| Autor: |
Dibyanshu Jaiswal, Debatri Chatterjee, Rahul Gavas, Ramesh Kumar Ramakrishnan, Arpan Pal |
| Rok vydání: |
2021 |
| Zdroj: |
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). |
| Popis: |
Stress detection is a widely researched topic and is important for overall well-being of an individual. Several approaches are used for prediction/classification of stress. Most of these approaches perform well for subject and activity specific scenarios as stress is highly subjective. So, it is difficult to create a generic model for stress prediction. Here, we have proposed an approach for creating a generic stress prediction model by utilizing knowledge from three different datasets. Proposed model has been validated using two open datasets as well as on a set of data collected in our lab. Results show that the proposed generic model performs well across studies conducted independently and hence can be used for monitoring stress in real life scenarios and to create mass-market stress prediction products. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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