Advanced Robotic Therapy Integrated Centers (ARTIC): an international collaboration facilitating the application of rehabilitation technologies
Abstract Background The application of rehabilitation robots has grown during the last decade. While meta-analyses have shown beneficial effects of robotic interventions for some patient groups, the evidence is less in others. We established the Advanced Robotic Therapy Integrated Centers (ARTIC) ne...
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BMC
2018-04-01
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Series: | Journal of NeuroEngineering and Rehabilitation |
Online Access: | http://link.springer.com/article/10.1186/s12984-018-0366-y |
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record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hubertus J. A. van Hedel Giacomo Severini Alessandra Scarton Anne O’Brien Tamsin Reed Deborah Gaebler-Spira Tara Egan Andreas Meyer-Heim Judith Graser Karen Chua Daniel Zutter Raoul Schweinfurther J. Carsten Möller Liliana P. Paredes Alberto Esquenazi Steffen Berweck Sebastian Schroeder Birgit Warken Anne Chan Amber Devers Jakub Petioky Nam-Jong Paik Won-Seok Kim Paolo Bonato Michael Boninger for the ARTIC network |
spellingShingle |
Hubertus J. A. van Hedel Giacomo Severini Alessandra Scarton Anne O’Brien Tamsin Reed Deborah Gaebler-Spira Tara Egan Andreas Meyer-Heim Judith Graser Karen Chua Daniel Zutter Raoul Schweinfurther J. Carsten Möller Liliana P. Paredes Alberto Esquenazi Steffen Berweck Sebastian Schroeder Birgit Warken Anne Chan Amber Devers Jakub Petioky Nam-Jong Paik Won-Seok Kim Paolo Bonato Michael Boninger for the ARTIC network Advanced Robotic Therapy Integrated Centers (ARTIC): an international collaboration facilitating the application of rehabilitation technologies Journal of NeuroEngineering and Rehabilitation |
author_facet |
Hubertus J. A. van Hedel Giacomo Severini Alessandra Scarton Anne O’Brien Tamsin Reed Deborah Gaebler-Spira Tara Egan Andreas Meyer-Heim Judith Graser Karen Chua Daniel Zutter Raoul Schweinfurther J. Carsten Möller Liliana P. Paredes Alberto Esquenazi Steffen Berweck Sebastian Schroeder Birgit Warken Anne Chan Amber Devers Jakub Petioky Nam-Jong Paik Won-Seok Kim Paolo Bonato Michael Boninger for the ARTIC network |
author_sort |
Hubertus J. A. van Hedel |
title |
Advanced Robotic Therapy Integrated Centers (ARTIC): an international collaboration facilitating the application of rehabilitation technologies |
title_short |
Advanced Robotic Therapy Integrated Centers (ARTIC): an international collaboration facilitating the application of rehabilitation technologies |
title_full |
Advanced Robotic Therapy Integrated Centers (ARTIC): an international collaboration facilitating the application of rehabilitation technologies |
title_fullStr |
Advanced Robotic Therapy Integrated Centers (ARTIC): an international collaboration facilitating the application of rehabilitation technologies |
title_full_unstemmed |
Advanced Robotic Therapy Integrated Centers (ARTIC): an international collaboration facilitating the application of rehabilitation technologies |
title_sort |
advanced robotic therapy integrated centers (artic): an international collaboration facilitating the application of rehabilitation technologies |
publisher |
BMC |
series |
Journal of NeuroEngineering and Rehabilitation |
issn |
1743-0003 |
publishDate |
2018-04-01 |
description |
Abstract Background The application of rehabilitation robots has grown during the last decade. While meta-analyses have shown beneficial effects of robotic interventions for some patient groups, the evidence is less in others. We established the Advanced Robotic Therapy Integrated Centers (ARTIC) network with the goal of advancing the science and clinical practice of rehabilitation robotics. The investigators hope to exploit variations in practice to learn about current clinical application and outcomes. The aim of this paper is to introduce the ARTIC network to the clinical and research community, present the initial data set and its characteristics and compare the outcome data collected so far with data from prior studies. Methods ARTIC is a pragmatic observational study of clinical care. The database includes patients with various neurological and gait deficits who used the driven gait orthosis Lokomat® as part of their treatment. Patient characteristics, diagnosis-specific information, and indicators of impairment severity are collected. Core clinical assessments include the 10-Meter Walk Test and the Goal Attainment Scaling. Data from each Lokomat® training session are automatically collected. Results At time of analysis, the database contained data collected from 595 patients (cerebral palsy: n = 208; stroke: n = 129; spinal cord injury: n = 93; traumatic brain injury: n = 39; and various other diagnoses: n = 126). At onset, average walking speeds were slow. The training intensity increased from the first to the final therapy session and most patients achieved their goals. Conclusions The characteristics of the patients matched epidemiological data for the target populations. When patient characteristics differed from epidemiological data, this was mainly due to the selection criteria used to assess eligibility for Lokomat® training. While patients included in randomized controlled interventional trials have to fulfill many inclusion and exclusion criteria, the only selection criteria applying to patients in the ARTIC database are those required for use of the Lokomat®. We suggest that the ARTIC network offers an opportunity to investigate the clinical application and effectiveness of rehabilitation technologies for various diagnoses. Due to the standardization of assessments and the use of a common technology, this network could serve as a basis for researchers interested in specific interventional studies expanding beyond the Lokomat®. |
