Skip to main content
Journal cover image

Three-dimensional, automated, real-time video system for tracking limb motion in brain-machine interface studies.

Publication ,  Journal Article
Peikon, ID; Fitzsimmons, NA; Lebedev, MA; Nicolelis, MAL
Published in: J Neurosci Methods
June 15, 2009

Collection and analysis of limb kinematic data are essential components of the study of biological motion, including research into biomechanics, kinesiology, neurophysiology and brain-machine interfaces (BMIs). In particular, BMI research requires advanced, real-time systems capable of sampling limb kinematics with minimal contact to the subject's body. To answer this demand, we have developed an automated video tracking system for real-time tracking of multiple body parts in freely behaving primates. The system employs high-contrast markers painted on the animal's joints to continuously track the three-dimensional positions of their limbs during activity. Two-dimensional coordinates captured by each video camera are combined and converted to three-dimensional coordinates using a quadratic fitting algorithm. Real-time operation of the system is accomplished using direct memory access (DMA). The system tracks the markers at a rate of 52 frames per second (fps) in real-time and up to 100fps if video recordings are captured to be later analyzed off-line. The system has been tested in several BMI primate experiments, in which limb position was sampled simultaneously with chronic recordings of the extracellular activity of hundreds of cortical cells. During these recordings, multiple computational models were employed to extract a series of kinematic parameters from neuronal ensemble activity in real-time. The system operated reliably under these experimental conditions and was able to compensate for marker occlusions that occurred during natural movements. We propose that this system could also be extended to applications that include other classes of biological motion.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

J Neurosci Methods

DOI

EISSN

1872-678X

Publication Date

June 15, 2009

Volume

180

Issue

2

Start / End Page

224 / 233

Location

Netherlands

Related Subject Headings

  • Video Recording
  • User-Computer Interface
  • Time Factors
  • Signal Processing, Computer-Assisted
  • Range of Motion, Articular
  • Pattern Recognition, Automated
  • Neurophysiology
  • Neurons
  • Neurology & Neurosurgery
  • Movement
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Peikon, I. D., Fitzsimmons, N. A., Lebedev, M. A., & Nicolelis, M. A. L. (2009). Three-dimensional, automated, real-time video system for tracking limb motion in brain-machine interface studies. J Neurosci Methods, 180(2), 224–233. https://doi.org/10.1016/j.jneumeth.2009.03.010
Peikon, Ian D., Nathan A. Fitzsimmons, Mikhail A. Lebedev, and Miguel A. L. Nicolelis. “Three-dimensional, automated, real-time video system for tracking limb motion in brain-machine interface studies.J Neurosci Methods 180, no. 2 (June 15, 2009): 224–33. https://doi.org/10.1016/j.jneumeth.2009.03.010.
Peikon ID, Fitzsimmons NA, Lebedev MA, Nicolelis MAL. Three-dimensional, automated, real-time video system for tracking limb motion in brain-machine interface studies. J Neurosci Methods. 2009 Jun 15;180(2):224–33.
Peikon, Ian D., et al. “Three-dimensional, automated, real-time video system for tracking limb motion in brain-machine interface studies.J Neurosci Methods, vol. 180, no. 2, June 2009, pp. 224–33. Pubmed, doi:10.1016/j.jneumeth.2009.03.010.
Peikon ID, Fitzsimmons NA, Lebedev MA, Nicolelis MAL. Three-dimensional, automated, real-time video system for tracking limb motion in brain-machine interface studies. J Neurosci Methods. 2009 Jun 15;180(2):224–233.
Journal cover image

Published In

J Neurosci Methods

DOI

EISSN

1872-678X

Publication Date

June 15, 2009

Volume

180

Issue

2

Start / End Page

224 / 233

Location

Netherlands

Related Subject Headings

  • Video Recording
  • User-Computer Interface
  • Time Factors
  • Signal Processing, Computer-Assisted
  • Range of Motion, Articular
  • Pattern Recognition, Automated
  • Neurophysiology
  • Neurons
  • Neurology & Neurosurgery
  • Movement