- Bilecik Şeyh Edebali Üniversitesi Fen Bilimleri Dergisi
- Vol: 6 Issue: 1
- A Novel Stress-Level-Specific Feature Ensemble for Drivers’ Stress Level Recognition
A Novel Stress-Level-Specific Feature Ensemble for Drivers’ Stress Level Recognition
Authors : Idil Işikli Esener
Pages : 12-23
Doi:10.35193/bseufbd.554791
View : 13 | Download : 3
Publication Date : 2019-06-28
Article Type : Research
Abstract :This paper proposes a novel feature set for drivers’ stress level recognition. The proposed feature set consists of data-independent and almost uncorrelated feature pairs for each stress level with very strong intra-class and relatively weak inter-class correlations, constructed by realizing a correlation analysis on the popular features studied in the literature. By using the proposed feature set, a maximum of 100% stress level recognition accuracy is achieved with an average increment of 24.85% while a mean reduction rate of 88.01% is satisfied in false positive rate compared to the full feature set. These outcomes clearly show that the proposed feature set can confidently be integrated into the driving assistance systems.Keywords : Stress Recognition, Feature Selection, Feature Correlation