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 Experiment Video

Updated: May 3, 2026

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
06:09

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation

Published on: September 8, 2023

1.2K

A P300-based brain computer interface system for words typing.

Faraz Akram1, Hee-Sok Han1, Tae-Seong Kim1

  • 1Department of Biomedical Engineering, Kyung Hee University, Republic of Korea.

Computers in Biology and Medicine
|February 1, 2014
PubMed
Summary
This summary is machine-generated.

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

Nonlinear EEG Complexity as a Marker of Maladaptive Brain Plasticity in Substance Use Disorders: A Multi-Group Machine Learning Classification Study.

Brain sciences·2026
Same author

Hyperparameter Optimization of Convolutional Neural Networks for Robust Tumor Image Classification.

Diagnostics (Basel, Switzerland)·2026
Same author

Bimanual Long-Horizon Lifecare Robotics with Temporal Context LLM Planner and Transformer Reinforcement Learning.

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

Counterfactual Multi-Agent Reinforcement Learning for Long- Horizon Medical Assistive Tasks with Dual-arm Robot.

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

Human Activity Prediction Based on Forecasted IMU Activity Signals by Sequence-to-Sequence Deep Neural Networks.

Sensors (Basel, Switzerland)·2023
Same author

Development and validation of a deep learning model to diagnose COVID-19 using time-series heart rate values before the onset of symptoms.

Journal of medical virology·2023

This study introduces a faster Brain Computer Interface (BCI) for typing. The new P300 BCI system integrates word suggestions, significantly reducing the time needed to type words.

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Human-Computer Interaction

Background:

  • P300 event-related potentials are brain responses to unexpected stimuli.
  • P300 Brain Computer Interface (BCI) systems enable communication via brain signals.
  • Conventional P300 spellers are slow, requiring character-by-character input.

Purpose of the Study:

  • To develop an improved P300 BCI word typing system.
  • To reduce the time and effort required for word input using P300 BCI.
  • To integrate dictionary-based word suggestions into a P300 BCI speller.

Main Methods:

  • Developed a novel P300 BCI system incorporating a dictionary and word suggestion feature.
  • Implemented an initial character spelling paradigm followed by a word selection paradigm.
Keywords:
BCIBrain computer interfaceDictionary searchHuman computer interactionP300 spellerWord typing paradigm

More Related Videos

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

11.4K
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

1.9K

Related Experiment Videos

Last Updated: May 3, 2026

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
06:09

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation

Published on: September 8, 2023

1.2K
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

11.4K
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

1.9K
  • Tested the system with ten human subjects.
  • Main Results:

    • The proposed P300 BCI system achieved an average word typing time of 1.91 minutes.
    • This represents a significant reduction compared to the conventional P300 speller's average time of 3.36 minutes.
    • User testing confirmed the system's efficiency and ease of use.

    Conclusions:

    • The integrated word suggestion mechanism substantially improves P300 BCI typing speed.
    • This enhanced P300 BCI system offers a more efficient and user-friendly communication method.
    • The findings suggest a promising advancement for assistive technology and communication for individuals with disabilities.