UNLABELLED: Purpose state: The aim of this preliminary study was to test a data glove, CyberTouch™, combined with a virtual reality (VR) environment, for using in therapeutic training of reaching movements after spinal cord injury (SCI). METHOD: Nine patients with thoracic SCI were selected to perform a pilot study by comparing two treatments: patients in the intervention group (IG) conducted a VR training based on the use of a data glove, CyberTouch™ for 2 weeks, while patients in the control group (CG) only underwent the traditional rehabilitation. Furthermore, two functional parameters were implemented in order to assess patient's performance of the sessions: normalized trajectory lengths and repeatability. RESULTS: Although no statistical significance was found, the data glove group seemed to obtain clinical changes in the muscle balance (MB) and functional parameters, and in the dexterity, coordination and fine grip tests. Moreover, every patient showed variations in at least one of the functional parameters, either along Y-axis trajectory or Z-axis trajectory. CONCLUSIONS: This study might be a step forward for the investigation of new uses of motion capture systems in neurorehabilitation, making it possible to train activities of daily living (ADLs) in motivational environments while measuring objectively the patient's functional evolution. Implications for Rehabilitation Key findings: A motion capture application based on a data glove is presented, for being used as a virtual reality tool for rehabilitation. This application has provided objective data about patient's functional performance. What the study has added: (1) This study allows to open new areas of research based on the use of different motion capture systems as rehabilitation tools, making it possible to train Activities of Daily Living in motivational environments. (2) Furthermore, this study could be a contribution for the development of clinical protocols to identify which types of patients will benefit most from the VR treatments, which interfaces are more suitable to be used in neurorehabilitation, and what types of virtual exercises will work best.
UNLABELLED: Purpose state: The aim of this preliminary study was to test a data glove, CyberTouch™, combined with a virtual reality (VR) environment, for using in therapeutic training of reaching movements after spinal cord injury (SCI). METHOD: Nine patients with thoracic SCI were selected to perform a pilot study by comparing two treatments: patients in the intervention group (IG) conducted a VR training based on the use of a data glove, CyberTouch™ for 2 weeks, while patients in the control group (CG) only underwent the traditional rehabilitation. Furthermore, two functional parameters were implemented in order to assess patient's performance of the sessions: normalized trajectory lengths and repeatability. RESULTS: Although no statistical significance was found, the data glove group seemed to obtain clinical changes in the muscle balance (MB) and functional parameters, and in the dexterity, coordination and fine grip tests. Moreover, every patient showed variations in at least one of the functional parameters, either along Y-axis trajectory or Z-axis trajectory. CONCLUSIONS: This study might be a step forward for the investigation of new uses of motion capture systems in neurorehabilitation, making it possible to train activities of daily living (ADLs) in motivational environments while measuring objectively the patient's functional evolution. Implications for Rehabilitation Key findings: A motion capture application based on a data glove is presented, for being used as a virtual reality tool for rehabilitation. This application has provided objective data about patient's functional performance. What the study has added: (1) This study allows to open new areas of research based on the use of different motion capture systems as rehabilitation tools, making it possible to train Activities of Daily Living in motivational environments. (2) Furthermore, this study could be a contribution for the development of clinical protocols to identify which types of patients will benefit most from the VR treatments, which interfaces are more suitable to be used in neurorehabilitation, and what types of virtual exercises will work best.
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