Stress Detection by monitoring physiological data

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@article{1704035,
      author = {Parshant, Dr. Anu Rathee},
      title = {Stress Detection by monitoring physiological data},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {6},
      number = {7},
      pages = {271-275},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1704035.pdf},
      abstract = {Human health effects of mental stress have been recognized for decades. Early detection of high levels of stress is necessary to stop detrimental effects. In order to prevent stress-related issues, it is crucial to identify them early on. This can only be done through continuous stress monitoring. This study examines the methods for detecting stress that are used in conjunction with sensory devices such as blood oxygen levels, body temperature, and respiration rate.Many researchers and scholars today use the data they gather from the internet to help in detecting stress. In order to resolve the issue of detecting stress, Once more, I am applying a machine learning model to identify that a person is stressed or not. This training model takes a sample data and train itself for detecting stress and give the output of stress level ranging from 0 to 4.},
      keywords = {Stress Prediction, physiological data, Machine Learning},
      month = {January},
  }