Literature DB >> 14523730

Robot-aided neurorehabilitation: from evidence-based to science-based rehabilitation.

H I Krebs1, B T Volpe, M Ferraro, S Fasoli, J Palazzolo, B Rohrer, L Edelstein, N Hogan.   

Abstract

There is no "magic bullet" in rehabilitation. In the absence of direct neural transplants, neurological rehabilitation is an arduous process. We have pioneered the clinical application of robotics in stroke rehabilitation and have shown evidence of the positive impact of targeted exercise on stroke recovery. In this article, we will review results obtained in the initial clinical trials with 96 stroke patients at the Burke Rehabilitation Hospital. We will provide evidence that robot-aided training enhances recovery, that this enhanced recovery is sustained in the long term, and that this recovery is not due to a general physiological improvement--in fact, it appears to be limb and muscle group specific. An evidence-based approach must now segue into a more scientific approach to stroke rehabilitation. Given the length of the required protocols and patients' variability and limited census, the practical limitations of the evidence-based approach are self-evident and extend trials for years. Each patient and lesion is unique in stroke rehabilitation, so there is no reason to believe that a "one-size-fits-all" optimal treatment exists. To optimize therapy for individual patients, we need science-based models. In this article, we will summarize the scientific tools and models that we are investigating and present some of the results to date.

Entities:  

Year:  2002        PMID: 14523730     DOI: 10.1310/6177-QDJJ-56DU-0NW0

Source DB:  PubMed          Journal:  Top Stroke Rehabil        ISSN: 1074-9357            Impact factor:   2.119


  31 in total

Review 1.  QSAR without borders.

Authors:  Eugene N Muratov; Jürgen Bajorath; Robert P Sheridan; Igor V Tetko; Dmitry Filimonov; Vladimir Poroikov; Tudor I Oprea; Igor I Baskin; Alexandre Varnek; Adrian Roitberg; Olexandr Isayev; Stefano Curtarolo; Denis Fourches; Yoram Cohen; Alan Aspuru-Guzik; David A Winkler; Dimitris Agrafiotis; Artem Cherkasov; Alexander Tropsha
Journal:  Chem Soc Rev       Date:  2020-05-01       Impact factor: 54.564

2.  Robotically facilitated virtual rehabilitation of arm transport integrated with finger movement in persons with hemiparesis.

Authors:  Alma S Merians; Gerard G Fluet; Qinyin Qiu; Soha Saleh; Ian Lafond; Amy Davidow; Sergei V Adamovich
Journal:  J Neuroeng Rehabil       Date:  2011-05-16       Impact factor: 4.262

3.  Normalized movement quality measures for therapeutic robots strongly correlate with clinical motor impairment measures.

Authors:  Ozkan Celik; Marcia K O'Malley; Corwin Boake; Harvey S Levin; Nuray Yozbatiran; Timothy A Reistetter
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2010-04-12       Impact factor: 3.802

4.  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

Review 5.  How a diverse research ecosystem has generated new rehabilitation technologies: Review of NIDILRR's Rehabilitation Engineering Research Centers.

Authors:  David J Reinkensmeyer; Sarah Blackstone; Cathy Bodine; John Brabyn; David Brienza; Kevin Caves; Frank DeRuyter; Edmund Durfee; Stefania Fatone; Geoff Fernie; Steven Gard; Patricia Karg; Todd A Kuiken; Gerald F Harris; Mike Jones; Yue Li; Jordana Maisel; Michael McCue; Michelle A Meade; Helena Mitchell; Tracy L Mitzner; James L Patton; Philip S Requejo; James H Rimmer; Wendy A Rogers; W Zev Rymer; Jon A Sanford; Lawrence Schneider; Levin Sliker; Stephen Sprigle; Aaron Steinfeld; Edward Steinfeld; Gregg Vanderheiden; Carolee Winstein; Li-Qun Zhang; Thomas Corfman
Journal:  J Neuroeng Rehabil       Date:  2017-11-06       Impact factor: 4.262

6.  Design and validation of low-cost assistive glove for hand assessment and therapy during activity of daily living-focused robotic stroke therapy.

Authors:  Dominic E Nathan; Michelle J Johnson; John R McGuire
Journal:  J Rehabil Res Dev       Date:  2009

7.  A comparison of functional and impairment-based robotic training in severe to moderate chronic stroke: a pilot study.

Authors:  Hermano Igo Krebs; Stephen Mernoff; Susan E Fasoli; Richard Hughes; Joel Stein; Neville Hogan
Journal:  NeuroRehabilitation       Date:  2008       Impact factor: 2.138

Review 8.  Robotics and other devices in the treatment of patients recovering from stroke.

Authors:  Bruce T Volpe; Mark Ferraro; Daniel Lynch; Paul Christos; Jennifer Krol; Christine Trudell; Hermano I Krebs; Neville Hogan
Journal:  Curr Atheroscler Rep       Date:  2004-07       Impact factor: 5.113

Review 9.  Sensorimotor training in virtual reality: a review.

Authors:  Sergei V Adamovich; Gerard G Fluet; Eugene Tunik; Alma S Merians
Journal:  NeuroRehabilitation       Date:  2009       Impact factor: 2.138

Review 10.  Technology-assisted training of arm-hand skills in stroke: concepts on reacquisition of motor control and therapist guidelines for rehabilitation technology design.

Authors:  Annick A A Timmermans; Henk A M Seelen; Richard D Willmann; Herman Kingma
Journal:  J Neuroeng Rehabil       Date:  2009-01-20       Impact factor: 4.262

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