TY - JOUR
T1 - Advanced Robotic Therapy Integrated Centers (ARTIC)
T2 - An international collaboration facilitating the application of rehabilitation technologies
AU - Van Hedel, Hubertus J.A.
AU - Severini, Giacomo
AU - Scarton, Alessandra
AU - O'Brien, Anne
AU - Reed, Tamsin
AU - Gaebler-Spira, Deborah
AU - Egan, Tara
AU - Meyer-Heim, Andreas
AU - Graser, Judith
AU - Chua, Karen
AU - Zutter, Daniel
AU - Schweinfurther, Raoul
AU - Möller, J. Carsten
AU - Paredes, Liliana P.
AU - Esquenazi, Alberto
AU - Berweck, Steffen
AU - Schroeder, Sebastian
AU - Warken, Birgit
AU - Chan, Anne
AU - Devers, Amber
AU - Petioky, Jakub
AU - Paik, Nam Jong
AU - Kim, Won Seok
AU - Bonato, Paolo
AU - Boninger, Michael
AU - Fabara, Eric
AU - Adans-Dester, Catherine
AU - O'Brien Murby, Jean
AU - Laliberte, Lori
AU - Revivo, Gadi
AU - Lee, Stella
AU - Toczylowski, Theresa
AU - Chan, Kay Fei
AU - Wee, Seng Kwee
AU - Lim, Pang Hung
AU - Lim, Wei Sheong
AU - Wang, Juliana Yun Ying
AU - Lee, Wing Kuen
AU - Ong, Chui Ni
AU - Ong, Cheng Hong
AU - Pereira, Charlene Cheryl
AU - Lee, Siew Yee
AU - Dewor, Alexander
AU - Urban, Michael
AU - Aurich, Tabea
AU - Lucic, Anja
AU - Nastulla, Thomas
AU - Badura, Katharina
AU - Steinbichler, Josephine
AU - Ji, Myungki
AU - Oh, Yunsung
AU - Calabro, Salvatore
AU - Van Hiel, Leslie
AU - Spiess, Martina
AU - Lünenburger, Lars
AU - Colombo, Gery
AU - Maier, Irin
N1 - Funding Information:
The company Hocoma currently supports this network by means of financial support for programming the database and online meetings. Hocoma also provides resources to aid with communication between network members. However, Hocoma has no influence on the design of the study, data collection, analysis, and interpretation of data and in writing the manuscript nor decisions made within the ARTIC network.
Funding Information:
Funding for meetings in person has been financed by institutional or third party money of each network member. Hocoma AG, Volketswil, Switzerland (company) currently supports this network by means of financial support for programming the database and online meetings. Hocoma also provided personnel resources to aid communication between network members. Grants were obtained from the Swiss Foundation for Children with Cerebral Palsy and the Mäxi-Foundation further develop the database.
PY - 2018/4/6
Y1 - 2018/4/6
N2 - 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®.
AB - 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®.
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U2 - 10.1186/s12984-018-0366-y
DO - 10.1186/s12984-018-0366-y
M3 - Article
C2 - 29625628
AN - SCOPUS:85045002670
VL - 15
JO - Journal of NeuroEngineering and Rehabilitation
JF - Journal of NeuroEngineering and Rehabilitation
SN - 1743-0003
IS - 1
M1 - 30
ER -