EEG analysis of mixed-reality music rehabilitation system for post-stroke lower limb therapy

Wei Chiao Chang, Li-Wei Ko*, Kuen Han Yu, Yu Chun Ho, Chia Hsin Chen, Yuh Jyh Jong, Yi-Pai Huang

*Corresponding author for this work

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Lots of evidence and guidelines recommended that stroke patients have to do the rehabilitation all the time, but in fact, the ratio of patients doing the rehabilitation is usually less than one third. In order to enhance the rehabilitation efficacy, we develop an innovative mixed-reality music rehabilitation (MR2) system, which is consisted of an MR goggle, inertial measurement unit sensors, and an EEG system. Several music contents with different levels are implemented into the MR system. While doing the rehabilitation task, our system can monitor patient's both gait information and electroencephalographic (EEG) signals to understand the rehabilitation performance in both central and peripheral nervous systems. The MR2 system has been pilot testing on two stroke patients and three healthy controls. Experiment results show that the patient's motor function is significantly activating when wearing the MR2 system during the rehabilitation task. Furthermore, the gait analysis results also show that flexion angle of the hemiplegic knee during walking was significantly improved when following the tempo of the MR music content in the rehabilitation. The pilot testing results provide new insights into the understanding of complex brain functions of patients actively and continuously performing the rehabilitation ordinary tasks within the mixed-reality applications.

Original languageEnglish
Pages (from-to)372-380
Number of pages9
JournalJournal of the Society for Information Display
Volume27
Issue number6
DOIs
StatePublished - 1 Jun 2019

Keywords

  • EEG analysis
  • event-related synchronization
  • gait analysis
  • mixed reality
  • music therapy
  • post-stroke rehabilitation

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