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Computer Science > Human-Computer Interaction

arXiv:2402.04326 (cs)
[Submitted on 6 Feb 2024]

Title:Personality Trait Recognition using ECG Spectrograms and Deep
Learning

Authors:Muhammad Mohsin Altaf, Saadat Ullah Khan, Muhammad Majd, Syed
Muhammad Anwar
Download a PDF of the paper titled Personality Trait Recognition
using ECG Spectrograms and Deep Learning, by Muhammad Mohsin Altaf
and 3 other authors
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    Abstract:This paper presents an innovative approach to
    recognizing personality traits using deep learning (DL) methods
    applied to electrocardiogram (ECG) signals. Within the framework
    of detecting the big five personality traits model encompassing
    extra-version, neuroticism, agreeableness, conscientiousness, and
    openness, the research explores the potential of ECG-derived
    spectrograms as informative features. Optimal window sizes for
    spectrogram generation are determined, and a convolutional neural
    network (CNN), specifically Resnet-18, and visual transformer
    (ViT) are employed for feature extraction and personality trait
    classification. The study utilizes the publicly available
    ASCERTAIN dataset, which comprises various physiological signals,
    including ECG recordings, collected from 58 participants during
    the presentation of video stimuli categorized by valence and
    arousal levels. The outcomes of this study demonstrate noteworthy
    performance in personality trait classification, consistently
    achieving F1-scores exceeding 0.9 across different window sizes
    and personality traits. These results emphasize the viability of
    ECG signal spectrograms as a valuable modality for personality
    trait recognition, with Resnet-18 exhibiting effectiveness in
    discerning distinct personality traits.

Subjects: Human-Computer Interaction (cs.HC); Machine Learning
          (cs.LG); Signal Processing (eess.SP)
Cite as:  arXiv:2402.04326 [cs.HC]
          (or arXiv:2402.04326v1 [cs.HC] for this version)
          https://doi.org/10.48550/arXiv.2402.04326
          Focus to learn more
          arXiv-issued DOI via DataCite

Submission history

From: Syed Anwar [view email]
[v1] Tue, 6 Feb 2024 19:09:44 UTC (1,182 KB)
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    Altaf and 3 other authors
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