Stress Detection in Computer Users From Keyboard and Mouse Dynamics

Stress Detection in Computer Users From Keyboard and Mouse Dynamics

₹5,000.00
Product Code: Matlab-Machine Learning
Availability: In Stock
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Product Description

Alternate Title: Dynamic Cat Boost enabled Stress level detection system using keyboard and mouse striking style


Abstract

The impact of digital gadgets is enormous in the current Internet world because of the easy accessibility,   flexibility and time saving benefits for the consumers. The number of computer users is increasing every year. Meanwhile, the time spent and the computers also increased. For various information gathering, computer users browse the internet and stay in the internet for longer time without control. Nowadays working people from home also spend time with the smart devices, computers, laptops, for longer duration to complete professional work, personal work etc. the proposed study focused on deriving the impact factors of Smartphones by analyzing the keystroke dynamics Based on the usage pattern of keystrokes the system evaluates the stress level detection using machine learning techniques. In the proposed study keyboard users are intended for testing purposes. Volunteers of 200 members are collectively involved in generating the test dataset. They are allowed to sit for certain frame of time to use the Laptop in the mean while keystroke of Mouse and keyboard is recorded. The system read the dataset and train the model using Dynamic Cat-Boost algorithm (DCB), that act as the classification  model here. The evaluation metrics are framed by calculating Euclidean distance(ED), Manhattan Distance (MahD), and Mahalanobis distance(MD) etc. Quantitative measures of DCB is framed through Accuracy, precision and F1Score.

Proposed system

In the proposed study keyboard users are intended for testing purposes. Volunteers of 200 members are collectively involved in generating the test dataset. They are allowed to sit for certain frame of time to use the Laptop in the mean while keystroke of Mouse and keyboard is recorded. The system read the dataset and train the model using Dynamic Cat-Boost algorithm (DCB), that act as the classification  model here. The evaluation metrics are framed by calculating Euclidean distance(ED), Manhattan Distance (MahD), and Mahalanobis distance(MD) etc. Quantitative measures of DCB is framed through Accuracy, precision and F1Score.

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Package Includes

Software Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support


The Delivery time for software projects is 2 -3 working days. Some of the software projects will require Hardware interface. Please go through the hardware Requirements in the abstract carefully. The Hardware will take 7-8 Working Days

 

Hardware Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. Datasheets
  6. Circuit Diagrams
  7. Source Code
  8. Screen Shots & Photos
  9. Software Links
  10. Reference Papers
  11. Lit survey
  12. Full Project Documentation
  13. Online support


The Delivery time for Hardware projects is 7-8 working days.

   

Mini Projects: Software Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support

 

The Delivery time for software Miniprojects is 2 -3 working days.

 

Mini Projects - Hardware includes

  1. Demo  Video
  2. Abstract
  3. PPT
  4. Datasheets
  5. Circuit Diagrams
  6. Source Code
  7. Screen Shots & Photos
  8. Software Links
  9. Reference Papers
  10. Full Project Documentation
  11. Online support

The Delivery time for Hardware Mini projects is 7-8 working days.