The rapidly changing lifestyles, technological advancements, and hectic work pace of today affect individuals levels of stress and fatigue. In this context, the fatigue detection application we have developed represents a significant step in determining users' fatigue levels. In this regard, our fatigue detection application offers a solution for users to determine and manage their personal fatigue levels.

To calculate the fatigue status, a classification model is employed using emotion recognition through the emotional state model on the user's image obtained from the camera or file. This model also utilizes eye width/height ratio, mouth width/height ratio, and eyebrow distance ratio on the user's face to determine fatigue levels.

How does it work?

• When the photo capture button is pressed, an image can be obtained from the user using the camera.
• When the file upload button is pressed, the user can upload an image from the gallery or their computer.
• The images uploaded from files and captured from the camera are added in a reduced size below the uploaded or captured image on the interface.
• This allows the user to review the results of previously uploaded images at any time retrospectively.