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 Video

Updated: Jul 7, 2026

Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy
10:22

Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy

Published on: December 6, 2016

Gripping-force identification using EEG and phase-demodulation approach.

Vito Logar1, Igor Skrjanc, Ales Belic

  • 1Faculty of Electrical Engineering, University of Ljubljana, Trzaska 25, SI-1000 Ljubljana, Slovenia. vito.logar@fe.uni-lj.si

Neuroscience Research
|February 5, 2008
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

Risdiplam treatment in adults with spinal muscular atrophy: a single-center, real-world study.

BMC neurology·2026
Same author

MyomiR Networks in Spinal Muscular Atrophy: Associations With Clinical Severity and Treatment Response.

Molecular neurobiology·2026
Same author

Large-scale exome analyses reveal new rare variant contributions in amyotrophic lateral sclerosis.

Nature genetics·2026
Same author

Correction: Shaky hands are a part of motor neuron disease phenotype: clinical and electrophysiological study of 77 patients.

Journal of neurology·2025
Same author

Genetic Variability in Oxidative Stress, Inflammatory, and Neurodevelopmental Pathways: Impact on the Susceptibility and Course of Spinal Muscular Atrophy.

Cellular and molecular neurobiology·2024
Same author

The endocrine manifestations of adults with spinal muscular atrophy.

Muscle & nerve·2024
Same journal

Transcriptomic and epigenetic characterization of paraventricular thalamic nucleus neurons in Polg1 mutant mice.

Neuroscience research·2026
Same journal

Modulation of the EEG alpha-band envelope during mental tasks: A task-related index based on second-order derivatives.

Neuroscience research·2026
Same journal

Enhanced calcium activity and transcriptomic alterations in iPSC-derived neurons from BAFME patients with repeat expansions.

Neuroscience research·2026
Same journal

Clustered protocadherinβs contribute to configuring functional cell populations in hippocampal-cortical regions.

Neuroscience research·2026
Same journal

ALS-associated protein TDP-43 disturbs axonal projections in the somatosensory cortex.

Neuroscience research·2026
Same journal

Microglial ontogeny and in vitro reconstruction: Bridging development and modeling.

Neuroscience research·2026
See all related articles

Researchers decoded gripping force from electroencephalography (EEG) signals using phase-demodulation. This brain-computer interface approach shows phase shifts in EEG are key for information transfer.

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Synchronized brain activity and phase dynamics are crucial for brain function and information transfer.
  • Electroencephalography (EEG) signals offer insights into brain activity but are complex superpositions of neural signals.

Purpose of the Study:

  • To investigate the fuzzy identification of brain-code during gripping-force control tasks.
  • To determine if encoded information, specifically gripping force, can be extracted from EEG signals using phase-demodulation.

Main Methods:

  • EEG data acquisition during visuomotor tasks involving gripping-force control.
  • Application of beta-rhythm filtering, phase demodulation, and principal component analysis.
  • Development and utilization of a fuzzy model for estimating gripping force from processed EEG signals.

More Related Videos

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
11:25

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

Published on: July 26, 2013

Related Experiment Videos

Last Updated: Jul 7, 2026

Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy
10:22

Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy

Published on: December 6, 2016

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
11:25

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

Published on: July 26, 2013

Main Results:

  • Successful estimation of gripping force using EEG signals as input to the fuzzy model.
  • Demonstration that information about gripping force can be decoded from EEG, despite signal complexity.
  • Cross-validation indicated consistent encoding of gripping force information across subjects.

Conclusions:

  • Phase shifts in EEG signals play a significant role in brain activity and information transfer.
  • The phase-demodulation method is a critical step for decoding neural information from EEG.
  • Fuzzy identification of brain-code is feasible for understanding motor control from EEG data.