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 color-coded SSVEP-based brain-computer interface.

Journal of neural engineering·2026
Same author

Correction: Meta-analysis of tuberculosis incidence and risk in cancer patients treated with immune checkpoint inhibitors.

Frontiers in oncology·2026
Same author

Paleo-salt water dominates coastal aquifer salinization: A continental-scale study in China.

Science advances·2026
Same author

Macroscopic on-site evaluation based on core tissues length and weight during EBUS-TBNA using 22-gauge needles.

Chinese medical journal·2026
Same author

Inorganic carbon exports from coastal wetlands can offset part of blue carbon systems' CO<sub>2</sub> removal.

Science bulletin·2026
Same author

Structural brain network alterations in schizophrenia and ultra-high risk populations: Linking olfactory dysfunction to clinical symptoms.

Progress in neuro-psychopharmacology & biological psychiatry·2026
Same journal

Autonomous Microrobots for Spatiotemporally Active Therapeutic Delivery and Controlled Release.

Cyborg and bionic systems (Washington, D.C.)·2026
Same journal

Optoelectronic Tweezers for Single-Cell Research: Principles, Applications, and Prospects‌.

Cyborg and bionic systems (Washington, D.C.)·2026
Same journal

Enhancing Shape Sensing of Slender Medical Continuum Robot Using Carbon Nanotube Piezoresistive Fiber Bandage.

Cyborg and bionic systems (Washington, D.C.)·2026
Same journal

Frequency-Specific Transcranial Photobiomodulation Elicits Complementary Glial Mechanisms for Neurovascular Protection and Amyloid Clearance in Alzheimer Disease.

Cyborg and bionic systems (Washington, D.C.)·2026
Same journal

Text Sequence Stimulation for High-Speed and Comfortable SSVEP-BCI.

Cyborg and bionic systems (Washington, D.C.)·2026
Same journal

Micro/Nanorobotic Systems for Imaging-Guided Closed-Loop Thrombus Recanalization.

Cyborg and bionic systems (Washington, D.C.)·2026
See all related articles

Related Experiment Video

Updated: Mar 31, 2026

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

3.4K

A High-Speed Visual BCI Based on Hybrid Frequency-Phase-Space Encoding and High-Density EEG Decoding.

Gege Ming1, Weihua Pei2,3, Sen Tian4

  • 1Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China.

Cyborg and Bionic Systems (Washington, D.C.)
|March 30, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a novel hybrid frequency-phase-space encoding method for brain-computer interfaces (BCIs). The new method significantly boosts information transfer rates (ITRs) using high-density electroencephalogram (EEG) recordings, paving the way for faster visual BCIs.

More Related Videos

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots
11:01

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots

Published on: November 24, 2015

13.9K
Assessment and Communication for People with Disorders of Consciousness
07:37

Assessment and Communication for People with Disorders of Consciousness

Published on: August 1, 2017

9.7K

Related Experiment Videos

Last Updated: Mar 31, 2026

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

3.4K
SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots
11:01

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots

Published on: November 24, 2015

13.9K
Assessment and Communication for People with Disorders of Consciousness
07:37

Assessment and Communication for People with Disorders of Consciousness

Published on: August 1, 2017

9.7K

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Brain-computer interface (BCI) technology enables direct brain-device communication.
  • Current visual BCIs have limited information transfer rates (ITRs) due to underexploited spatial information and low recording resolution.
  • High spatiotemporal resolution is crucial for capturing brain signal dynamics.

Purpose of the Study:

  • To develop high-speed BCI systems by enhancing spatial information utilization.
  • To propose a hybrid frequency-phase-space encoding method integrated with high-density electroencephalogram (EEG) recordings.
  • To investigate the impact of electrode configuration and density on BCI performance.

Main Methods:

  • Recorded EEG data using a 256-channel cap.
  • Compared four parieto-occipital electrode configurations (66/256, 32/128, 21/64, 9/64).
  • Implemented classical frequency-phase encoding and a novel hybrid frequency-phase-space encoding method in BCI paradigms.

Main Results:

  • The hybrid method with higher electrode density configurations (66/256, 32/128, 21/64) significantly increased theoretical ITRs compared to the traditional 9/64 setup (up to 195.56%).
  • An online BCI system achieved a high average actual ITR of (472.72 ± 15.06) bits per minute.
  • Demonstrated that spatiotemporal encoding strategy and electrode density jointly determine achievable ITRs.

Conclusions:

  • The proposed hybrid frequency-phase-space encoding method substantially improves BCI speed and efficiency.
  • High-density EEG recordings and optimized electrode configurations are critical for high-speed visual BCIs.
  • Findings provide quantitative guidelines for designing advanced high-speed visual BCI systems.