… fNIRS SIGNALS The decision fusion was achieved by fusing the outputs/decisions from two
… The global classifier used in this study for decision fusion is also SVM with RBF kernels. Let …

… In this work, we evaluate emotion in terms of low/high arousal and valence classification
through Supervised Learning (SL), Decision Fusion (DF) and Feature Fusion (FF) techniques …

… decision level fusion to enhance the accuracy of stress levels classification. We also introduce
a dataset with multiple stress … binary levels datasets for stress analysis. Experimental …

… , in [23], we propose a decision level fusion framework. ECG signals are converted into signal
… Finally, decision level fusion is performed on multidomain modalities. In [24], ECG heart-…

… Mental stressors impact involuntary activities such as those … provides an indicator of the ANS
and stress states. Metrics, such as … EEG and fNIRs at the decision fusion level by taking into …

… An adaptive decision fusion method is then proposed to … is evaluated on the Wearable Stress
and Affect Detection dataset … adaptive decision fusion strategies for emotion classification. …

… will be expected to delegate more activities and decisions to automation. In ATC, high demand
… In order to avoid bias in the stress assessment owing to different workload demands, we …

… Decision Fusion technique in health care in the form of a systematic scoping review. It assessed
… review that has assessed the applicability of Decision Fusion in the field of health care. …

… In one study, physiological parameters were used to measure stress (70). In another study,
the … SVM-based multi-sensor fusion for free-living physical activity assessment. Annu Int Conf …

… Stress and mental fatigue are in existence constantly in daily … states of stress and mental
fatigue using data fusion while e-… the game is partly caused by stress and mental fatigue. HRV …