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

Small-Molecule Targeted and Activatable Photoacoustic Probes for In Vivo Imaging: Design Principles and Recent Advances.

Chemistry (Weinheim an der Bergstrasse, Germany)·2026
Same author

Low-Effort Respiratory Function Estimation with a Soft Wearable Digital Spirometry Patch.

Biosensors·2026
Same author

At-Home Sleep Electroencephalography Assessment in Young and Older Adults Using a Novel Wireless Soft Electronics Sleep Monitoring System: Experimental Study.

JMIR formative research·2026
Same author

Wrinkle-Adaptive Kirigami Wearables With Anisotropic Deformability for Sleep EEG Monitoring.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Predicting Stereotactic Body Radiation Therapy Response Using an AI-Based Tumor Vessel Biomarker.

Technology in cancer research & treatment·2026
Same author

Robust Multimodal Deep Learning for Lymphoma Subtype Classification Using <sup>18</sup>F-FDG PET Maximum Intensity Projection Images and Clinical Data: A Multi-Center Study.

Cancers·2026
Same journal

Analytical Solution for the Potential Distribution in the Channel of A Graphene Field-Effect Transistor Validated with a Custom-Fabricated Test Platform.

ACS applied electronic materials·2026
Same journal

Atomic Layer Etching of Nickel Using N<sub>2</sub>/H<sub>2</sub> Plasma Exposure and Hexafluoroacetylacetone.

ACS applied electronic materials·2026
Same journal

Characterization of Electronic Stress-Induced Changes in Multilayer MoS<sub>2</sub>.

ACS applied electronic materials·2026
Same journal

Enhanced Zero-Bias Rectification in 1D Metal-Double-Insulator-Graphene Diodes for RF Energy Harvesting.

ACS applied electronic materials·2026
Same journal

Zero-Bias Photodetection and Opto-Synaptic Plasticity in BP/MoS<sub>2</sub> and WS<sub>2</sub>/PdSe<sub>2</sub> van der Waals Heterostructures.

ACS applied electronic materials·2026
Same journal

Enhanced Piezoelectric Effect in P(VDF-TrFE) through Synergistic Templating by PEDOT:PSS and Paper.

ACS applied electronic materials·2026
See all related articles

Related Experiment Video

Updated: Aug 8, 2025

A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare
06:34

A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare

Published on: July 7, 2023

2.5K

Soft Wireless Headband Bioelectronics and Electrooculography for Persistent Human-Machine Interfaces.

Seunghyeb Ban1,2, Yoon Jae Lee2,3, Shinjae Kwon2,4

  • 1School of Engineering and Computer Science, Washington State University, Vancouver, Washington 98686, United States.

ACS Applied Electronic Materials
|March 6, 2023
PubMed
Summary
This summary is machine-generated.

This study presents a new soft wearable system with dry electrodes for electrooculography (EOG) to enable eye movement-controlled human-machine interfaces (HMIs). The system achieved 98.3% accuracy in classifying eye motions, demonstrating its potential for advanced applications.

More Related Videos

Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients
06:11

Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients

Published on: April 18, 2025

665
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

10.5K

Related Experiment Videos

Last Updated: Aug 8, 2025

A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare
06:34

A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare

Published on: July 7, 2023

2.5K
Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients
06:11

Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients

Published on: April 18, 2025

665
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

10.5K

Area of Science:

  • Biomedical Engineering
  • Wearable Technology
  • Human-Machine Interfaces

Background:

  • Conventional gel electrodes for electrooculography (EOG) cause skin irritation and motion artifacts.
  • Existing wearable systems for EOG often involve bulky electronics, limiting persistent use.
  • There is a need for comfortable, low-profile, and reliable EOG-based human-machine interfaces (HMIs).

Purpose of the Study:

  • To develop a soft, wearable electronic system with dry electrodes for continuous EOG signal detection.
  • To demonstrate the efficacy of this system for real-time eye movement classification.
  • To evaluate the system's potential for controlling external devices and applications.

Main Methods:

  • A low-profile, headband-type soft wearable system with embedded stretchable dry electrodes was designed.
  • Nanomembrane electrodes were fabricated using thin-film deposition and laser cutting on a flexible thermoplastic polyurethane base.
  • A flexible wireless circuit was integrated for EOG signal acquisition and processing.
  • Convolutional neural networks (CNNs) were employed for machine learning-based classification of EOG signals.

Main Results:

  • The developed system successfully detected EOG signals in real-time using dry electrodes.
  • Accurate classification of six eye motion classes (blink, up, down, left, right) was achieved.
  • A convolutional neural network model demonstrated 98.3% accuracy, outperforming other machine learning methods.
  • Continuous wireless control of a two-wheeled radio-controlled car was demonstrated in real-time.

Conclusions:

  • The proposed soft wearable electronic system with dry electrodes offers a promising solution for persistent, non-invasive HMIs.
  • The high accuracy achieved in EOG classification highlights the potential of this technology for various applications, including virtual reality.
  • This bioelectronic system and algorithm pave the way for advanced eye-controlled interfaces.