Browsing ODA Open Digital Archive by Author "Zhang, Jianhua"
Now showing items 1-20 of 20
-
Assessing cognitive mental workload via EEG signals and an ensemble deep learning classifier based on denoising autoencoders
Yang, Shuo; Yin, Zhong; Wang, Yagang; Zhang, Wei; Wang, Yongxiong; Zhang, Jianhua (Computers in Biology and Medicine;Volume 109, June 2019, Journal article; Peer reviewed, 2019-04-26)To estimate the reliability and cognitive states of operator performance in a human-machine collaborative environment, we propose a novel human mental workload (MW) recognizer based on deep learning principles and utilizing ... -
Automatic Analysis of Large-scale Nanopore Data Using Hidden Markov Models
Zhang, Jianhua; Liu, Xiuling (IFAC-PapersOnLine;Volume 53, Issue 2, 2020, Peer reviewed; Journal article, 2020-04-14)In this paper we developed a modified Hidden Markov Model (HMM) to analyze the raw nanopore experimental data. Traditionally, prior to further analysis the measured nanopore data must be pre-filtered, but the filtering ... -
Classifying Mental Workload Levels Using Semi-Supervised Learning Technique
Zhang, Jianhua; Li, Jianrong (IFAC-PapersOnLine;Volume 53, Issue 2, Peer reviewed; Journal article, 2021-04-14)Real-time monitoring and analysis of human operator’s mental workload (MWL) is crucial for development of adaptive/intelligent human-machine cooperative systems in various safety/mission-critical application fields. Although ... -
Cross-Subject emotion recognition from EEG using Convolutional Neural Networks
Zhong, Xiaolong; Yin, Zhong; Zhang, Jianhua (Chinese Control Conference (CCC);2020 39th Chinese Control Conference (CCC), Peer reviewed; Journal article, 2020-09-09)Using electroencephalogram (EEG) signals for emotion detection has aroused widespread research concern. However, across subjects emotional recognition has become an insurmountable gap which researchers cannot step across ... -
EEG-based affect classification with machine learning algorithms
Zhang, Jianhua; Yin, Zhong; Chen, Peng (Chapter, 2023)In this paper, we aim to study the EEG-based emotion recognition problem. First, we use clustering algorithm to determine the target class of emotions and perform binary classification of emotion along its arousal and ... -
An ELM-based Deep SDAE Ensemble for Inter-Subject Cognitive Workload Estimation with Physiological Signals
Zheng, Zhanpeng; Yin, Zhong; Zhang, Jianhua (Chinese Control Conference (CCC);2020 39th Chinese Control Conference (CCC), Conference object, 2020-09-09)Evaluating operator cognitive workload (CW) levels in human-machine systems based on neurophysiological signals is becoming the basis to prevent serious accidents due to abnormal state of human operators. This study proposes ... -
EMG Signals based Human Action Recognition via Deep Belief Networks
Zhang, Jianhua; Ling, Chen; Li, Sunan (IFAC-PapersOnLine;Volume 52, Issue 19, 2019, Journal article; Peer reviewed, 2019-12-24)Electromyography (EMG) signals can be used for action classification. Nonetheless, due to their nonlinear and time-varying properties, it is difficult to classify the EMG signals and it is critical to use appropriate ... -
Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review
Zhang, Jianhua; Yin, Zhong; Chen, Peng; Nichele, Stefano (Information Fusion;Volume 59, July 2020, Peer reviewed; Journal article, 2020-01-31)In recent years, the rapid advances in machine learning (ML) and information fusion has made it possible to endow machines/computers with the ability of emotion understanding, recognition, and analysis. Emotion recognition ... -
EvoDynamic: A Framework for the Evolution of Generally Represented Dynamical Systems and Its Application to Criticality
Pontes-Filho, Sidney; Lind, Pedro; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Tufte, Gunnar; Nichele, Stefano (Lecture Notes in Computer Science;Volume 12104, Conference object, 2020-04-09)Dynamical systems possess a computational capacity that may be exploited in a reservoir computing paradigm. This paper presents a general representation of dynamical systems which is based on matrix multiplication. That ... -
Hierarchical MPC of Hybrid Power Systems based on Fuzzy Discrete Abstraction
Zhang, Jianhua; Xia, Jiajun (IFAC-PapersOnLine;Volume 53, Issue 2, 2020, Peer reviewed; Journal article, 2020-04-14)A hierarchical control approach is proposed for hybrid systems with discrete-valued input based on fuzzy discrete abstraction and model predictive control (MPC) scheme. The system is firstly abstracted to a discrete event ... -
