Neuromagnetic decoding of simultaneous bilateral hand movements for multidimensional brain-machine interfaces

Abdelkader Nasreddine Belkacem, Shuichi Nishio, Takafumi Suzuki, Hiroshi Ishiguro, Masayuki Hirata

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)

Abstract

To provide multidimensional control, we describe the first reported decoding of bilateral hand movements by using single-trial magnetoencephalography signals as a new approach to enhance a user's ability to interact with a complex environment through a multidimensional brain-machine interface. Ten healthy participants performed or imagined four types of bilateral hand movements during neuromagnetic measurements. By applying a support vector machine (SVM) method to classify the four movements regarding the sensor data obtained from the sensorimotor area, we found the mean accuracy of a two-class classification using the amplitudes of neuromagnetic fields to be particularly suitable for real-time applications, with accuracies comparable to those obtained in previous studies involving unilateral movement. The sensor data from over the sensorimotor cortex showed discriminative time-series waveforms and time-frequency maps in the bilateral hemispheres according to the four tasks. Furthermore, we used four-class classification algorithms based on the SVM method to decode all types of bilateral movements. Our results provided further proof that the slow components of neuromagnetic fields carry sufficient neural information to classify even bilateral hand movements and demonstrated the potential utility of decoding bilateral movements for engineering purposes such as multidimensional motor control.

Original languageEnglish
Pages (from-to)1301-1310
Number of pages10
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume26
Issue number6
DOIs
Publication statusPublished - Jun 2018
Externally publishedYes

Keywords

  • Android
  • Bilateral movements
  • Brain-machine interface
  • Magnetoencephalography
  • Motor imagery
  • SVM classification
  • Voluntary motor control

ASJC Scopus subject areas

  • Internal Medicine
  • Neuroscience(all)
  • Biomedical Engineering
  • Rehabilitation

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