Search research articles

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

Thermal enhancement of ternary hybrid Casson nanofluid in porous media: a sensitivity analysis study.

Scientific reports·2026

Same author

Optimization of Pesticides Spray on Crops in Agriculture using Machine Learning.

Computational intelligence and neuroscience·2022

Same author

A Machine Learning and Deep Learning Approach for Recognizing Handwritten Digits.

Computational intelligence and neuroscience·2022

Same author

Tree-Based and Machine Learning Algorithm Analysis for Breast Cancer Classification.

Computational intelligence and neuroscience·2022

Same author

Yoga Pose Estimation and Feedback Generation Using Deep Learning.

Computational intelligence and neuroscience·2022

Same author

Genetic Programming-Based Feature Selection for Emotion Classification Using EEG Signal.

Journal of healthcare engineering·2022

Same journal

RETRACTION: Framework to Segment and Evaluate Multiple Sclerosis Lesion in MRI Slices Using VGG-UNet.

Computational intelligence and neuroscience·2026

Same journal

RETRACTION: Facial Emotion Recognition Using a Novel Fusion of Convolutional Neural Network and Local Binary Pattern in Crime Investigation.

Computational intelligence and neuroscience·2026

Same journal

RETRACTION: Automatic Intelligent System Using Medical of Things for Multiple Sclerosis Detection.

Computational intelligence and neuroscience·2026

Same journal

RETRACTION: Intangible Cultural Heritage Reproduction and Revitalization: Value Feedback, Practice, and Exploration Based on the IPA Model.

Computational intelligence and neuroscience·2026

Same journal

RETRACTION: CNN Based Multiclass Brain Tumor Detection Using Medical Imaging.

Computational intelligence and neuroscience·2025

Same journal

RETRACTION: Distributed Scheduling Strategy of Virtual Power Plant Using the Particle Swarm Optimization Neural Network under Blockchain Background.

Computational intelligence and neuroscience·2025

See all related articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: Sep 8, 2025

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

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

Published on: November 24, 2015

Personality Prediction with Hybrid Genetic Programming using Portable EEG Device.

Harshit Bhardwaj¹, Pradeep Tomar¹, Aditi Sakalle¹

¹Department of CSE, USICT, Gautam Buddha University, Greater Noida, India.

Computational Intelligence and Neuroscience

|June 13, 2022

Summary

This summary is machine-generated.

This study uses electroencephalogram (EEG) to identify personality traits from film clips. Hybrid genetic programming achieved 82.25% accuracy in classifying Myers-Briggs Type Indicator (MBTI) traits from brainwave data.

More Related Videos

Event Related Potentials ERPs and other EEG Based Methods for Extracting Biomarkers of Brain Dysfunction: Examples from Pediatric Attention Deficit/Hyperactivity Disorder ADHD

Event Related Potentials ERPs and other EEG Based Methods for Extracting Biomarkers of Brain Dysfunction: Examples from Pediatric Attention Deficit/Hyperactivity Disorder ADHD

Published on: March 12, 2020

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

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

Published on: July 26, 2013

Related Experiment Videos

Last Updated: Sep 8, 2025

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

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

Published on: November 24, 2015

Event Related Potentials ERPs and other EEG Based Methods for Extracting Biomarkers of Brain Dysfunction: Examples from Pediatric Attention Deficit/Hyperactivity Disorder ADHD

Event Related Potentials ERPs and other EEG Based Methods for Extracting Biomarkers of Brain Dysfunction: Examples from Pediatric Attention Deficit/Hyperactivity Disorder ADHD

Published on: March 12, 2020

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

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

Published on: July 26, 2013

Area of Science:

Neuroscience
Psychology
Machine Learning

Background:

Personality traits influence emotional responses to stimuli.
Electroencephalogram (EEG) captures brain activity related to emotional states.
The Myers-Briggs Type Indicator (MBTI) is a widely used personality assessment tool.

Purpose of the Study:

To develop a real-time method for identifying personality traits using EEG signals.
To correlate specific brainwave patterns with MBTI personality types.
To explore the application of machine learning in personality assessment.

Main Methods:

Utilized a single-channel NeuroSky MindWave 2 for EEG data acquisition.
Employed Fast Fourier Transform (FFT) for feature extraction from EEG signals.
Applied Hybrid Genetic Programming (HGP) for classifying EEG data against MBTI traits.

Main Results:

Developed four two-class HGP classifiers for different MBTI trait groups.
Achieved an overall classification accuracy of 82.25% using 10-fold cross-validation.
Demonstrated the feasibility of real-time personality trait identification from EEG.

Conclusions:

EEG data, analyzed with FFT and HGP, can effectively predict personality traits.
This approach offers a novel, objective method for personality assessment.
Future research can refine the model for broader applications in psychology and human-computer interaction.