Utilizing movement synergies to improve decoding performance for a brain machine interface

Yan T. Wong, David Putrino, Adam Weiss, Bijan Pesaran

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A major challenge facing the development of high degree of freedom (DOF) brain machine interface (BMI) devices is a limited ability to provide prospective users with independent control of many DOFs when using a complex prosthesis. It has been previously shown that a large range of complex hand postures can be replicated using a relatively low number of movement synergies. Thus, a high DOF joint space, such as the one the hand resides in, may be decomposed via principal component analysis (PCA) into a lower DOF (eigen-reach) space that contains most of the variance of the original movements. By decoding in this eigen-reach space, BMI users need only control a few eigen-reach values to be able to make movements using all DOFs in the arm and hand. In this paper we examine how using PCA before decoding neural activity may lead to improvements in decoding performance.

Original languageEnglish (US)
Title of host publication2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
Pages289-292
Number of pages4
DOIs
StatePublished - 2013
Event2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 - Osaka, Japan
Duration: Jul 3 2013Jul 7 2013

Other

Other2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
CountryJapan
CityOsaka
Period7/3/137/7/13

Fingerprint

Brain-Computer Interfaces
Decoding
Brain
Hand
Principal Component Analysis
Principal component analysis
Posture
User interfaces
Prostheses and Implants
Arm
Joints
Equipment and Supplies

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

Wong, Y. T., Putrino, D., Weiss, A., & Pesaran, B. (2013). Utilizing movement synergies to improve decoding performance for a brain machine interface. In 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 (pp. 289-292). [6609494] https://doi.org/10.1109/EMBC.2013.6609494

Utilizing movement synergies to improve decoding performance for a brain machine interface. / Wong, Yan T.; Putrino, David; Weiss, Adam; Pesaran, Bijan.

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013. 2013. p. 289-292 6609494.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wong, YT, Putrino, D, Weiss, A & Pesaran, B 2013, Utilizing movement synergies to improve decoding performance for a brain machine interface. in 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013., 6609494, pp. 289-292, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013, Osaka, Japan, 7/3/13. https://doi.org/10.1109/EMBC.2013.6609494
Wong YT, Putrino D, Weiss A, Pesaran B. Utilizing movement synergies to improve decoding performance for a brain machine interface. In 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013. 2013. p. 289-292. 6609494 https://doi.org/10.1109/EMBC.2013.6609494
Wong, Yan T. ; Putrino, David ; Weiss, Adam ; Pesaran, Bijan. / Utilizing movement synergies to improve decoding performance for a brain machine interface. 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013. 2013. pp. 289-292
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