Research Article
[Retracted] Employing Multimodal Machine Learning for Stress Detection
Table 7
Other research works on SWELL-KW dataset, the modalities used, and accuracy scores.
| Research model | Modalities used | Accuracy (%) |
| SVM classifier with RBF kernel [24] | Heart rate variability and physiological data | 92.75 | Fast-GRNN [44] | Heart rate variability and physiological data | 87.87 | Support Vector Machine [27] | Heart rate variability, computer interactions, body posture, and facial features | 90 | Active Bayesian Learning [45] | Heart rate variability and physiological data | 91.92 | Our model | Heart rate variability, computer interactions, body posture, and facial features (with early fusion) | 96.67 |
|
|