Delta band contribution in cue based single trial classification of real and imaginary wrist movements.

The aim of this study was to classify different movements about the right wrist. Four different movements were performed: extension, flexion, pronation and supination. Two-class single trial classification was performed on six possible combinations of two movements (extension-flexion, extension-supi...

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Publicado en:Medical & Biological Engineering & Computing Vol. 46; no. 6; pp. 529 - 540
Autores principales: Vuckovic A, Sepulveda F, Vuckovic, Aleksandra, Sepulveda, Francisco
Formato: clinical trial research Journal Article
Publicado: Springer Nature Jun2008
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jun2008
      vid: 46
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s11517-008-0345-8
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        atl: Delta band contribution in cue based single trial classification of real and imaginary wrist movements.
      aug:
        au:
          Vuckovic A
          Sepulveda F
          Vuckovic, Aleksandra
          Sepulveda, Francisco
        affil: Centre for Rehabilitation Engineering, University of Glasgow, Glasgow, UK
      sug:
        subj:
          Classification
          Cues
          Movement Physiology
          Wrist Joint Physiology
          Adult
          Clinical Trials
          Electrodiagnosis
          Electroencephalography
          Female
          Imagination
          Limb Prosthesis
          Male
          Neural Networks (Computer)
          Human
          Adult: 19-44 years
          Female
          Male
      ab: The aim of this study was to classify different movements about the right wrist. Four different movements were performed: extension, flexion, pronation and supination. Two-class single trial classification was performed on six possible combinations of two movements (extension-flexion, extension-supination, extension-pronation, flexion-supination, flexion-pronation, pronation-supination). Both real and imaginary movements were analysed. The analysis was done in the joint time-frequency domain using the Gabor transform. Feature selection was based on the Davis-Bouldin Index (DBI) and feature classification was based on Elman's recurrent neural networks (ENN). The best classification results, near 80% true positive rate, for imaginary movements were achieved for discrimination between extension and any other type of movement. The experiments were run with 10 able-bodied subjects. For some subjects, real movement classification rates higher than 80% were achieved for any combination of movements, though not simultaneously for all six combinations of movements. For classification of the imaginary movements, the results suggest that the type of movement and frequency band play an important role. Unexpectedly, the delta band was found to carry significant class-related information.
      pubtype: Academic Journal
      doctype:
        clinical trial
        research
        Journal Article
      ougenre: Article
    language: English
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