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

Motor Unit Stimulation01:20

Motor Unit Stimulation

4.7K
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...
4.7K
Hierarchy of Motor Control01:18

Hierarchy of Motor Control

6.7K
The hierarchy of motor control refers to the different levels of organization and processing involved in controlling movement in the body. These levels range from higher cortical areas involved in planning and decision-making to lower spinal cord reflexes that respond automatically to external stimuli.
6.7K

You might also read

Related Articles

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

Sort by
Same author

A Deep Learning Framework With Domain Generalization and Few-Shot Learning for Locomotion Mode Classification Across Users, Sessions, and Prostheses.

IEEE transactions on medical robotics and bionics·2026
Same author

Quantifying human adaptation to a novel split-belt walking condition after broad experience at different belt speeds.

Scientific reports·2026
Same author

Learning powered mobility: caregiver perceptions of young children's capabilities and device impact.

Disability and rehabilitation. Assistive technology·2026
Same author

Assessing Functional Changes With the Integration of Wrist Flexion Into a Myoelectric Prosthesis.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2025
Same author

Evaluating the impact of channel count and feature set on online pattern recognition control of a virtual arm.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

Pattern Recognition Control of a 2 Degree-of-Freedom Prosthetic Device.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]·2025
Same journal

Analysis of End-Tidal CO2 Variability During Plateau Waves Episodes: An Information Theoretic Approach<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

AI and Tomosynthesis for Breast Cancer Molecular Subtyping: A step toward precision medicine<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Towards Sustainable Protein Recovery from Biological Waste: Assessing Polyethersulfone-based Microfiltration.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Analysis of the cardiovascular response to standardized polymicrobial peritonitis experimental model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Automated Wrist Ultrasound Image Bone Enhancement and Segmentation Using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

A Deep Learning approach for Depressive Symptoms assessment in Parkinson's disease patients using facial videos.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
See all related articles

Related Experiment Video

Updated: Mar 27, 2026

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
06:58

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

Published on: November 6, 2015

10.4K

Nonlinear mappings between discrete and simultaneous motions to decrease training burden of simultaneous pattern

Kimberly A Ingraham, Lauren H Smith, Ann M Simon

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |January 7, 2016
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel training method for pattern recognition (PR) control systems. Using artificial neural networks (ANNs) to simulate data significantly reduces classification error and training burden for simultaneous multi-degree of freedom (DOF) control.

    More Related Videos

    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
    11:54

    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

    Published on: May 8, 2021

    5.3K
    Combining Multiple Data Acquisition Systems to Study Corticospinal Output and Multi-segment Biomechanics
    08:48

    Combining Multiple Data Acquisition Systems to Study Corticospinal Output and Multi-segment Biomechanics

    Published on: January 9, 2016

    7.3K

    Related Experiment Videos

    Last Updated: Mar 27, 2026

    A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
    06:58

    A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

    Published on: November 6, 2015

    10.4K
    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
    11:54

    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

    Published on: May 8, 2021

    5.3K
    Combining Multiple Data Acquisition Systems to Study Corticospinal Output and Multi-segment Biomechanics
    08:48

    Combining Multiple Data Acquisition Systems to Study Corticospinal Output and Multi-segment Biomechanics

    Published on: January 9, 2016

    7.3K

    Area of Science:

    • Biomedical Engineering
    • Neuroscience
    • Rehabilitation Technology

    Background:

    • Real-time simultaneous pattern recognition (PR) control of multiple degrees of freedom (DOF) is crucial for advanced prosthetics and assistive devices.
    • Current training methods for PR control systems, often relying on extensive discrete (1-DOF) and simultaneous (2-DOF) motion data, pose a significant clinical challenge due to data requirements and retraining burdens.

    Purpose of the Study:

    • To present and evaluate a novel parallel classifier training method for simultaneous PR control that reduces the training data burden.
    • To investigate the efficacy of using artificial neural networks (ANNs) to generate simulated 2-DOF motion data from 1-DOF data for training LDA classifiers.

    Main Methods:

    • Developed a method using ANNs to create a nonlinear mapping between surface electromyography (sEMG) features of 2-DOF motions and their 1-DOF components.
    • Transformed experimentally collected 1-DOF sEMG features into simulated 2-DOF features using the established ANN mapping.
    • Trained parallel linear discriminant analysis (LDA) classifiers using three methods: (1) novel method (experimental 1-DOF + ANN-simulated 2-DOF), (2) experimental 1-DOF data only, and (3) experimental 1-DOF and 2-DOF data.

    Main Results:

    • The novel training method, utilizing ANN-simulated 2-DOF data alongside experimental 1-DOF data, resulted in significantly lower overall classification error (p<0.01).
    • This method also demonstrated significantly improved performance in predicting 2-DOF motions compared to training solely with experimental 1-DOF data (p<0.01).
    • Classification error was lowest when using the novel training method compared to using only experimental 1-DOF data.

    Conclusions:

    • The proposed ANN-based approach effectively simulates 2-DOF motion data from 1-DOF data, significantly enhancing PR control system performance.
    • This method alleviates the substantial data collection and retraining burden associated with traditional training protocols for simultaneous multi-DOF PR control.
    • The findings support the clinical feasibility of improved simultaneous PR control systems with reduced training demands.