Literature DB >> 34042413

State of the art and challenges for the classification of studies on electromechanical and robotic devices in neurorehabilitation: a scoping review.

Marialuisa Gandolfi1, Nicola Valè2, Federico Posteraro3, Giovanni Morone4, Antonella Dell'orco5, Anita Botticelli5, Eleonora Dimitrova2, Elisa Gervasoni6, Michela Goffredo7, Jacopo Zenzeri8, Arianna Antonini9, Carla Daniele10, Paolo Benanti11, Paolo Boldrini12, Donatella Bonaiuti13, Enrico Castelli14, Francesco Draicchio15, Vincenzo Falabella16, Silvia Galeri6, Francesca Gimigliano17, Mauro Grigioni18, Stefano Mazzon19, Franco Molteni20, Maurizio Petrarca21, Alessandro Picelli5, Michele Senatore22, Giuseppe Turchetti23, Daniele Giansanti18, Stefano Mazzoleni24.   

Abstract

INTRODUCTION: The rapid development of electromechanical and robotic devices has profoundly influenced neurorehabilitation. Growth in the scientific and technological aspects thereof is crucial for increasing the number of newly developed devices, and clinicians have welcomed such growth with enthusiasm. Nevertheless, improving the standard for the reporting clinical, technical, and normative aspects of such electromechanical and robotic devices remains an unmet need in neurorehabilitation. Accordingly, this study aimed to analyse the existing literature on electromechanical and robotic devices used in neurorehabilitation, considering the current clinical, technical, and regulatory classification systems. EVIDENCE ACQUISITION: Within the CICERONE Consensus Conference framework, studies on electromechanical and robotic devices used for upper- and lower-limb rehabilitation in persons with neurological disabilities in adulthood and childhood were reviewed. We have conducted a literature search using the following databases: MEDLINE, Cochrane Library, PeDro, Institute of Electrical and Electronics Engineers, Science Direct, and Google Scholar. Clinical, technical, and regulatory classification systems were applied to collect information on the electromechanical and robotic devices. The study designs and populations were investigated. EVIDENCE SYNTHESIS: Overall, 316 studies were included in the analysis. More than half (52%) of the studies were randomised controlled trials (RCTs). The population investigated the most suffered from strokes, followed by spinal cord injuries, multiple sclerosis, cerebral palsy, and traumatic brain injuries. In total, 100 devices were described; of these, 19% were certified with the CE mark. Overall, the main type of device was an exoskeleton. However, end-effector devices were primarily used for the upper limbs, whereas exoskeletons were used for the lower limbs (for both children and adults).
CONCLUSIONS: The current literature on robotic neurorehabilitation lacks detailed information regarding the technical characteristics of the devices used. This affects the understanding of the possible mechanisms underlying recovery. Unfortunately, many electromechanical and robotic devices are not provided with CE marks, strongly hindering the research on the clinical outcomes of rehabilitation treatments based on these devices. A more significant effort is needed to improve the description of the robotic devices used in neurorehabilitation in terms of the technical and functional details, along with high-quality RCT studies.

Entities:  

Year:  2021        PMID: 34042413     DOI: 10.23736/S1973-9087.21.06922-7

Source DB:  PubMed          Journal:  Eur J Phys Rehabil Med        ISSN: 1973-9087            Impact factor:   2.874


  4 in total

1.  Kinematic Analysis of Exoskeleton-Assisted Community Ambulation: An Observational Study in Outdoor Real-Life Scenarios.

Authors:  Michela Goffredo; Paola Romano; Francesco Infarinato; Matteo Cioeta; Marco Franceschini; Daniele Galafate; Rebecca Iacopini; Sanaz Pournajaf; Marco Ottaviani
Journal:  Sensors (Basel)       Date:  2022-06-16       Impact factor: 3.847

2.  Retrospective Robot-Measured Upper Limb Kinematic Data From Stroke Patients Are Novel Biomarkers.

Authors:  Michela Goffredo; Sanaz Pournajaf; Stefania Proietti; Annalisa Gison; Federico Posteraro; Marco Franceschini
Journal:  Front Neurol       Date:  2021-12-21       Impact factor: 4.003

3.  Hybrid robot-assisted gait training for motor function in subacute stroke: a single-blind randomized controlled trial.

Authors:  Yen-Nung Lin; Shih-Wei Huang; Yi-Chun Kuan; Hung-Chou Chen; Wen-Shan Jian; Li-Fong Lin
Journal:  J Neuroeng Rehabil       Date:  2022-09-14       Impact factor: 5.208

4.  Information Security in Medical Robotics: A Survey on the Level of Training, Awareness and Use of the Physiotherapist.

Authors:  Lisa Monoscalco; Rossella Simeoni; Giovanni Maccioni; Daniele Giansanti
Journal:  Healthcare (Basel)       Date:  2022-01-14
  4 in total

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