Recognition of emotions using multimodal physiological signals and an ensemble deep learning model
Z Yin, M Zhao, Y Wang, J Yang, J Zhang - Computer methods and …, 2017 - Elsevier
Abstract Background and Objective Using deep-learning methodologies to analyze
multimodal physiological signals becomes increasingly attractive for recognizing human …
multimodal physiological signals becomes increasingly attractive for recognizing human …
Cross-session classification of mental workload levels using EEG and an adaptive deep learning model
Z Yin, J Zhang - Biomedical Signal Processing and Control, 2017 - Elsevier
Abstract Evaluation of operator Mental Workload (MW) levels via ongoing
electroencephalogram (EEG) is quite promising in Human-Machine (HM) collaborative task …
electroencephalogram (EEG) is quite promising in Human-Machine (HM) collaborative task …
Electro-encephalography and electro-oculography in aeronautics: A review over the last decade (2010–2020)
C Belkhiria, V Peysakhovich - Frontiers in Neuroergonomics, 2020 - frontiersin.org
Electro-encephalography (EEG) and electro-oculography (EOG) are methods of
electrophysiological monitoring that have potentially fruitful applications in neuroscience …
electrophysiological monitoring that have potentially fruitful applications in neuroscience …
Linear and nonlinear analyses of heart rate variability signals under mental load
T Hao, X Zheng, H Wang, K Xu, S Chen - Biomedical Signal Processing …, 2022 - Elsevier
Mental load has an important effect on the efficiency and reliability of human–machine
systems. This study discussed in this paper looked at the heart rate variability (HRV) signal …
systems. This study discussed in this paper looked at the heart rate variability (HRV) signal …
Recognition of mental workload levels under complex human–machine collaboration by using physiological features and adaptive support vector machines
J Zhang, Z Yin, R Wang - IEEE Transactions on Human …, 2014 - ieeexplore.ieee.org
In order to detect human operator performance degradation or breakdown, this paper
proposes an adaptive support vector machine-based method to classify operator mental …
proposes an adaptive support vector machine-based method to classify operator mental …
Operator functional state classification using least-square support vector machine based recursive feature elimination technique
Z Yin, J Zhang - Computer methods and programs in biomedicine, 2014 - Elsevier
This paper proposed two psychophysiological-data-driven classification frameworks for
operator functional states (OFS) assessment in safety-critical human-machine systems with …
operator functional states (OFS) assessment in safety-critical human-machine systems with …
Cross-subject recognition of operator functional states via EEG and switching deep belief networks with adaptive weights
Z Yin, J Zhang - Neurocomputing, 2017 - Elsevier
Assessing operator functional states (OFS) by using neurophysiological signals can provide
continuous prediction of instantaneous human performance in safety-critical human …
continuous prediction of instantaneous human performance in safety-critical human …
Identification of temporal variations in mental workload using locally-linear-embedding-based EEG feature reduction and support-vector-machine-based clustering …
Z Yin, J Zhang - Computer methods and programs in biomedicine, 2014 - Elsevier
Identifying the abnormal changes of mental workload (MWL) over time is quite crucial for
preventing the accidents due to cognitive overload and inattention of human operators in …
preventing the accidents due to cognitive overload and inattention of human operators in …
Pattern classification of instantaneous cognitive task-load through gmm clustering, laplacian eigenmap, and ensemble svms
J Zhang, Z Yin, R Wang - IEEE/ACM transactions on …, 2016 - ieeexplore.ieee.org
The identification of the temporal variations in human operator cognitive task-load (CTL) is
crucial for preventing possible accidents in human-machine collaborative systems. Recent …
crucial for preventing possible accidents in human-machine collaborative systems. Recent …
Data-driven operator functional state classification in smart manufacturing
F Besharati Moghaddam, AJ Lopez, C Van Gheluwe… - Applied …, 2023 - Springer
One of the main challenges in the industry is having trained and efficient operators in
manufacturing lines. Smart adaptive guidance systems are developed that offer assistance …
manufacturing lines. Smart adaptive guidance systems are developed that offer assistance …