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

RAP<sup>2</sup>G: Relation-Aware Progressive Pseudo-label Generation for Cross-subject MI-EEG Recognition.

IEEE transactions on bio-medical engineering·2026
Same author

Mitophagy deficiency and calcium dyshomeostasis underlying the pathogenesis and progression of Alzheimer's disease.

Journal of Alzheimer's disease : JAD·2026
Same author

Dissipation behavior and risk assessment of four pesticides in shiitake mushrooms from cultivation to processing.

NPJ science of food·2026
Same author

MELF: A multi-view ensemble learning framework for normative resting state EEG signal quality assessment.

Biomedical physics & engineering express·2026
Same author

Ventilation-assisted functional visualization: a stepwise workflow for planned management of a preoperatively identified tracheal diverticulum during thyroidectomy.

Gland surgery·2026
Same author

[Formula: see text]AC-Dep: dynamic adaptive feature fusion and domain adaptation collaboration for cross-subject depression detection.

Cognitive neurodynamics·2026

Related Experiment Video

Updated: Dec 20, 2025

Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome
08:31

Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome

Published on: July 31, 2016

14.3K

An improved common spatial pattern combined with channel-selection strategy for electroencephalography-based emotion

Mengmeng Yan1, Zhao Lv2, Wenhui Sun3

  • 1School of Computer Science and Technology, Anhui University, Hefei 230601, China; Shan'xi Key Laboratory of Network and System Security, Xidian University, Xi'an 710071, China.

Medical Engineering & Physics
|June 2, 2020
PubMed
Summary

This study introduces an improved common spatial pattern with channel selection (ICSPCS) for recognizing emotions using electroencephalography (EEG). The method achieves high accuracy, enhancing emotional human-computer interaction (HCI).

Keywords:
Channel selectionCommon spatial pattern (CSP)Emotion recognitionJoint approximation diagonalization (JAD)

More Related Videos

Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
11:25

Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

Published on: July 26, 2013

43.9K
Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

1.9K

Related Experiment Videos

Last Updated: Dec 20, 2025

Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome
08:31

Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome

Published on: July 31, 2016

14.3K
Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
11:25

Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

Published on: July 26, 2013

43.9K
Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

1.9K

Area of Science:

  • Artificial Intelligence
  • Cognitive Science
  • Human-Computer Interaction (HCI)

Background:

  • Emotional HCI requires accurate emotion perception.
  • Electroencephalography (EEG) is crucial for analyzing emotions in HCI.
  • Existing methods for EEG-based emotion recognition have limitations.

Purpose of the Study:

  • To propose an improved common spatial pattern combined with a channel-selection strategy (ICSPCS) for enhanced EEG-based emotion recognition.
  • To address limitations in traditional methods for multi-class emotion representation.
  • To improve the efficiency and reduce the computational load of EEG-based emotion recognition systems.

Main Methods:

  • Utilized a common spatial pattern (CSP) algorithm to design spatial filters for three emotions (positive, neutral, negative).
  • Developed novel eigenvalue selection methods to overcome limitations of the traditional joint approximation diagonalization.
  • Implemented a channel-selection strategy based on channel weight values to reduce computational complexity.

Main Results:

  • Achieved average recognition accuracies of 85.85% on a self-collected dataset.
  • Attained average recognition accuracies of 94.13% on the MAHNOB-HCI dataset.
  • Demonstrated the effectiveness of the ICSPCS method in EEG-based emotion recognition.

Conclusions:

  • The proposed ICSPCS method significantly enhances EEG-based emotion recognition.
  • The channel-selection strategy simplifies installation and reduces computational load.
  • The findings contribute to advancing emotional HCI through improved EEG analysis.