url |
http://link.springer.com/article/10.1186/s12984-018-0366-y |
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doaj-3a8059aff06346f98a3793501596700b2020-11-25T00:52:15ZengBMCJournal of NeuroEngineering and Rehabilitation1743-00032018-04-0115111610.1186/s12984-018-0366-yAdvanced Robotic Therapy Integrated Centers (ARTIC): an international collaboration facilitating the application of rehabilitation technologiesHubertus J. A. van Hedel0Giacomo Severini1Alessandra Scarton2Anne O’Brien3Tamsin Reed4Deborah Gaebler-Spira5Tara Egan6Andreas Meyer-Heim7Judith Graser8Karen Chua9Daniel Zutter10Raoul Schweinfurther11J. Carsten Möller12Liliana P. Paredes13Alberto Esquenazi14Steffen Berweck15Sebastian Schroeder16Birgit Warken17Anne Chan18Amber Devers19Jakub Petioky20Nam-Jong Paik21Won-Seok Kim22Paolo Bonato23Michael Boninger24for the ARTIC networkRehabilitation Center for Children and Adolescents, University Children’s Hospital ZurichDepartment of Physical Medicine and Rehabilitation, Harvard Medical School, at Spaulding Rehabilitation HospitalDepartment of Physical Medicine and Rehabilitation, Harvard Medical School, at Spaulding Rehabilitation HospitalDepartment of Physical Medicine and Rehabilitation, Harvard Medical School, at Spaulding Rehabilitation HospitalAcute Neurological Rehabilitation Unit, Wellington HospitalShirley Ryan AbilityLabShirley Ryan AbilityLabRehabilitation Center for Children and Adolescents, University Children’s Hospital ZurichRehabilitation Center for Children and Adolescents, University Children’s Hospital ZurichTan Tock Seng Hospital Rehabilitation CentreRehaklinik Zihlschlacht, Center for Neurological RehabilitationRehaklinik Zihlschlacht, Center for Neurological RehabilitationRehaklinik Zihlschlacht, Center for Neurological RehabilitationRehaklinik Zihlschlacht, Center for Neurological RehabilitationDepartment of Physical Medicine and Rehabilitation, MossRehabClinic for Neuropediatrics and Neurological Rehabilitation, Epilepsy center for children and adolescents, Schön Klinik VogtareuthPaediatric Neurology, Developmental Medicine and Social Paediatrics, Ludwig Maximilian University, Hauner Children’s HospitalPaediatric Neurology, Developmental Medicine and Social Paediatrics, Ludwig Maximilian University, Hauner Children’s HospitalSheltering Arms Physical Rehabilitation CenterSheltering Arms Physical Rehabilitation CenterRehabilitation Centre KladrubyDepartment of Rehabilitation Medicine, Seoul National University Bundang HospitalDepartment of Rehabilitation Medicine, Seoul National University Bundang HospitalDepartment of Physical Medicine and Rehabilitation, Harvard Medical School, at Spaulding Rehabilitation HospitalDepartment of Physical Medicine and Rehabilitation, University of Pittsburgh and VA Pittsburgh Health Care SystemAbstract Background The application of rehabilitation robots has grown during the last decade. While meta-analyses have shown beneficial effects of robotic interventions for some patient groups, the evidence is less in others. We established the Advanced Robotic Therapy Integrated Centers (ARTIC) network with the goal of advancing the science and clinical practice of rehabilitation robotics. The investigators hope to exploit variations in practice to learn about current clinical application and outcomes. The aim of this paper is to introduce the ARTIC network to the clinical and research community, present the initial data set and its characteristics and compare the outcome data collected so far with data from prior studies. Methods ARTIC is a pragmatic observational study of clinical care. The database includes patients with various neurological and gait deficits who used the driven gait orthosis Lokomat® as part of their treatment. Patient characteristics, diagnosis-specific information, and indicators of impairment severity are collected. Core clinical assessments include the 10-Meter Walk Test and the Goal Attainment Scaling. Data from each Lokomat® training session are automatically collected. Results At time of analysis, the database contained data collected from 595 patients (cerebral palsy: n = 208; stroke: n = 129; spinal cord injury: n = 93; traumatic brain injury: n = 39; and various other diagnoses: n = 126). At onset, average walking speeds were slow. The training intensity increased from the first to the final therapy session and most patients achieved their goals. Conclusions The characteristics of the patients matched epidemiological data for the target populations. When patient characteristics differed from epidemiological data, this was mainly due to the selection criteria used to assess eligibility for Lokomat® training. While patients included in randomized controlled interventional trials have to fulfill many inclusion and exclusion criteria, the only selection criteria applying to patients in the ARTIC database are those required for use of the Lokomat®. We suggest that the ARTIC network offers an opportunity to investigate the clinical application and effectiveness of rehabilitation technologies for various diagnoses. Due to the standardization of assessments and the use of a common technology, this network could serve as a basis for researchers interested in specific interventional studies expanding beyond the Lokomat®.http://link.springer.com/article/10.1186/s12984-018-0366-y |