Individual-Specific Classification of Mental Workload Levels Via an Ensemble Heterogeneous Extreme Learning Machine for EEG Modeling
Zhang, Jianhua; Tao, J.; Yin, Z.; Liu, L.; Tian, Y.; Sun, Z. (Symmetry;Volume 11, Issue 7, Journal article; Peer reviewed, 2019-07-16)In a human–machine cooperation system, assessing the mental workload (MW) of the human operator is quite crucial to maintaining safe operation conditions. Among various MW indicators, electroencephalography (EEG) signals ... -
Instantaneous mental workload assessment using time–frequency analysis and semi-supervised learning
Zhang, Jianhua; Li, Jianrong; Wang, Rubin (Cognitive Neurodynamics;volume 14, issue 5, Peer reviewed; Journal article, 2020-05-12)The real-time assessment of mental workload (MWL) is critical for development of intelligent human–machine cooper- ative systems in various safety–critical applications. Although data-driven machine learning (ML) approach ... -
Instantaneous Mental Workload Recognition Using Wavelet-Packet Decomposition and Semi-Supervised Learning
Zhang, Jianhua; Li, Jianrong; Nichele, Stefano (IEEE Symposium Series on Computational Intelligence (SSCI);2019 IEEE Symposium Series on Computational Intelligence (SSCI), Conference object, 2020-02-20)The real-time monitoring of human operator's mental workload (MWL) is crucial for development of adaptive/intelligent human-machine cooperative systems in various safety/mission-critical application fields. Although ... -
Manifold feature fusion with dynamical feature selection for cross-subject emotion recognition
Hua, Yue; Zhong, Xiaolong; Zhang, Bingxue; Yin, Zhong; Zhang, Jianhua (Brain Sciences;Volume 11 / Issue 11, Peer reviewed; Journal article, 2021-10-23)Affective computing systems can decode cortical activities to facilitate emotional human– computer interaction. However, personalities exist in neurophysiological responses among different users of the brain–computer ... -
A neuro-inspired general framework for the evolution of stochastic dynamical systems: Cellular automata, random Boolean networks and echo state networks towards criticality
Pontes-Filho, Sidney; Lind, Pedro; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Tufte, Gunnar; Nichele, Stefano (Cognitive Neurodynamics;, Journal article; Peer reviewed, 2020-06-11)Although deep learning has recently increased in popularity, it suffers from various problems including high computational complexity, energy greedy computation, and lack of scalability, to mention a few. In this paper, ... -
Operator Performance Prediction based on Fuzzy Modeling Approach
Zhang, Jianhua; Yin, Zhong (IFAC-PapersOnLine;Volume 53, Issue 2, 2020, Peer reviewed; Journal article, 2021-04-14)In this paper, physiological signals were measured from five participants, each participating in two sessions of experiment with identical experimental procedure. A simulation platform, AutoCAMS (Automation-enhanced Cabin ... -
Physiological-signal-based mental workload estimation via transfer dynamical autoencoders in a deep learning framework
Yin, Zhong; Zhao, Mengyuan; Zhang, Wei; Wang, Yongxiong; Wang, Yagang; Zhang, Jianhua (Neurocomputing;Volume 347, 28 June 2019, Journal article; Peer reviewed, 2019-02-19)Evaluating operator mental workload (MW) in human-machine systems via neurophysiological signals is crucial for preventing unpredicted operator performance degradation. However, the feature of physiological signals is ... -
Prediction and correlation analysis of ventilation performance in a residential building using artificial neural network models based on data-driven analysis
Kim, Moon Keun; Cremers, Bart; Liu, Jiying; Zhang, Jianhua; Wang, Junqi (Sustainable Cities and Society (SCS);Volume 83, August 2022, 103981, Peer reviewed; Journal article, 2022-06-14)This study investigates approaches to evaluate prediction and correlation how significantly mechanical and natural ventilation rate and local weather conditions affect the actual ventilation performance of a residential ... -
Recognition of cognitive load with a stacking network ensemble of denoising autoencoders and abstracted neurophysiological features
Cao, Zixuan; Yin, Zhong; Zhang, Jianhua (Peer reviewed; Journal article, 2020) -
Selection of Optimal EEG Electrodes for Human Emotion Recognition
Zhang, Jianhua; Chen, Peng (IFAC-PapersOnLine;Volume 53, Issue 2, 2020, Peer reviewed; Journal article, 2021-04-14)In recent years, emotion recognition has attracted increasing interest from researchers from diverse fields. Because of their intrinsic correlation with emotions, physiological signals based emotion recognition method is ...