Resources

Introduction:

Personality trait recognition is an important psychological paradigm to understand the differences in the people behavior. This study presents a new dataset, which we dubbed as PROPER (Personality Recognition based On Public Speaking task using Electroencephalography (EEG) Recordings). To the best of our knowledge, this is the first database which connects the personality traits of an individual and public speaking activity via EEG signals. EEG data of 40 healthy individuals is recorded before, during, and after public speaking activity using MUSE headband. Score from big five personality trait questionnaire is used to label the participants EEG data. The dataset developed in this study aims at creating a starting point for new researches in the field of personality recognition.

Equipment:

EEG Data Acquisition:

EEG data acquisition was performed by using a Muse headband, which is a lightweight, adjustable, and easy to wear device. The headband consists of 4 dry electrodes positioned according to 10-20 electrode positioning system at TP9, AF7, AF8 and T P10 locations. A reference electrode Fpz is located on the forehead. The data acquisition was performed using an android mobile application (Muse Monitor) via a Bluetooth connection at a sampling rate of 256 Hz.

Experimental Procedure:

The subject was escorted to a noise free and temperature-controlled room. The complete experimental procedure was explained, and written consent was obtained. The demographic details of the subject were also recorded. A subjective personality assessment questionnaire (Big Five personality test questionnaire) was filled by the participants. The total score of each personality trait ranges from 0 to 40. After filling the big five questionnaire, the Muse headband is placed on user scalp for recording of EEG signals. The user is given a comfortable chair to be seated and pre-stimulus phase EEG recording is performed in open eye condition for three minutes. Next the user is given a time duration of 5 minutes as a public speaking task preparation time for preparing a presentation on an unknown topic, which the subject is asked to present in front of a real audience. The EEG data is recorded during the public speaking activity. Moreover, EEG data is again recorded in post-stimulus phase sitting in a relaxed position in open eye condition for a duration of three minutes.

Dataset Contents:

The dataset contains .csv files of the raw EEG signals collected from the 40 participants acquired in pre-public speaking activity phase, during a five minutes public speaking activity phase, and post-public speaking activity phase.

To download the dataset, please download the pdf release agreement from, fill-in and scan it, then attach it in the form here

Download

• • A new dataset of EEG, GSR, and PPG signals are recorded for emotion analysis and recognition task. 

  • The dataset is made publicly available and we encourage other researchers to use it for testing purpose. The dataset was first used in the paper submitted in Information Fusion Journal titled "DEAR-MULSEMEDIA: Dataset for Emotion Analysis and Recognition in response to Multiple Sensorial Media".    

  • In case of any query related to dataset contact asim.raheel@uettaxila.edu.pk

Download

• • A new dataset of EEG signals recorded in pre-activity, during activity and post activity phase for perceived mental stress classification.

  • The dataset is made publicly available and we encourage other researchers to use it for testing purpose. The dataset was first used in the following paper. 

  • Aamir Arsalan, Muhammad Majid, Amna Rauf Butt, Syed Muhammad Anwar, “Classification of Perceived Mental Stress Using A Commercially Available EEG Headband”, IEEE Journal of Biomedical and Health Informatics, Vol. 23, No. 6 pp. 2257-2264, 2019.    

  • In case of any query related to dataset contact aamir.arsalan@uettaxila.edu.pk