Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

A systems approach for data compression and latency reduction in cortically controlled brain machine interfaces.

Karim G Oweiss1

  • 1Electrical and Computer Engineering Department, Michigan State University, East Lansing, MI 48824, USA. koweiss@msu.edu

IEEE Transactions on Bio-Medical Engineering
|July 13, 2006
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Proceedings of the Third Annual Deep Brain Stimulation Think Tank: A Review of Emerging Issues and Technologies.

Frontiers in neuroscience·2016
Same author

Neuroplasticity subserving the operation of brain-machine interfaces.

Neurobiology of disease·2015
Same author

Temporal precision in population-but not individual neuron-dynamics reveals rapid experience-dependent plasticity in the rat barrel cortex.

Frontiers in computational neuroscience·2014
Same author

A fully automated rodent conditioning protocol for sensorimotor integration and cognitive control experiments.

Journal of visualized experiments : JoVE·2014
Same author

Sorting and tracking neuronal spikes via simple thresholding.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2013
Same author

Neural feedback for instantaneous spatiotemporal modulation of afferent pathways in bi-directional brain-machine interfaces.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2011
Same journal

Enhancing Volumetric Imaging in Linear-Array Photoacoustic Tomography: multiview fusion with deep learning.

IEEE transactions on bio-medical engineering·2026
Same journal

Robust Rule-based Heuristic Assistance Strategy for a Semi-Active Shoulder Exoskeleton Used in Overhead Work.

IEEE transactions on bio-medical engineering·2026
Same journal

Highly Accelerated 1-mm Isotropic 3D Chemical Exchange Saturation Transfer MRI Using Wave-Co-CAIPI at 5 Tesla.

IEEE transactions on bio-medical engineering·2026
Same journal

Systematic Evaluation of Hip Exoskeleton Assistance Parameters for Enhancing Gait Stability During Ground Slip Perturbations.

IEEE transactions on bio-medical engineering·2026
Same journal

SleepConFormer: A Single-Channel EEG Framework for Sleep Staging and Consciousness Assessment in Patients with Disorders of Consciousness.

IEEE transactions on bio-medical engineering·2026
Same journal

Modeling Partial and Total Support of Left Ventricular Assist Device for Discrete Hemodynamic Control Framework.

IEEE transactions on bio-medical engineering·2026
See all related articles

This study introduces a novel data compression method for neural signals, reducing bandwidth and latency. The approach enhances signal processing for improved extracutaneous transmission and data fidelity.

Area of Science:

  • Neuroscience
  • Signal Processing
  • Biomedical Engineering

Background:

  • High-density microelectrode arrays in the cortex generate large neural signal datasets.
  • Extracutaneous transmission of neural data faces bandwidth limitations, often requiring on-chip processing.
  • Current methods for neural signal processing and transmission can be inefficient.

Purpose of the Study:

  • To propose a new data compression approach for neural signals recorded by high-density microelectrode arrays.
  • To reduce bandwidth requirements and latency during extracutaneous transmission of neural data.
  • To offer a potential alternative to on-chip spike detection and sorting.

Main Methods:

  • Exploiting temporal and spatial characteristics of neural recordings for redundancy reduction.

Related Experiment Videos

  • Utilizing discrete wavelet transform for temporal processing and exploiting sparseness.
  • Employing quasi-periodic eigendecomposition of the data covariance matrix for spatial processing.

    • Main Results:

    • Substantial improvements in lower transmission bandwidth, reduced latency, and optimized processor utilization.
    • Demonstrated superior denoising capabilities of the proposed signal processing algorithms.
    • Achieved higher fidelity of the obtained neural signals post-compression.

    Conclusions:

    • The proposed data compression approach effectively addresses bandwidth limitations in neural signal transmission.
    • The method offers significant advantages over current on-chip processing techniques.
    • This approach enhances the efficiency and quality of extracutaneous neural data transfer.