Scholarlink

Thanks to artificial intelligence (AI), machines will eventually have the same emotional impact as humans. Deep emotions, not just words, are used by this “affective computing” to engage with humans. Bypassing societal masks, sensors like the EEG and GSR are able to sense our genuine feelings. However, creating robots that are actually sensitive to our emotions is challenging. To build genuinely emotionally intelligent machines, we need to improve the methods we use to choose, arrange, and evaluate these signals. This paper propose a method for assessing mental stress in the workplace in real-time using deep learning algorithms in conjunction with wearing EEG and GSR. The major goal is to make computers smarter emotionally so that they can change the way people interact with computers (HCI). Our proposed system can discreetly track a worker’s emotional and psychological well-being as they go about their daily tasks. By combining electroencephalogram (EEG) and pulse signal analysis, our system is able to record not only the mental but also the physiological reactions to mental stress.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Mental Stress Assessment in Working Environment for an Individual Using Wearable Sensor of EEG and Pulse Signal Measured with Help of Deep Learning Algorithm

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • M. V. Karthikeyan,
  • S. Bhuvaneshwar,
  • V. Nishanth

摘要

Thanks to artificial intelligence (AI), machines will eventually have the same emotional impact as humans. Deep emotions, not just words, are used by this “affective computing” to engage with humans. Bypassing societal masks, sensors like the EEG and GSR are able to sense our genuine feelings. However, creating robots that are actually sensitive to our emotions is challenging. To build genuinely emotionally intelligent machines, we need to improve the methods we use to choose, arrange, and evaluate these signals. This paper propose a method for assessing mental stress in the workplace in real-time using deep learning algorithms in conjunction with wearing EEG and GSR. The major goal is to make computers smarter emotionally so that they can change the way people interact with computers (HCI). Our proposed system can discreetly track a worker’s emotional and psychological well-being as they go about their daily tasks. By combining electroencephalogram (EEG) and pulse signal analysis, our system is able to record not only the mental but also the physiological reactions to mental stress.