Department of Computer Science and Information Systems
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Item An analysis of the psychological implications of covid-19 pandemic on undergraduate students and efforts on mitigation(Springer, 2022-02) Rao, Shreyas SureshThe whole world is combating the COVID-19 pandemic, which has affected mankind in enormous ways. To limit its pervasive expansion, many measures were taken up by the Indian government, as a result of which colleges were closed, and education was imparted through the online mode. The pandemic has induced psychological strain in the minds of students. The present study analyses the psychological impact of the COVID-19 pandemic on engineering undergraduates in south India, who are in the age group of 19 to 22. A survey from 365 students was analyzed during the second wave of COVID-19. Data revealed that although there is an overall increased awareness about the outbreak, there is a considerable inclination towards depression, anxiety, and stress in students. Amongst the participants, 116 (31.78%) screened positive for depression, 79 (21.64%) for anxiety, and 53 (14.52%) for stress. Besides, 46 (12.60%) participants had comorbid conditions, with moderate, severe, or extremely severe levels of stress, anxiety, and depression. The Center of Excellence in AI&ML at the study center implemented a multilingual chatbot to provide mental health support during the pandemic and deployed the bot in Facebook and Web modes.Item Introducing ISAP and MATSS: mental stress induced speech utterance procedure and obtained dataset(Elsevier, 2022-11) Phartiyal, Gopal SinghMental stress persisting for long can cause severe health issues. There are various approaches available in the literature for investigating stress through speech utterances. The available procedure to obtain speech under stress dataset requires the speakers to undergo the actual stress situations in a real environment with limited control or inducing stress with a mental task in a lab environment. These approaches either suffer from ethical issues or unreliable labeling of the obtained speech samples. In this paper, we attempt to overcome these limitations with Induced mental Stress based speech production And labeling Procedure (ISAP), for obtaining speech utterances under mental stress along with labeling the samples simultaneously. The proposed ISAP can be incorporated by future studies as per their need to create a speech under stress dataset. We also present the obtained dataset, the baseline experiments, and classification results with various machine learning models. A total of 1260 speech utterances are obtained, with ISAP able to induce stress in 54.4% of the cases. The accuracy of the SVM classifier in recognizing three stress classes, namely, No Stress, Low Stress, and High Stress is found to be 57.1%.Item A study on psychological implications of COVID-19 on nursing professionals(Taylor & Francis, 2021) Rao, Shreyas SureshThe World Health Organization declared COVID-19 as a pandemic on 11 March, 2020, followed by an unprecedented global increase of the disease in recent times. Healthcare workers, including Nursing Professionals (NP), are more likely to experience psychological distress during the pandemic. The purpose of the study is to examine the stress, depression, and anxiety experienced by the nursing professionals in India, who provide care to COVID positive patients.