Semantic Scholar Open Access 2025

Stress Detection Through Facial Expressions and Personalized Recommendations using Machine

P. S. Kumar K. Swathika D. Teja Soumya Sahoo B. Chanti +1 lainnya

Abstrak

Stress is a widespread issue that tells Mental and physical health, look good Cognitive and functional solutions. This is a job that is done He introduces a system based on deep learning for meditation Insights from facial expressions, pairs Personalized stress reduction tips. Using a FER dataset optimized for stress-specific sensitivity classification, the system allows the user to upload an image or log in in real time. They investigate through their laptop cameras. It has been worked on before Inputs are analyzed using a trained set model by combining Xception with NasNetMobile construction, which made it most accurate In classifying stress and nonstress situations. above By detecting stress, the system provides customized results Suggestions, like movies, music, websites Games and books. Performance descriptions such as Accuracy, recall, and F1 scores were assessed determine the effectiveness of the policies. There are consequences It is determined by the forward-backward correlative interaction,. Make sure they are usable and engaged. This is the whole point. The method enhances users' well-being by simplifying it timely and relieving stress detection.

Penulis (6)

P

P. S. Kumar

K

K. Swathika

D

D. Teja

S

Soumya Sahoo

B

B. Chanti

P

P. Sahana

Format Sitasi

Kumar, P.S., Swathika, K., Teja, D., Sahoo, S., Chanti, B., Sahana, P. (2025). Stress Detection Through Facial Expressions and Personalized Recommendations using Machine. https://doi.org/10.1109/ASSIC64892.2025.11158659

Akses Cepat

Informasi Jurnal
Tahun Terbit
2025
Bahasa
en
Sumber Database
Semantic Scholar
DOI
10.1109/ASSIC64892.2025.11158659
Akses
Open Access ✓