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

Temporal point process modeling of aggressive behavior onset in psychiatric inpatient youths with autism.

Scientific reports·2026
Same author

Corticomorphic Hybrid CNN-SNN Architecture for EEG-Based Low-Footprint Low-Latency Auditory Attention Detection.

Annals of biomedical engineering·2026
Same author

Deep Learning-Based Prediction of Cardiopulmonary Disease in Retinal Images of Premature Infants.

JAMA ophthalmology·2026
Same author

In vitro affinity maturation of a single-chain antibody against thyroxine based on computer-aided design.

The FEBS journal·2026
Same author

Longitudinal monitoring of twenty homes reveals spatiotemporal dynamics which require new models of discomfort and thermostat use.

Scientific reports·2026
Same author

Association Between Family Support Combined With Exercise Rehabilitation and Psychological Resilience, Neurological Function and Daily Living Activities in Patients With Stroke and Anxiety.

Actas espanolas de psiquiatria·2025

Related Experiment Video

Updated: Jul 10, 2026

Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking
05:58

Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking

Published on: August 29, 2018

Boosting linear logistic regression for single trial ERP detection in rapid serial visual presentation tasks.

Yonghong Huang1, Deniz Erdogmus, Santosh Mathan

  • 1Comput. Sci. & Electr. Eng. Dept., Oregon Health & Sci. Univ., Portland, OR 97239, USA. huang@csee.ogi.edu

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
|October 20, 2007
PubMed
Summary

This study improved detecting visual recognition signals in electroencephalography (EEG) using AdaBoost with logistic regression. The method enhanced performance by 3% in single-trial evoked response potential detection.

More Related Videos

Simultaneous Eye Tracking and Single-Neuron Recordings in Human Epilepsy Patients
07:43

Simultaneous Eye Tracking and Single-Neuron Recordings in Human Epilepsy Patients

Published on: June 17, 2019

Event-related Potentials During Target-response Tasks to Study Cognitive Processes of Upper Limb Use in Children with Unilateral Cerebral Palsy
08:26

Event-related Potentials During Target-response Tasks to Study Cognitive Processes of Upper Limb Use in Children with Unilateral Cerebral Palsy

Published on: January 11, 2016

Related Experiment Videos

Last Updated: Jul 10, 2026

Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking
05:58

Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking

Published on: August 29, 2018

Simultaneous Eye Tracking and Single-Neuron Recordings in Human Epilepsy Patients
07:43

Simultaneous Eye Tracking and Single-Neuron Recordings in Human Epilepsy Patients

Published on: June 17, 2019

Event-related Potentials During Target-response Tasks to Study Cognitive Processes of Upper Limb Use in Children with Unilateral Cerebral Palsy
08:26

Event-related Potentials During Target-response Tasks to Study Cognitive Processes of Upper Limb Use in Children with Unilateral Cerebral Palsy

Published on: January 11, 2016

Area of Science:

  • Neuroscience
  • Machine Learning
  • Biomedical Engineering

Background:

  • Electroencephalography (EEG) records brain activity.
  • Evoked response potentials (ERPs) are EEG signals linked to specific events.
  • Detecting single-trial ERPs is challenging due to signal variability.

Purpose of the Study:

  • To enhance the detection of visual recognition events using EEG.
  • To apply the AdaBoost algorithm to a linear logistic regression model for single-trial ERP detection.
  • To evaluate the performance improvement offered by the AdaBoost method.

Main Methods:

  • Utilized the AdaBoost algorithm combined with linear logistic regression.
  • Recorded EEG data from 32 electrodes during rapid serial visual presentation (RSVP) of images.
  • Subjects identified target images by clicking a mouse.

Main Results:

  • The AdaBoost-enhanced model improved the detection of visual recognition signatures.
  • Performance enhancement was measured by the area under the ROC curve.
  • The boosting method achieved approximately a 3% improvement over the base classifier.

Conclusions:

  • AdaBoost significantly improves the detection accuracy of single-trial ERPs in visual recognition tasks.
  • This approach offers a more robust method for analyzing EEG data in real-time.
  • The findings have implications for brain-computer interfaces and cognitive neuroscience research.