AIMC Topic: Electroencephalography
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Assessing Continuous Operator Workload With a Hybrid Scaffolded Neuroergonomic Modeling Approach.
Human factors
Feb 1, 2017
OBJECTIVE: We aimed to predict operator workload from neurological data using statistical learning methods to fit neurological-to-state-assessment models.
Epileptic seizure detection in EEG signal with GModPCA and support vector machine.
Bio-medical materials and engineering
Jan 1, 2017
BACKGROUND AND OBJECTIVE: Epilepsy is one of the most common neurological disorders caused by recurrent seizures. Electroencephalograms (EEGs) record neural activity and can detect epilepsy. Visual inspection of an EEG signal for epileptic seizure de...
Automatic epileptic seizure detection in EEGs using MF-DFA, SVM based on cloud computing.
Journal of X-ray science and technology
Jan 1, 2017
BACKGROUND: Epilepsy is a chronic disease with transient brain dysfunction that results from the sudden abnormal discharge of neurons in the brain. Since electroencephalogram (EEG) is a harmless and noninvasive detection method, it plays an important...
[A Classification Algorithm for Epileptic Electroencephalogram Based on Wavelet Multiscale Analysis and Extreme Learning Machine].
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Dec 1, 2016
The automatic classification of epileptic electroencephalogram(EEG)is significant in the diagnosis and therapy of epilepsy.A classification algorithm for epileptic EEG based on wavelet multiscale analysis and extreme learning machine(ELM)is proposed ...
[Research of Partial Least Squares Decoding Method for Motion Intent].
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Aug 1, 2016
Due to the sparsity of brain encoding,the neural ensemble signals recorded by microelectrode arrays contain a lot of noise and redundant information,which could reduce the stability and precision of decoding of motion intent.To solve this problem,we ...
[Thalamocortical Neural Mass Model Simulation and Study Based on Field Programmable Gate Array].
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Aug 1, 2016
Using the computer to imitate the neural oscillations of the brain is of great significance for the analysis of brain functions.Thalamocortical neural mass model(TNMM)reflects the mechanisms of neural activities by establishing the relationships betw...
Classification of EEG based-mental fatigue using principal component analysis and Bayesian neural network.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Aug 1, 2016
This paper presents an electroencephalography (EEG) based-classification of between pre- and post-mental load tasks for mental fatigue detection from 65 healthy participants. During the data collection, eye closed and eye open tasks were collected be...
Automatic recognition of pleasant content of odours through ElectroEncephaloGraphic activity analysis.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Aug 1, 2016
This study presents a machine learning approach applied to ElectroEnchephaloGraphic (EEG) response in a group of subjects when exposed to a controlled olfactory stimulation experiment. In the literature, in fact, there are controversial results on EE...
Applicability of SSVEP-based brain-computer interfaces for robot navigation in real environments.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Aug 1, 2016
Brain-computer interfaces have been extensively studied and used in order to aid patients suffering from neuromuscular diseases to communicate and control the surrounding environment. Steady-state visual evoked potentials (SSVEP) constitute a very po...
Automatic seizure detection using correlation integral with nonlinear adaptive denoising and Kalman filter.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Aug 1, 2016
The ability of correlation integral for automatic seizure detection using scalp EEG data has been re-examined in this paper. To facilitate the detection performance and overcome the shortcoming of correlation integral, nonlinear adaptive denoising an...
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