Human Stress Monitoring System Using Convolution Neural Network

Authors

  • Prathiksha M  UG Scholar, Department of Computer Science and Engineering, Akshaya College of Engineering and Technology, Coimbatore, Tamil Nadu, India
  • Arunachalam CV  Assistant Professor, Department of Computer Science and Engineering, Akshaya College of Engineering and Technology, Coimbatore, Tamil Nadu, India
  • Gokulakrishnan A  
  • Ponraj V  
  • Lakshmanan V  

Keywords:

Consumer Face Detection, Face Expressions, Stress Monitoring, Neural Network, Convolutional Neural Network.

Abstract

Psychological problems are becoming a major threat to people’s life. Mental stress is a major issue nowadays, especially among youngsters and working people. The age that was considered once most carefree is now under a large amount of stress due to the surroundings. It is important to detect and manage stress before it turns into a severe health issue. Stress increase nowadays leads to many problems like depression, suicide, heart attack, and stroke. In this paper, the stress of the working people is being monitoring in their work environment. Image processing technique is used to monitor the stress of a person. The stress is identified by the face detection mechanism. In this face detection project, a computer system will be able to find and recognize human faces fast and precisely in images or videos that are being captured through a surveillance/web camera. It helps in conversion of the frames of the video into images so that the face of the student can be easily recognized for their face expressions. The dataset is taken from various people and their face expressions. These expressions are stored as values in XML files. These values are used to train the system using Convolution Neural Network algorithm. It predicts the results based on the values in the dataset. The resulting values will be stored in the text document. It will be helpful to their organisation counsellor for further future reference.

References

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International Journal of Scientific Research in Science and Technology

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Published

2021-04-30

Issue

Volume 8, Issue 2, March-April-2021

Section

Research Articles

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Copyright (c) IJSRST

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Prathiksha M, Arunachalam CV, Gokulakrishnan A, Ponraj V, Lakshmanan V "Human Stress Monitoring System Using Convolution Neural Network " International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 8, Issue 2, pp.527-533, March-April-2021.