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

You might also read

Related Articles

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

Sort by
Same author

Neural decoding from surface high-density EMG signals: influence of anatomy and synchronization on the number of identified motor units.

Journal of neural engineering·2022
Same author

Mathematical relationships between spinal motoneuron properties.

eLife·2022
Same author

Standard intensities of transcranial alternating current stimulation over the motor cortex do not entrain corticospinal inputs to motor neurons.

The Journal of physiology·2022
Same author

Correlation networks of spinal motor neurons that innervate lower limb muscles during a multi-joint isometric task.

The Journal of physiology·2022
Same author

Reducing the Calibration Time in Somatosensory BCI by Using Tactile ERD.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2022
Same author

The control and training of single motor units in isometric tasks are constrained by a common input signal.

eLife·2022

Related Experiment Video

Updated: Apr 10, 2026

The Bionic Clicker Mark I & II
08:23

The Bionic Clicker Mark I & II

Published on: August 14, 2017

16.9K

Human-Machine Interface for the Control of Multi-Function Systems Based on Electrocutaneous Menu: Application to

Jose Gonzalez-Vargas1, Strahinja Dosen2, Sebastian Amsuess2

  • 1Center for Frontier Medical Engineering, Chiba University, Chiba, Japan.

Plos One
|June 13, 2015
PubMed
Summary

This study introduces a new bidirectional human-machine interface (HMI) using electro-tactile feedback for controlling complex assistive devices. This novel HMI offers comparable or improved performance over traditional myoelectric control for prosthetic hands.

More Related Videos

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
09:41

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

2.4K
Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
05:21

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

Published on: January 7, 2019

8.5K

Related Experiment Videos

Last Updated: Apr 10, 2026

The Bionic Clicker Mark I & II
08:23

The Bionic Clicker Mark I & II

Published on: August 14, 2017

16.9K
Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
09:41

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

2.4K
Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
05:21

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

Published on: January 7, 2019

8.5K

Area of Science:

  • Biomedical Engineering
  • Human-Computer Interaction
  • Rehabilitation Engineering

Background:

  • Conventional human-machine interfaces (HMIs) struggle with the complexity of modern assistive devices.
  • User control is challenging due to intricate device functions and potential user impairments.
  • Existing HMIs require complex command patterns, limiting usability.

Purpose of the Study:

  • To propose a novel, general-purpose HMI concept for intuitive control of complex assistive systems.
  • To simplify user interaction by using bidirectional communication and electro-tactile feedback.
  • To demonstrate the HMI's effectiveness in controlling a prosthetic hand without myoelectric channels.

Main Methods:

  • Developed a bidirectional HMI system utilizing electro-tactile stimulation for presenting choices.
  • Implemented a single-command signal acknowledgment by the user.
  • Tested the HMI concept on a commercial prosthetic hand with healthy subjects and an amputee.

Main Results:

  • The novel HMI demonstrated performance comparable or superior to traditional myoelectric interfaces in specific outcome measures.
  • The system successfully controlled all functions of a prosthetic hand without myoelectric input.
  • Feasibility was validated through experiments with diverse user groups.

Conclusions:

  • The proposed HMI offers a simplified and effective control strategy for complex assistive devices.
  • This approach enhances user communication and reduces decoding complexity.
  • The general-purpose HMI has broad applicability for prosthetics, wheelchairs, and integration with other control schemes like brain-machine interfaces.