Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Muscle Coordination and Action

Muscle Coordination and Action

Muscle coordination is a complex and finely tuned process essential for smooth and purposeful movements like flexion, extension, adduction, abduction, and rotation. The human body orchestrates the actions of various muscles working in concert, each with a specific role. Four functional types describe how muscles work together: agonist, antagonist, synergist, and fixator.
Agonists
Agonist muscles, often called prime movers, are the primary muscles responsible for producing a specific movement....

You might also read

Related Articles

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

Sort by

Same author

Dual-variable force characterisation method for human-robot interaction in wearable robotics.

Journal of the mechanical behavior of biomedical materials·2026

Same author

Torque-sensorless control of a high-ratio, backdrivable Wolfrom-gearbox for safe human-centered robotics.

Frontiers in robotics and AI·2026

Same author

Human-inspired sensorimotor controller for dynamic motion adaptation: a study in robotic arms.

Frontiers in neurorobotics·2026

Same author

Cyberlegs X-Leg at CYBATHLON 2024: insights on the control development of an active transfemoral prosthesis.

Journal of neuroengineering and rehabilitation·2026

Same author

Markerless 3D ultrasound reconstruction for augmented reality assisted minimally invasive spine surgery.

International journal of computer assisted radiology and surgery·2026

Same author

Markerless Augmented Reality Guidance System for Maxillofacial Surgery: An Omnidirectional Tracking Method.

Health science reports·2026

Same journal

DSPE-ViT: a lightweight vision transformer with dynamic sparse positional encoding for dense small object detection in UAV imagery.

Frontiers in neurorobotics·2026

Same journal

ST-HONet: Spatio-Temporal Hierarchical Network for long-horizon bimanual visuomotor imitation.

Frontiers in neurorobotics·2026

Same journal

ST-HADP: Spatio-Temporal hierarchical attention diffusion policy for long-horizon generalizable bimanual visuomotor imitation.

Frontiers in neurorobotics·2026

Same journal

EQISP: efficient quantized image signal processing with multi-scale pyramid fusion for resource constrained embodied perception.

Frontiers in neurorobotics·2026

Same journal

Research on embodied agent multimodal perception and real-time path planning algorithms for complex unstructured environments.

Frontiers in neurorobotics·2026

Same journal

NL-YOLOv5: a model with a larger receptive field and the ability to globally acquire features.

Frontiers in neurorobotics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Oct 13, 2025

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

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

Published on: November 6, 2015

Improved Motion Classification With an Integrated Multimodal Exoskeleton Interface.

Kevin Langlois^1,2, Joost Geeroms^1,3, Gabriel Van De Velde¹

¹Robotics & Multibody Mechanics Research Group, MECH Department, Vrije Universiteit Brussel, Brussel, Belgium.

Frontiers in Neurorobotics

|November 11, 2021

Summary

This summary is machine-generated.

This study introduces a new wearable sensor system for exoskeletons that combines surface electromyography (sEMG) and pressure sensing. This novel interface improves human motion intention detection for better exoskeleton control, even without precise electrode placement.

Keywords:

classification electromyogram exoskeletons human-machine interface intention recognition machine learning wearable sensor

More Related Videos

Author Spotlight: Enhancing Post-Stroke Upper Limb Rehabilitation with Robotic Technologies for Improved Motor Recovery and Functional Outcomes

Author Spotlight: Enhancing Post-Stroke Upper Limb Rehabilitation with Robotic Technologies for Improved Motor Recovery and Functional Outcomes

Published on: September 6, 2024

Author Spotlight: Enhancing Remote Rehabilitation with Virtual Reality and Electromyography

Author Spotlight: Enhancing Remote Rehabilitation with Virtual Reality and Electromyography

Published on: January 12, 2024

Related Experiment Videos

Last Updated: Oct 13, 2025

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

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

Published on: November 6, 2015

Author Spotlight: Enhancing Post-Stroke Upper Limb Rehabilitation with Robotic Technologies for Improved Motor Recovery and Functional Outcomes

Author Spotlight: Enhancing Post-Stroke Upper Limb Rehabilitation with Robotic Technologies for Improved Motor Recovery and Functional Outcomes

Published on: September 6, 2024

Author Spotlight: Enhancing Remote Rehabilitation with Virtual Reality and Electromyography

Author Spotlight: Enhancing Remote Rehabilitation with Virtual Reality and Electromyography

Published on: January 12, 2024

Area of Science:

Robotics
Biomedical Engineering
Human-Computer Interaction

Background:

Surface electromyography (sEMG) is crucial for controlling upper-body exoskeletons.
Current sEMG systems require precise electrode placement, limiting practical application and ease of use.

Purpose of the Study:

To develop a novel physical interface for exoskeletons integrating sEMG and pressure sensors.
To enable robust human motion intention detection for industrial worker tasks.

Main Methods:

3D-printed flexible, conductive sensors for multi-modal data acquisition.
K-Nearest Neighbours classifier for detecting reaching and lifting movements.
Offline validation comparing the novel system against a unimodal sEMG approach.

Main Results:

Excellent prediction performance achieved for human motion intention detection.
The system demonstrates effectiveness with minimal sEMG electrodes.
Robust performance demonstrated without the need for specific electrode placement.

Conclusions:

The proposed integrated sEMG and pressure sensor interface offers a practical solution for exoskeleton control.
This approach enhances usability and broadens the applicability of exoskeleton technology.
Accurate motion intention detection is achievable with a simplified sensor setup.