Advanced Robotic Therapy Integrated Centers (ARTIC): an international collaboration facilitating the application of rehabilitation technologies

Autor: Deborah Gaebler-Spira, Anne O’Brien, Alessandra Scarton, Anne Chan, Andreas Meyer-Heim, Tara Egan, Hubertus J. A. van Hedel, Amber Devers, Won Seok Kim, Alberto Esquenazi, Michael L. Boninger, Karen Chua, Sebastian A. Schroeder, Jens Carsten Möller, Daniel Zutter, Tamsin Reed, Paolo Bonato, Nam-Jong Paik, Steffen Berweck, Liliana P. Paredes, Jakub Petioky, Judith V. Graser, B. Warken, Giacomo Severini, Raoul Schweinfurther
Rok vydání: 2018
Předmět:
Zdroj: Journal of NeuroEngineering and Rehabilitation
BASE-Bielefeld Academic Search Engine
Journal of NeuroEngineering and Rehabilitation, Vol 15, Iss 1, Pp 1-16 (2018)
ISSN: 1743-0003
DOI: 10.1186/s12984-018-0366-y
Popis: 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®.
Databáze: OpenAIRE
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