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 Concept Videos

Muscle Stimulation Frequency01:22

Muscle Stimulation Frequency

3.3K
The contraction strength of muscles is regulated by motor neurons, which modulate the frequency of action potentials dispatched to the motor units based on the body's requirements. This process of varying the muscle stimulation frequency allows muscles to contract with a force that is precisely tailored to the needs of the moment, whether lifting a feather or a heavy box.
Wave summation
At low firing rates, motor neurons induce individual twitch contractions in muscle fibers. These twitches...
3.3K
Motor Unit Stimulation01:20

Motor Unit Stimulation

2.5K
When the neuron of a motor unit fires an action potential, it triggers a series of events, leading to a twitch contraction in the muscle fibers. The process of excitation-contraction coupling is crucial in relaying the action potential to the muscle fibers.
The latent period of contraction marks the onset of excitation-contraction coupling, when the action potential propagates across the sarcolemma, preparing the muscle fibers for contraction. As the fibers enter the contraction phase, the...
2.5K

You might also read

Related Articles

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

Sort by
Same author

Solving the problem of inception: a cross-species perspective on strategies for a mechanistic refinement of intracortical microstimulation.

Journal of neural engineering·2026
Same author

Targeting Optimal Grasp-Related Cortical Areas for Intracortical Brain-Machine Interfaces after Spinal Cord Injury.

medRxiv : the preprint server for health sciences·2025
Same author

Simplified control of neuromuscular stimulation systems for restoration of reach with limb stiffness as a modifiable degree of freedom.

Journal of neural engineering·2025
Same journal

Cortex-anchored sensor-space harmonics for event-related EEG.

Journal of neural engineering·2026
Same journal

Neural mechanisms of mixed speech and grasp representation in sensorimotor cortices.

Journal of neural engineering·2026
Same journal

Developing a binary communication protocol between biological neural networks using virtual white matter.

Journal of neural engineering·2026
Same journal

Spatiotemporally distinctive astrocytic and neuronal responses to repetitive intracortical microstimulation.

Journal of neural engineering·2026
Same journal

A neural mass modelling framework for evaluating EEG source localisation of seizure activity.

Journal of neural engineering·2026
Same journal

Functional and effective connectivity methods from SEEG for characterizing epileptogenic networks in refractory epilepsy: a comprehensive review and future directions.

Journal of neural engineering·2026
See all related articles

Related Experiment Video

Updated: Oct 17, 2025

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
11:06

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

Published on: April 12, 2016

10.6K

Improving reaching with functional electrical stimulation by incorporating stiffness modulation.

Tyler Johnson1,2,3, Dawn Taylor1,2,3

  • 1Cleveland Clinic, Cleveland, OH, United States of America.

Journal of Neural Engineering
|October 13, 2021
PubMed
Summary
This summary is machine-generated.

Modulating muscle coactivation during functional electrical stimulation (FES) improves upper-limb reaching performance and reduces energy use after spinal cord injury. This brain-controlled FES approach enhances restoration of arm function.

Keywords:
brain–computer interfacebrain–machine interfacecocontractionfunctional electrical stimulationimpedancemuscle fatigueneuromuscular stimulation

More Related Videos

Use of a Foot-Induced Digitally Controlled Resistance Device for Functional Magnetic Resonance Imaging Evaluation in Patients with Foot Paresis
08:55

Use of a Foot-Induced Digitally Controlled Resistance Device for Functional Magnetic Resonance Imaging Evaluation in Patients with Foot Paresis

Published on: July 7, 2023

412
Paradigms of Lower Extremity Electrical Stimulation Training After Spinal Cord Injury
08:07

Paradigms of Lower Extremity Electrical Stimulation Training After Spinal Cord Injury

Published on: February 1, 2018

12.8K

Related Experiment Videos

Last Updated: Oct 17, 2025

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
11:06

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

Published on: April 12, 2016

10.6K
Use of a Foot-Induced Digitally Controlled Resistance Device for Functional Magnetic Resonance Imaging Evaluation in Patients with Foot Paresis
08:55

Use of a Foot-Induced Digitally Controlled Resistance Device for Functional Magnetic Resonance Imaging Evaluation in Patients with Foot Paresis

Published on: July 7, 2023

412
Paradigms of Lower Extremity Electrical Stimulation Training After Spinal Cord Injury
08:07

Paradigms of Lower Extremity Electrical Stimulation Training After Spinal Cord Injury

Published on: February 1, 2018

12.8K

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Rehabilitation Robotics

Background:

  • Functional electrical stimulation (FES) combined with intracortical recordings shows promise for restoring upper-limb function after spinal cord injury.
  • A challenge in FES is that multiple muscle stimulation patterns can achieve a desired limb position, impacting performance and energy efficiency.

Purpose of the Study:

  • To investigate the impact of modulating antagonist muscle coactivation during FES on reaching performance and energy consumption.
  • To develop and optimize a method for automatically adjusting coactivation levels based on decoded kinematic information.

Main Methods:

  • Utilized simulations to test a suite of lookup tables with varying coactivation levels for arm reaching control.
  • Optimized a function to automatically switch between coactivation tables based on decoded endpoint speed and its derivative.
  • Compared performance and energy usage of the dynamic modulation method against fixed coactivation levels.

Main Results:

  • Dynamically modulating limb stiffness through coactivation significantly improved energy usage and/or movement performance.
  • A simple function based on decoded speed and its derivative effectively controlled coactivation levels.
  • The multi-table method demonstrated enhanced reaching capabilities compared to fixed coactivation.

Conclusions:

  • Modulating muscle coactivation during brain-controlled FES is a viable strategy to improve energy efficiency and movement performance.
  • This approach enhances the potential of FES for restoring reaching function in individuals with paralysis.
  • Dynamic control of limb stiffness offers a more adaptable and efficient FES system.