Chan, Vicky

Cramer, Steven C

Ingemanson, Morgan L

Reinkensmeyer, David J

Rowe, Justin B

eScholarship - University of California

UC IrvineUC Irvine Previously Published WorksTitleRobotic Retraining of Finger Movements After Stroke.Permalinkhttps://escholarship.org/uc/item/3jd4w5dgAuthorsIngemanson, Morgan LRowe, Justin BChan, Vickyet al.Publication Date2016Copyright InformationThis work is made available under the terms of a Creative Commons Attribution License, availalbe at https://creativecommons.org/licenses/by/4.0/ Peer reviewedeScholarship.org Powered by the California Digital LibraryUniversity of CaliforniaVOLUNTEER WARNING SIGNS DONATE FREE ACCESS | ARTICLEINTERNATIONAL STROKE CONFERENCE POSTER ABSTRACTSSESSION TITLE: CLINICAL REHABILITATION AND RECOVERY POSTERS IIAbstract TP155: Robotic Retraining of Finger MovementsAfter StrokeMorgan L Ingemanson, Justin B Rowe, Vicky Chan, Steven C Cramer, and David J ReinkensmeyerUniv ofCalifornia, Irvine, Irvine, CAAbstractBackground: Robots aid motor rehabilitation, but there has been limited attention to recovery offinger movements. This study evaluated robotic assistance during finger movement training.Functional MRI (fMRI) was acquired at baseline to understand predictors of treatment gains.Methods: Patients with chronic stroke underwent a baseline fMRI scan, alternating rest withaffected-side finger movements similar to those made during robotic therapy. Next, subjectsreceived therapy 3 hr/wk for 3 weeks using FINGER (Finger Individuating Grasp Exercise Robot),with which subjects moved their paretic index and middle fingers to play a musical game similar toGuitarHero. FINGER used an assistance-as-needed algorithm to facilitate completion of graspingmovements, which increased sensory feedback without altering voluntary motor output. Participantswere randomized to receive High Assistance (to insure 85% success) or Low Assistance (55%success).Results: 30 subjects (mean age 58 yr; baseline Fugl-Meyer 46 out of 66; 37 mo post-stroke)completed the study. Significant gains were found in the primary outcome measure, change in Box& Blocks (B&B) score (23 to 25.5, p<0.0001). There was no difference between High and LowAssistance groups in the primary endpoint (p=0.65), though some secondary outcomes favoredHigh Assistance. The fMRI scans found that greater treatment gains were associated with higherlaterality index in primary sensory cortex, indicating greater boost in B&B score over time with higherpretreatment balance of activation towards ipsilesional rather than contralesional sensory cortex;laterality index in primary motor cortex lacked predictive value.Conclusions: Significant motor gains were found with a robotic device that targets fingermovements. Sensory factors appear key: treatment content emphasized augmented sensoryOriginally published 1 Feb 2016 Stroke. 2016;47:ATP155feedback, and the hemispheric balance of fMRI activation within sensory but not motor cortexpredicted treatment gains. Together these findings suggest Hebbian rules of sensorimotor cortexplasticity during finger robotic therapy after stroke.FootnotesAuthor Disclosures: M.L. Ingemanson: None. J.B. Rowe: None. V. Chan: None. S.C. Cramer:Consultant/Advisory Board; Modest; Roche, MicroTransponder. Ownership Interest; Significant;personlRN. Consultant/Advisory Board; Significant; RAND Corp, Dart Neuroscience. D.J.Reinkensmeyer: Ownership Interest; Significant; Flint Rehabilitation Devices.  Back to top StrokeAHA JournalsArteriosclerosis, Thrombosis, and Vascular Biology (ATVB)CirculationCirc: Arrhythmia and ElectrophysiologyCirc: Genomic and Precision MedicineCirc: Cardiovascular ImagingCirc: Cardiovascular InterventionsCirc: Cardiovascular Quality & OutcomesCirc: Heart FailureCirculation ResearchHypertensionStrokeJournal of the American Heart Association (JAHA)Journal InformationAbout Stroke

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Robotic Retraining of Finger Movements After Stroke.

https://escholarship.org/content/qt3jd4w5dg/qt3jd4w5dg.pdf?t=pri4j9

Robotic Retraining of Finger Movements After Stroke.

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