Literature DB >> 24110764

Proprioception rehabilitation training system for stroke patients using virtual reality technology.

Sun I Kim, In-Ho Song, Sangwoo Cho, In Young Kim, Jeonghun Ku, Youn Joo Kang, Dong Pyo Jang.   

Abstract

We investigated a virtual reality (VR) proprioceptive rehabilitation system that could manipulate the visual feedback of upper-limb during training and could do training by relying on proprioception feedback only. Virtual environments were designed in order to switch visual feedback on/off during upper-limb training. Two types of VR training tasks were designed for evaluating the effect of the proprioception focused training compared to the training with visual feedback. In order to evaluate the developed proprioception feedback virtual environment system, we recruited ten stroke patients (age: 54.7± 7.83years, on set: 3.29± 3.83 years). All patients performed three times PFVE task in order to check the improvement of proprioception function just before training session, after one week training, and after all training. In a comparison between FMS score and PFVE, the FMS score had a significant relationship with the error distance(r = -.662, n=10, p = .037) and total movement distance(r = -.726, n=10, p = .018) in PFVE. Comparing the training effect between in virtual environment with visual feedback and with proprioception, the click count, error distance and total error distance was more reduced in PFVE than VFVE. (Click count: p = 0.005, error distance: p = 0.001, total error distance: p = 0.007). It suggested that the proprioception feedback rather than visual feedback could be effective means to enhancing motor control during rehabilitation training. The developed VR system for rehabilitation has been verified in that stroke patients improved motor control after VR proprioception feedback training.

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Year:  2013        PMID: 24110764     DOI: 10.1109/EMBC.2013.6610577

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

Review 1.  Digital therapeutics in neurology.

Authors:  S Bonavita; L Lavorgna; G Abbadessa; F Brigo; M Clerico; S De Mercanti; F Trojsi; G Tedeschi
Journal:  J Neurol       Date:  2021-05-20       Impact factor: 4.849

2.  Robotics-assisted visual-motor training influences arm position sense in three-dimensional space.

Authors:  Bulmaro A Valdés; Mahta Khoshnam; Jason L Neva; Carlo Menon
Journal:  J Neuroeng Rehabil       Date:  2020-07-14       Impact factor: 4.262

  2 in total

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