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@article{163853,
        author = {Swati Arjun Yadgire and Prof. Sachin Manohar Dandage},
        title = {A review on detection of stress from facial parameters using Machine Learning Techniques},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {11},
        pages = {510-515},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=163853},
        abstract = {Mental stress is a psychological condition that affects all aspects of life, including sleep. Individuals experience daily mental strain as a result of various factors, including social situations. The sources of stress can include financial constraints, familial and social worries, unfavourable environmental conditions such as inclement weather, heavy traffic, or excessive noise, as well as challenging situations like delivering a presentation to a large audience or organizing a wedding. An optimal level of stress is beneficial for an individual's well-being and can serve as a motivator. However, an excessive amount of stress or an intense response to stress might pose potential risks to one's health. Consequently, the identification and anticipation of mental stress has gained significant attention in the community. This research examines and evaluates different techniques for detecting stress using machine learning technologies.},
        keywords = {Mental stress, Hazardous, Machine learning, Stress detection, Anticipating mental stress},
        month = {},
        }