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

A Roadmap to Navigate the Future of Neural Engineering.

Journal of neural engineering·2026
Same author

Electrospun Surface-Modified Epidermal Strain Sensors Enable Silent Speech and Hand Gesture Recognition for Virtual Reality Interaction.

Nanomaterials (Basel, Switzerland)·2026
Same author

Detecting isolated REM sleep behavior disorder at home using a lower-back wearable sensor.

NPJ digital medicine·2026
Same author

Automated Facial Expression Analysis: A New Framework for Comparing Facial Muscle Activity Across Individuals.

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

Towards Objective Cognitive Load Quantification with Multi-modal and Soft Facial Electrophysiology.

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

Sleep Spindle Detection with Soft Dry Electrodes: Toward Clinical and Home-Based Monitoring in Parkinson's Disease.

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 Video Protocol of a Randomized Controlled Clinical Trial - Electrochemotherapy of Cutaneous Metastases with Reduced Dose Bleomycin (BLESS Trial).

Journal of visualized experiments : JoVE·2026
Same journal

A Standardized Ex Vivo Porcine Oromucosal Model for Evaluating Peptide Fluxes.

Journal of visualized experiments : JoVE·2026
Same journal

Lightweight English Text Classification with Deep Learning Based on Complex System Theory.

Journal of visualized experiments : JoVE·2026
Same journal

Integrating Artificial Intelligence-Assisted Translation Support into English Courses: Effects on Translation Accuracy, Perceived Stress, and Anxiety.

Journal of visualized experiments : JoVE·2026
Same journal

A Toxin-Based Counter-Selection System for Markerless Gene Deletion and High-Density Tn5 Transposon Mutagenesis in Pectobacterium brasiliense.

Journal of visualized experiments : JoVE·2026
Same journal

Seamless Multimodal Human-Robot Communication: Integration Techniques in Human-Computer Interaction.

Journal of visualized experiments : JoVE·2026
See all related articles

Related Experiment Video

Updated: May 13, 2025

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
08:15

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Published on: March 28, 2025

300

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision.

Nitzan Luxembourg1, Dvir Ben-Dov1, Rufael Fekadu Marew2

  • 1School of Electrical Engineering, Tel Aviv University.

Journal of Visualized Experiments : Jove
|April 14, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a novel wearable system combining surface electromyography (sEMG) and finger tracking for dynamic gesture recognition. This approach enhances human-computer interaction for prosthetics and rehabilitation by capturing real-world hand movements.

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

1.4K
An Emerging Target Paradigm to Evoke Fast Visuomotor Responses on Human Upper Limb Muscles
09:27

An Emerging Target Paradigm to Evoke Fast Visuomotor Responses on Human Upper Limb Muscles

Published on: August 25, 2020

4.2K

Related Experiment Videos

Last Updated: May 13, 2025

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
08:15

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Published on: March 28, 2025

300
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

1.4K
An Emerging Target Paradigm to Evoke Fast Visuomotor Responses on Human Upper Limb Muscles
09:27

An Emerging Target Paradigm to Evoke Fast Visuomotor Responses on Human Upper Limb Muscles

Published on: August 25, 2020

4.2K

Area of Science:

  • Biomedical Engineering
  • Human-Computer Interaction
  • Rehabilitation Technology

Background:

  • Finger gestures are crucial for communication and human-computer interfaces.
  • Surface electromyography (sEMG) combined with deep learning shows promise for gesture recognition.
  • Current sEMG methods are limited by static hand positions and complex setups.

Purpose of the Study:

  • To present an advanced protocol for capturing comprehensive data during dynamic hand movements.
  • To integrate wearable surface EMG and finger tracking for robust gesture recognition.
  • To guide researchers in developing intuitive gesture recognition systems.

Main Methods:

  • Utilized soft printed electrode arrays (16 electrodes) on the forearm to record sEMG.
  • Employed a wearable finger tracking system to capture dynamic hand movements.
  • Synchronized sEMG recordings with finger position data during prompted gestures.

Main Results:

  • Successfully captured comprehensive data during dynamic hand movements.
  • Enabled detailed analysis of muscle activity patterns corresponding to specific gestures.
  • Demonstrated the potential of combined EMG and visual tracking for gesture recognition.

Conclusions:

  • The integration of sEMG and finger tracking offers a powerful approach for dynamic gesture recognition.
  • This protocol facilitates the development of responsive systems for prosthetics, rehabilitation, and interactive technologies.
  • The findings support innovation in real-world gesture recognition applications.