor: 1.784

9.  Robot-assisted training compared with an enhanced upper limb therapy programme and with usual care for upper limb functional limitation after stroke: the RATULS three-group RCT.

Authors:  Helen Rodgers; Helen Bosomworth; Hermano I Krebs; Frederike van Wijck; Denise Howel; Nina Wilson; Tracy Finch; Natasha Alvarado; Laura Ternent; Cristina Fernandez-Garcia; Lydia Aird; Sreeman Andole; David L Cohen; Jesse Dawson; Gary A Ford; Richard Francis; Steven Hogg; Niall Hughes; Christopher I Price; Duncan L Turner; Luke Vale; Scott Wilkes; Lisa Shaw
Journal:  Health Technol Assess       Date:  2020-10       Impact factor: 4.014

10.  Perceived effort affects choice of limb and reaction time of movements.

Authors:  Jing Wang; Peter S Lum; Reza Shadmehr; Sang Wook Lee
Journal:  J Neurophysiol       Date:  2020-11-04       Impact factor: 2.714

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