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  • Open Access

    ARTICLE

    Emotion Detection Using ECG Signals and a Lightweight CNN Model

    Amita U. Dessai*, Hassanali G. Virani

    Computer Systems Science and Engineering, Vol.48, No.5, pp. 1193-1211, 2024, DOI:10.32604/csse.2024.052710 - 13 September 2024

    Abstract Emotion recognition is a growing field that has numerous applications in smart healthcare systems and Human-Computer Interaction (HCI). However, physical methods of emotion recognition such as facial expressions, voice, and text data, do not always indicate true emotions, as users can falsify them. Among the physiological methods of emotion detection, Electrocardiogram (ECG) is a reliable and efficient way of detecting emotions. ECG-enabled smart bands have proven effective in collecting emotional data in uncontrolled environments. Researchers use deep machine learning techniques for emotion recognition using ECG signals, but there is a need to develop efficient models… More >

  • Open Access

    ARTICLE

    Suicide Ideation Detection of Covid Patients Using Machine Learning Algorithm

    R. Punithavathi1,*, S. Thenmozhi2, R. Jothilakshmi3, V. Ellappan4, Islam Md Tahzib Ul5

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 247-261, 2023, DOI:10.32604/csse.2023.025972 - 16 August 2022

    Abstract During Covid pandemic, many individuals are suffering from suicidal ideation in the world. Social distancing and quarantining, affects the patient emotionally. Affective computing is the study of recognizing human feelings and emotions. This technology can be used effectively during pandemic for facial expression recognition which automatically extracts the features from the human face. Monitoring system plays a very important role to detect the patient condition and to recognize the patterns of expression from the safest distance. In this paper, a new method is proposed for emotion recognition and suicide ideation detection in COVID patients. This More >

  • Open Access

    ARTICLE

    BERT-CNN: A Deep Learning Model for Detecting Emotions from Text

    Ahmed R. Abas1, Ibrahim Elhenawy1, Mahinda Zidan2,*, Mahmoud Othman2

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2943-2961, 2022, DOI:10.32604/cmc.2022.021671 - 07 December 2021

    Abstract Due to the widespread usage of social media in our recent daily lifestyles, sentiment analysis becomes an important field in pattern recognition and Natural Language Processing (NLP). In this field, users’ feedback data on a specific issue are evaluated and analyzed. Detecting emotions within the text is therefore considered one of the important challenges of the current NLP research. Emotions have been widely studied in psychology and behavioral science as they are an integral part of the human nature. Emotions describe a state of mind of distinct behaviors, feelings, thoughts and experiences. The main objective… More >

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