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2022 | OriginalPaper | Buchkapitel

Effects of Brain-Computer Interface and Classical Motor Imagery for Upper Limb Impairment After Stroke: A Case Report

verfasst von : Yi-Qian Hu, Rong-Rong Lu, Tian-Hao Gao, Jie Zhuang, Yu-Long Bai

Erschienen in: Intelligent Robotics and Applications

Verlag: Springer International Publishing

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Abstract

Background. There still exists limitations in the recovery of severe upper limb impairment after stroke, and brain computer interface maybe a hopeful therapy. Methods. A 76-year-old male hemiplegic patient with severe paretic upper limb was admitted. In the first four weeks, 20 sessions classic motor imagery was added in addition to routine treatments. Then, 20 sessions brain-computer interface training was added over the next four weeks. Behavioral characteristics, neuroelectrophysiology and neuroimaging were assessed at multiple time, such as the Fugl­Meyer Assessment Upper Extremity, the Motor Status Scale (MSS), the Action Research Arm Test (ARAT), Active range of motion of the paretic wrist and Modified Barthel Index (MBI). Functional magnetic resonance imaging (fMRI) was used to investigate the effect of the above interventions on the recovery of brain and its structural plasticity. Results. The patient's upper limb motor function improved after two different therapy interventions, however, the efficacy of BCI training was more obvious: after classic motor imagery, the paretic wrist could actively flex, but extension is still irrealizable. However, after BCI training, the paretic wrist was able to extend proactively. The fMRI findings revealed positive and dynamic changes on brain structure and function. Conclusion. BCI training could effectively promote the movement recovery after stroke than traditional motor imagery even if they showed apparent initial paralysis. An association between functional improvement and brain structure remodeling was observed. These findings serve as a conceptual investigations to encourage further relevant research.

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Literatur
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Metadaten
Titel
Effects of Brain-Computer Interface and Classical Motor Imagery for Upper Limb Impairment After Stroke: A Case Report
verfasst von
Yi-Qian Hu
Rong-Rong Lu
Tian-Hao Gao
Jie Zhuang
Yu-Long Bai
Copyright-Jahr
2022
DOI
https://doi.org/10.1007/978-3-031-13835-5_7